2026-09-19T09:05:36Z https://ejournal.brin.go.id/ijreses/oai

oai:ejournal.brin.go.id:article/6566 2026-01-05T02:46:53Z ijreses:ART

THE EVOLUTION OF AGRICULTURAL LAND AROUND THE SAND MINING AREA FROM 2011 – 2021 IN LELES DISTRICT, GARUT REGENCY, WEST JAVA Damayanti, Astrid Fachrizal, Helmi Rahmat Kintan Maulidina Mining activities can alter land use patterns, including converting agricultural land.  The transformation of agricultural land is occurring at varying rates, whether rapid or gradual.  The evolution of agricultural land may be observed in terms of its shape, area, and land function.  This paper was prepared to determine the evolution of agricultural land due to the expansion of limestone mining in Leles District from 2011 to 2021 to support further research in this area.  The data collection process employed a combination of historical Google Earth images, secondary data, and land farm surveys conducted in Leles District, Garut Regency, from 2011 to 2021.  The images were then assessed to identify land shape, area, and function changes.  Subsequently, the data were subjected to analysis and comparison with existing literature.  The study results demonstrate the evolution of the site and the utilization of agricultural land as a consequence of mining development.  The expansion of the mining area has resulted in the transformation of the surrounding land into agricultural land.  During the observation period, the mining area increased by 98%, while the farming area decreased by 27%. BRIN 2025-04-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/6566 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/6566/8885 Copyright (c) 2025 Astrid Damayanti, Helmi Rahmat Fachrizal, Kintan Maulidina https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/7089 2026-01-05T02:46:53Z ijreses:ART

MARINE CRIME IN INDONESIA: A SPATIO-TEMPORAL ASSESSMENT OF EMERGING TRENDS AND HOTSPOTS Kurniawan, Rahmad Manessa, Masita Dwi Mandini Golkariansyah Wiratama, Eska Yosep Budiman, Asep Indonesia, with its vast maritime domain, faces significant challenges related to maritime crime, including illegal, unreported, and unregulated (IUU) fishing, piracy, human trafficking, and smuggling. The country’s strategic position, bordering key shipping routes like the Strait of Malacca and the Sunda Strait, exacerbates its vulnerability to transnational crimes. This study provides a spatio-temporal assessment of emerging trends and hotspots of marine crime in Indonesia during the period of 2022-2023. Through an analysis of crime incidents, the research identifies key areas of concern, such as the Java Sea, Sumatra, and Eastern Indonesia, where illegal activities have shown persistent and intensifying patterns. The Strait of Malacca and Aceh emerged as critical zones, with increased incidents of piracy and human trafficking, partly linked to the Rohingya refugee crisis. Additionally, the study highlights the environmental impact of illegal activities in ecologically sensitive regions, such as Papua and the Coral Triangle, where illegal logging, mining, and destructive fishing practices threaten marine ecosystems. The analysis also reveals seasonal trends, with the highest concentration of incidents occurring between July and September, coinciding with peak fishing activities. Despite efforts by the Indonesian government, including the Sinking of Foreign Vessels Policy and regional cooperation initiatives like ReCAAP, enforcement gaps remain, particularly in remote regions. The study identifies critical gaps in maritime security, including the need for improved technological surveillance and enhanced community engagement in enforcement efforts. The findings underscore the importance of spatial-temporal monitoring to inform targeted law enforcement and policy responses, thereby protecting Indonesia’s marine resources and enhancing national security. BRIN 2025-04-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/7089 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/7089/8856 Copyright (c) 2025 Rahmad Kurniawan, Masita Dwi Mandini Manessa, Golkariansyah, Eska Yosep Wiratama, Asep Budiman https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/8915 2026-01-05T02:46:53Z ijreses:ART

ASSESSMENT OF GROUND SURFACE DEFORMATION IN BENGKULU CITY INDUCED BY EARTHQUAKES USING DINSAR-BASED REMOTE SENSING IMAGE ANALYSIS Utama, Ferzha Putra Vatresia, Arie Zalbuin Mase, Lindung Faris, Ahmad Bengkulu deformation DInSAR earthquake Sentinel-1 In 2007, Bengkulu city, Indonesia and its surrounding areas experienced a significant earthquake with a magnitude of 8.6 Mw, resulting in extensive damage. Between 2014 and 2022, Bengkulu Province encountered a total of 3469 earthquakes, signifying a heightened frequency of seismic activity in the region. This escalated seismic activity in Bengkulu elicits concerns regarding potential ground surface deformation. To address this, the study utilized DInSAR (Differential Interferometry SAR) technology, employing a blend of satellite images to quantify land surface deformation. Notably, the research made use of three pairs of satellite images for analysis. One pair of ALOS-PALSAR images dated between January 29 and September 16, 2007, was employed to investigate ground surface deformation following the September 12, 2007 earthquake. Additionally, observations were made using two pairs of Sentinel-1 satellite images covering periods from November 3 to 27, 2014, and from June 30 to July 24, 2022, to monitor land surface deformation resulting from earthquakes on November 10, 2014 and July 20, 2022. The study findings depicted uplift deformation reaching 53.4 mm and the highest subsidence measuring -12.8 mm in the ALOS-PALSAR image pair. In the Sentinel-1 image pair between November 3 and 27, 2014, the most notable observed uplift amounted to 38.9 mm, while the greatest subsidence was recorded at -34.8 mm. Lastly, the image pair dated between June 30 and July 24, 2022, exclusively exhibited uplift, with values peaking at 45.2 mm. BRIN 2025-04-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/8915 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/8915/8884 Copyright (c) 2025 Ferzha Putra Utama, Arie Vatresia, Lindung Zalbuin Mase, Ahmad Faris https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/9068 2026-01-05T03:47:39Z ijreses:ART

ASSESSING FUTURE SPATIAL DISTRIBUTION OF THE SEASONAL RAINFALL IN BINTAN ISLANSD USING THE DOWNSCALED CORDEX-SEA MODELS Narulita, Ida Dwita Sutjiningsih Eko Kusratmoko Muhamad Rahman Djuwansah Faiz Rohman Fajary Widya Ningrum Keywords: Future-rainfall, probability, CORDEX_SEA, Climate-change Sustainable water resource management must consider climate change to minimize climate disasters. The water resources of Bintan island are limited, although rainfall is quite high, but the small catchment area and the component rocks of the island of Bintan have low water retention capacity. Currently, Bintan Island is experiencing an increase in water needs due to population growth and economic activities. Therefore, understanding changes in seasonal rainfall in the future is important on this island. This paper aims to study the chances of future seasonal rainfall variability using long-term projection climate modeling. Currently, a high-resolution climate model is available for historical and future periods, namely CORDEX-SEA for the Southeast Asia region. Because the study area is a small island with an area of around 1170 km2, the resolution of the CORDEX-SEA projection climate model data is insufficient. This study uses a statistical downscaling method with quantile mapping to detail the spatial resolution. The results of the analysis show that rainfall on Bintan Island is likely to change in the future due to climate change. Rainfall in Bintan Island in the future will likely be below normal rainfall in all seasons, except in the northern part of Bintan in the SON season. The greatest posibility of rainfall is below normal rainfall in the JJA season. The analysis results show that the eastern part of Bintan Island is a suitable area to build a water reservoir for managing water shortages in Bintan island caused by potentially decreasing rainfall in the future. BRIN 2025-07-23 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/9068 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/9068/10184 Copyright (c) 2025 Ida Narulita, Dwita Sutjiningsih, Eko Kusratmoko, Muhamad Rahman Djuwansah, Faiz Rohman Fajary, Widya Ningrum https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/11217 2026-01-05T03:39:24Z ijreses:ART

ASSESSING THE PERFORMANCE OF DETERMINISTIC PRECIPITATION NOWCASTING ALGORITHMS WITH WEATHER RADAR DATA AND MULTIMETRIC VERIFICATION Ali, Abdullah weather radar deterministic nowcasting ROC Taylor Diagram Target Diagram This study assesses the performance of four deterministic radar-based nowcasting algorithms—LINDA, SPROG, ANVIL, and Extrapolation—using C-band weather radar data located at Tangerang. Forecasts were generated with the pysteps library and verified up to +96 minutes using spatial inspection, ROC analysis, and Taylor/Target diagrams. At short lead times (+8 to +24 minutes), all algorithms achieved high discrimination skill (AUC > 0.90), with SPROG and LINDA reaching peak AUC values of 0.96 and 0.95, respectively. Beyond +56 minutes, LINDA maintained the highest AUC (0.64), while SPROG and Extrapolation dropped below 0.60. Statistical verification showed that LINDA consistently preserved rainfall structure with correlation coefficients ≥ 0.80 at short range and ~0.65 at +80 minutes. Target diagrams indicated low bias (< ±0.1) and uRMSD stability for LINDA, while SPROG exhibited increasing overdispersion and structural error. Spatially, LINDA captured convective growth and peak intensities more realistically than other methods. These results demonstrate that LINDA offers the most balanced and skillful performance across metrics, especially in maintaining accuracy during medium-range forecasts. The findings support its operational suitability for nowcasting convective rainfall in tropical regions. BRIN 2025-07-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/11217 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/11217/10164 Copyright (c) 2025 Abdullah Ali https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/11405 2026-01-05T03:03:58Z ijreses:ART

GLOBAL HORIZONTAL IRRADIANCE ESTIMATION IN TROPICAL TERRAIN USING SEMI-EMPIRICAL APPROACH: A SEASONAL ASSESSMENT IN WEST JAVA, INDONESIA Garniwa, Pranda Mulya Azzahra, Rifdah Octavi Dimyati, Muhammad Solar irradiance Semi-empirical Topography Estimation Tropical Region Accurate estimation of solar irradiance is essential for optimizing solar energy planning, particularly in tropical regions like Indonesia, where observational infrastructure is limited and atmospheric conditions are highly variable. This study addresses the challenge by applying the Perez semi-empirical model to estimate Global Horizontal Irradiance (GHI) across West Java, a topographically diverse province with seasonal weather dynamics. The model integrates satellite-based reflectance data from the GK2A satellite and atmospheric parameters from AERONET, using a spatial resolution of 0.5 km. GHI estimation was conducted for four tropical seasonal phases: the rainy season, transition to dry, dry season, and transition to rainy. Model validation was performed using hourly GHI measurements from two BMKG stations in Indramayu. The Perez model showed strong performance, with RMSE ranging from 146.96 to 163.52 W/m² and relative RMSE below 38%. The results indicate that the model reliably captures both seasonal and spatial variations of solar radiation under tropical atmospheric conditions. Spatial analysis reveals a consistent pattern: lowland and coastal areas receive significantly higher GHI compared to highland regions, which are affected by cloud formation and orographic effects. These findings confirm the model’s suitability for tropical solar forecasting and offer valuable insights for identifying high-potential zones for photovoltaic development. BRIN 2025-07-15 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/11405 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/11405/10163 Copyright (c) 2025 Pranda Mulya Garniwa, Rifdah Octavi Azzahra, Muhammad Dimyati https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13244 2026-01-05T03:01:01Z ijreses:ART

ILLEGAL OIL MINING DETECTION THROUGH REMOTE SENSING IN MUSI BANYUASIN REGENCY, SOUTH SUMATRA, INDONESIA Setiadi, Restu Supriatna Dimyati, Muhammad Arsyad, Ibrahim illegal oil mining remote sensing DJI Phantom 4 spatial analysis Musi Banyuasin Illegal oil mining activities present significant environmental, economic, and regulatory challenges, particularly in resource-abundant regions that are difficult to monitor such as Musi Banyuasin Regency in South Sumatra. This study applied an integrated method that combines drone-based remote sensing, visual interpretation, and spatial statistical analysis to detect, map, and evaluate the spatial distribution of illegal shallow oil wells. High-resolution aerial imagery was acquired using DJI Phantom 4 Pro drones, processed into orthomosaic images, and interpreted visually to identify suspected well locations. A total of 2664 illegal oil wells were identified and georeferenced. The results of spatial autocorrelation analysis using Moran’s I indicated a clustered distribution pattern, with significant concentrations found in subdistricts such as Lawang Wetan, Batang Hari Leko, and Tungkal Jaya. The Moran’s I index value of 0.652075 confirmed a statistically significant spatial clustering. Ground validation was conducted through direct field surveys, which verified the presence of the wells and provided supporting photographic documentation and GPS coordinates. The dataset was also compared with official records of legal oil wells to ensure accuracy and distinction between legal and illegal infrastructure. The findings demonstrate that unmanned aerial vehicle-based spatial analysis offers a reliable and scalable solution for monitoring unregulated extraction activities. This approach supports data-driven enforcement, enhances environmental oversight, and informs the development of more effective regulatory policies in regions impacted by informal oil production. BRIN 2026-01-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13244 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13244/11493 Copyright (c) 2025 Restu Setiadi, Prof. Supriatna, Prof. Dimyati, Dr. Ibrahim https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13466 2026-01-05T03:36:52Z ijreses:ART

RANDOM FOREST CLASSIFICATION FOR MANGROVE CANOPY COVER SPATIAL ANALYSIS IN BENOA BAY – BALI, INDONESIA Nanin Noverita Dian Takarina Ratih Dewanti Dimyati Dwi Nowo Martono Evi Frimawaty Rahmadi A. A. Md. Ananda Putra Suardana classification; Random Forest; mangrove; Benoa Bay Mangroves play a crucial role in maintaining the stability of coastal ecosystems by providing habitats for diverse species, protecting shorelines from erosion, and acting as a carbon sink. The importance of conserving and developing mangrove areas can be effectively monitored using remote sensing data and classification methods, such as Random Forest (RF), ensuring an accurate assessment and management of these vital ecosystems. This research aims to develop and evaluate an RF classification model to produce accurate spatial information on mangrove canopy cover. The research area, Benoa Bay in Bali, Indonesia, is known for its dynamic and ecologically complex mangrove habitats. The inputs for RF classification are bands on Sentinel-2A satellite imagery, Mangrove Vegetation Index (MVI), Normalized Difference Vegetation Index (NDVI), Enhanced Mangrove Index (EMI), Modified Normalized Difference Water Index (MNDWI), Normalized Difference Moisture Index (NDMI), and the Normalized Difference Salinity Index (NDSalI), along with topographic variables such as elevation and slope. Model validation was conducted using high-resolution imagery from Google Earth Pro and cross-referenced with the 2024 National Mangrove Map. The classification of coastal land cover is divided into water bodies, mangroves, open land, built-up land, and non-mangrove vegetation, with an overall accuracy of 0.98 and a kappa statistic of 0.98. In contrast, the accuracy of the classification of mangrove canopy cover concerning the national mangrove map produces an overall accuracy of 0.97 and a kappa value of 0.86. These findings demonstrate the robustness of the RF model and its potential for supporting data-driven coastal management practices. BRIN 2026-01-05 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13466 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 2 (2024) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13466/11509 Copyright (c) 2025 Nanin, Noverita Dian Takarina, Ratih Dewanti Dimyati, Dwi Nowo Martono, Evi Frimawaty, Rahmadi, A. A. Md. Ananda Putra Suardana https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13539 2026-02-22T07:01:08Z ijreses:ART

Land Use/Land Cover Changes Using Landsat Imagery in The Upper Citarum Watershed, West Java, Province, Indonesia Marko, Kuswantoro Sutjiningsih, Dwita Kusratmoko, Eko Adi Prakoso, Widjojo LULC Landsat Imagery remote sensing GIS Upper Citarum Watershed The growth of the population and its activities, especially in the Upper Citarum Watershed (UCW) since the last decade has changed the condition of land that was originally vegetated into built-up land. Uncontrolled land use/land cover (LULC) changes in this watershed will certainly have an ecological and hydrological impact. Moreover, this watershed has a very vital role as a provider of agricultural products and water sources in three large reservoirs on the Java island, i.e. the Saguling, Cirata, and Jatiluhur reservoirs. The existence of these three reservoirs is very reliable in supplying electrical energy for the islands of Java and Bali. This study aims to determine changes in LULC over the last 30 years period (1990-2020). LULC information was obtained from analysis of Landsat imagery in 1990, 2000, 2010 and 2020. Supervised classification methods based on remote sensing and geographic information systems were applied to identify types and changes in LULC, i.e. forests, rice fields, dry farm land, bush-grass, mixed gardens, built-up land, and water bodies. The results showed that during the last 30 years there was a fairly high increase on built-up land (+16.4%), and a fairly high decrease in rice fields (-11.5%). The high increase in the ​​built-up land from 1990 to 2020 is indicated by the high level of land conversion from rice fields and dry land farming. The area of ​​natural LULC such as forest has decreased by -3.2% or about 5,705 ha in the last 30 years. The results of this study are expected to be a reference for the government and environmentalists so that efforts to prevent environmental damage can be carried out early on. BRIN 2026-02-22 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13539 International Journal of Remote Sensing and Earth Sciences; Vol. 22 No. 1 (2025) 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13539/11894 Copyright (c) 2026 Kuswantoro Marko, Dwita Sutjiningsih, Eko Kusratmoko, Widjojo Adi Prakoso https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13676 2025-11-25T04:22:56Z ijreses:ART

COMPARATIVE ACCURACIES USING MACHINE LEARNING MODELS FOR MAPPING OF SUGARCANE PLANTATION BASED ON SENTINEL-2A IMAGERY IN KEDIRI AREA, EAST JAVA Ridson Al Farizal Pulungan Rani Nooraeni remote sensing CART SVM RBF kernel SVM polynomial kernel Random Forest XGBoost LightGBM Data collection in smallholder sugarcane plantations is still very sensitive to the subjectivity of informants and data collectors. In the meantime, the problem with data collection on sugarcane plantation companies is a low response rate. This situation can reduce the precision of the estimates that are produced. Consequently, the goal of this research is to recognize sugarcane fields using the machine learning models on Sentinel-2A satellite imagery in Kediri Area that covering Kediri Regency and Kediri Municipality, East Java. Along with developing machine learning algorithms, this research will evaluate how well LightGBM performs when compared to other algorithms, including CART, SVM, Random Forest, and XGBoost. Each model employed hyperparameter tuning with random search and stratified 10-fold cross validation to avoid overfitting. The process of labelling satellite imagery using images from Google Street View, then predictor variables used are NDVI, NDWI, NDBI, EVI, and elevation. The most accurate classification model obtained was LightGBM, with a 98% accuracy and a cohen’s kappa of 97.7%. The estimated area of sugarcane plantations in the Kediri Regency and Kediri Municipality in September 2022 is 18,897.6 ha and 571.87 ha.  BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13676 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 1-14 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13676/10638 Copyright (c) 2024 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13679 2025-11-25T04:22:56Z ijreses:ART

SPATIAL TEMPORAL ANALYSIS OF LAND USE CHANGES IN AREAS VULNERABLE TO EARTHQUAKES AND LANDSLIDES, (Case Study: Cianjur Regency) Marwah Noer Ayu Mardalena Yulia Indri Astuty Rahmadi Masita Dwi Mandini Manessa land use earthquakes landslides cianjur regency Cianjur Regency is a regency that is vulnerable to earthquakes and landslides. This is because the Cianjur Regency is crossed by the Cimandiri Fault which is actively moving. Meanwhile, the population growth rate in Cianjur district has increased based on data from Badan Pusat Statistik (BPS) for 2020-2021. Population growth causes many problems, especially the problem of space. Built-up land will be higher as the population increases. This study uses the temporal spatial analysis method of land use with variables of land use in 2013 and 2022, Earthquake Vulnerability Index, and Landslide Vulnerability Index. This variable was obtained based on the processing of Landsat 8 Satellite Imagery data in 2013 and 2022 and disaster vulnerability raster data from Badan Nasional Penanggulangan Bencana (BNPB). The results of this study are a temporal spatial analysis of changes in land use from 2013 - 2022 for earthquake-vulnerable areas and landslide-vulnerable areas. Changes in the use of built-up land to the Landslide Vulnerability Index experienced an increase in area in all categories. In contrast, the Earthquake Vulnerability Index only experienced an increase in the medium and high categories. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13679 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 15-27 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13679/10639 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13683 2025-11-25T04:35:06Z ijreses:FP

Front Pages IJReSES Vol. 19, No. 2 (2022) Journal Manager Front Pages IJReSES Vol. 19, No. 2 (2022) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13683 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); I-X 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13683/10643 Copyright (c) 2022 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13684 2025-11-25T04:22:20Z ijreses:FP

Front Pages IJReSES Vol. 20, No. 1 (2023) Journal Manager Front Pages IJReSES Vol. 20, No. 1 (2023) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13684 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); I-V 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13684/10644 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13686 2025-11-25T04:22:56Z ijreses:ART

UTILIZATION OF GEOGRAPHIC INFORMATION SYSTEM BASED ON UNMANNED AERIAL VEHICLE (UAV) FOR DETAILED MAPPING OF SRIWEDARI CULTURAL HERITAGE COMPLEX IN SURAKARTA CITY Dewi Novita Sari Tri Cahyo Utomo Muhammad Doriski 3D Cultural Heritage Mapping GIS Photogrammetry Application UAV Sriwedari cultural heritage complex in the City of Surakarta, Middle Java, is one of the buildings from the golden era of Keraton Kesunanan of Surakarta. Sriwedari park was built as a recreation area, entertainment, and recreation place for the Keraton family, which is why it’s called “Kebon Rojo” (Park of King). Besides being a park, there are a couple of other cultural heritage buildings like Radya Pustaka museum, Wayang Orang Building, Sriwedari Stadium, and Segaran. According to the Ministry of Education and Culture Republic of Indonesia, Sriwedari has become a kind of cultural heritage in the form of sites. The purpose of this research (1) Utilization of spatial based technology using a Geographic Information System that can map in detail the location of cultural heritage with the data sources from the Unmanned Aerial Vehicle (UAV) complete with the coordinate position and supporting information; (2) 3D Visualization using GIS-based software for distributive functional communication media that is communicative for the people. There are three stages of methods in this research. First, license/permission and collecting coordinate data (Ground Control Point) GCP, data of object distance in the field, and other information related to functions of every building. Second, UAV data processing uses spatial-based software, Agisoft Photoscan, and ArcGIS. Third, 3D and 2D map visualization about the building detail, function, and other information is available at Sriwedari Cultural Heritage Complex. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13686 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 28-36 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13686/10646 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13688 2025-11-25T04:22:20Z ijreses:ART

THE SPATIO-TEMPORAL DYNAMIC IN WATER NEAR PALABUHAN RATU COAL FIRE PLANT, SUKABUMI, WEST JAVA Niken Anissa Putri Masita Dwi Mandini Manessa Hafid Setiadi spatial-temporal river water quality seawater quality palabuhanratu Indonesia Power PLTU Jabar 2 Palabuhanratu's activities have an impact on the quality of the surrounding river water and ocean. Monitoring the quality of the water thereafter became an important factor. Using remote sensing technologies, the spatial and temporal sea surface temperature and chlorophyll-a of water can be determined. This study aims to (1)  ; (2)  ; and (3)  . River water and ocean quality, including physical parameters (total dissolved solids, electrical conductivity, and temperature) and chemical parameters (pH and salinity). (1) River water and saltwater quality in the Cimandiri Downstream River and Batu Bintang Beach are suitable with regard to physical parameters (total dissolved solids, electrical conductivity, and temperature) and chemical parameters (pH and salinity). (2) According to Health Ministerial Regulation No. 32/2017 and Government Regulation No.22/2021, the river and seawater quality in the Cimandiri Downstream River and Batu Bintang Beach for clean water is adequate in terms of physical characteristics (total dissolved solids, electrical conductivity, and temperature) and chemical parameters (pH and salinity). (3) The average Salinity from August through November of 2021 was 20.76 ppt, 16.25 ppt, 15.76 ppt, and 18.51 ppt. The average Salinity between April and July of 2022 was -2.74 ppt, 3.51 ppt, 0.51 ppt, and 4.25 ppt.   BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13688 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 1-7 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13688/10645 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13689 2025-11-25T04:35:06Z ijreses:ART

PLATFORM REEF LAGOON DETECTION FROM SENTINEL-2 IN PANGGANG ISLAND AND SEMAKDAUN ISLAND Wikanti Asriningrum Azura Ulfa Kholifatul Aziz Kuncoro T. Setiawan Dyah Pangastuti Sentinel-2 lagoon platform reef Panggang Island Semakdaun Island Processing of satellite image data for the detection of platform reef lagoons is intended as one of the geo-physical parameters of the reef landform. Panggang Island and Semakdaun Island were chosen to make the detection model because they are ideal for lagoon reef landforms and tapulang court reefs. This model is only valid in the continental shelf area and the back arc and small island tectonic type. Determination of this location is done to improve the accuracy of spectral-based data processing. Platform reefs are one of four classes of reef landforms. Sentinel-2A data with a spatial resolution of 10m, blue, green, red, and near infrared bands were selected to investigate their ability to detect lagoons. Processing of data by calculating the Optimum Index Factor (OIF) to produce a composite image and drawing transect lines to produce pixel values and spectral graphics of the lagoon. The results of data processing in the form of graphs, composite images and pixel values were built to realize a digital lagoon detection model. These results are used for lagoon growth stage analysis for the classification of three reef platform landforms, visually and digitally interpretation. This digital and visual detection system design is useful for monitoring coral reef ecosystems. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13689 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 101-118 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13689/10647 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13690 2025-11-25T04:22:20Z ijreses:ART

TEA PLANTATION MAPPING USING UAV MULTISPECTRAL IMAGERY Dedi Septyadi Enrico Gracia Riza Putera Syamsuddin tea plantation mapping OBIA spatial analysis vegetation index UAV Tea is one of Indonesia’s most famous commodities, which is dominantly planted on the Java Island of Indonesia. Tea is one of the leading sources of exports, and the Indonesian government is very concerned about the stability of their export commodity sustainability. Therefore, monitoring and evaluating its sustainability and availability become necessary. One of the solutions to the tea plantation monitoring and management program is mapping through remote sensing and GIS. In this study, high-resolution multispectral imageries are captured from a UAV and used to map the tea plantation with three vegetation indexes (VIs). An Object-Based Image Analysis (OBIA) is used to classify the tea field’s condition based on spectral characteristics. The results of this study are: (i) high-resolution multispectral imageries can be used to map the tea plantation with different VIs, and (ii) SAVI is the best VI to map the tea plantation since it has the lowest RMSE value with observed data. Hopefully, this study can support the government program on their export commodity with valuable baseline information on the tea plantation. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13690 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 8-15 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13690/10648 https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13692 2025-11-25T04:22:56Z ijreses:ART

THE EFFECT OF LEAF AREA INDEX CHANGES ON LAND SURFACE TEMPERATURE IN WEST KALIMANTAN Aprilina Aprilina Riza Adriat Laras Toersilowati Leaf Area Index Land Surface Temperature Terra-MODIS West Kalimantan, located along the equator, is a tropical area with high surface temperatures. Decreasing forests or green spaces in this region could endanger the creatures living there, due to rising surface temperatures. Hence, analyzing the impact of Leaf Area Index changes on soil surface temperature is vital. This research employed remote sensing technology via the Terra-MODIS satellite to analyze this impact. The satellite imagery was used to determine Leaf Area Index (LAI) and Land Surface Temperature (LST), using image data from 2001 and 2021 in West Kalimantan Province. The research revealed that the region underwent changes, with wide pine forests being replaced by savanna land. The surface temperature value with the largest distribution area remained between 25ᵒC to 30ᵒC in both 2001 and 2021. LAI changes affected LST by 46% to 47%, but substantial changes require a significant number of years to observe. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13692 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 37-44 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13692/10649 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13693 2025-11-25T04:35:06Z ijreses:ART

DETECTION OF WATER-BODY BOUNDARIES FROM SENTINEL-2 IMAGERY FOR FLOODPLAIN LAKES Azura Ulfa Fajar Bahari Kusuma A. A. Md. Ananda Putra Suardana Wikanti Asriningrum Andi Ibrahim Lintang Nur Fadlillah Lake Floodplain Remote Sensing OBIA Water Bodies The impact of climate and human interaction has resulted in environmental degradation. Consistent observations of lakes in Indonesia are quite limited, especially for flood-exposure lake types. Satellite imagery data improves the ability to monitor water bodies of different scales and the efficiency of generating lake boundary information. This research aims to detect the boundaries of flood-exposure type lake water bodies from the detection model and calculate its accuracy in Semayang Melintang Lake using Sentinel-2 imagery data. The characteristics of water, soil, and vegetation objects were investigated based on the spectral values of the composite image bands from the Optimum Index Factor (OIF) calculation, to support the lake water body boundary detection model. The Object-Based Image Analysis (OBIA) method is used for water and non-water classification, by applying the machine learning algorithms random forest (RF), support vector machine (SVM), and decision tree (DT). Model validation was conducted by comparing spectral graphs and lake water body boundary model results. The accuracy test used the confusion matrix method and resulted in the highest accuracy value in the SVM algorithm with an Overall Accuracy of 95% and a kappa coefficient of 0.9. Based on the detection model, the area of Lake Semayang Melintang in 2021 is 23392.30 ha. This model can be used to estimate changes in the area of the flood-exposure lake consistently. Information on the boundaries of lake water bodies is needed to control the decline in the capacity and inundation area of flood-exposure lakes for management and monitoring plans. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13693 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 199-132 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13693/10650 Copyright (c) 2022 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13694 2025-11-25T04:22:20Z ijreses:ART

ANALYSIS OF TSUNAMI EVACUATION ROUTE PLANNING IN KULON PROGO REGENCY Bernadeta Aurora Edwina Kumala Jati Muhammad Falakh Al Akbar Tri Wahyuni Ernani Uswatun Khasanah Amelia Rizki Gita Paramanandi Hubertus Ery Cantas Pratama Sutiono Dwiana Putri Setyaningsih Wirastuti Widyatmanti Totok Wahyu Wibowo tsunami evacuation route Least Cost Path Situated on the southern coast of Java Island, Kulon Progo Regency is prone to tsunami hazards since it directly faces the subduction zone of the Eurasian Plate and the Indo-Australian Plate. The road condition on the coast of Kulon Progo Regency, which extends from east to west, can be an obstacle in the evacuation process if there is no proper evacuation route planning. Total population in the study area reached 149,574 people. Therefore, it is essential to plan an evacuation route in the coastal area of Kulon Progo Regency. This study proposes the tsunami evacuation route and evaluates it with field conditions on the coast of Kulon Progo Regency. The evacuation route was built using Multi-Criteria Based Least Cost Path Analysis, which uses road network, land use, and slope data as parameters. The least cost path analysis for determining the evacuation route was carried out in 2 scenarios, namely for vehicles and pedestrians. The results of the least cost path analysis of the vehicle scenario are considered less suitable because the results are more through land use and away from the road network. The pedestrian evacuation scenario is more in line with reality because it produces a path adjacent to the road network so that it can be passed either by vehicle or pedestrian.   BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13694 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 16-25 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13694/10652 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13696 2025-11-25T04:22:56Z ijreses:ART

UTILIZATION OF SPOT 6/7 AND LANDSAT TO ANALYZE OPEN GREEN SPACE AND BUILT AREA IN SURABAYA CITY Mohammad Ardha Nurwita Mustika Sar Mukhoriyah Open Green Space NDVI NDBI SPOT Remote Sensing The migration of people from rural to urban areas is a common phenomenon nowadays. One of the goals of urbanization is in the city of Surabaya. The increase in population causes the need for housing and the need for life to increase. One of the many changes in land use is the change of land into built-up land. The increase in the area of built-up land currently raises a new phenomenon where the area of open space is reduced due to changes in land use, one of the changes in land use is from green open space to built-up land. This study aims to see the extent to which the growth trend of green open space and built-up land in the city of Surabaya by using the NDVI method to see the trend of changes in green open space in the city of Surabaya and NDBI for the land built in the city of Surabaya. The data used in this study are SPOT 7 images for green open space and Landsat 8 for built land. Based on this method, green open space in the city of Surabaya in 2015 was 29.19%, in 2016 it was 21.22%, then in 2017 it was 24.54 %, and in 2018 it was 27.60%. While for Built land in 2015, it was 26.43%, in 2016 it was 26.44%, in 2017 it was 30.99% and in 2018 it was 42.88%. Other results were also obtained for the change of green open space into the land. awakened has increased every year, namely from 2015 to 2016 by 2.67%, from 2016 to 2017 by 4.43%, and from 2017 to 2018 by 8.08%. As for the land built into green open space, namely 2015 to 2016 of 2.01%, 2016 to 2017 of 2.84%, 2017 to 2018 of 2.72%. The conclusion from this activity is that NDVI can be used to see the level of vegetation density which can indicate the existence of green open space in urban areas. And NDBI can show the existence of built-up land. The city of Surabaya, has stable green open space, while the built land continues to increase every year. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13696 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 45-53 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13696/10651 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13697 2025-11-25T04:35:06Z ijreses:ART

SPATIAL MACHINE LEARNING FOR MONITORING TEA LEAVES AND CROP YIELD ESTIMATION USING SENTINEL-2 IMAGERY, (A Case of Gunung Mas Plantation, Bogor) Dini Nuraeni Masita Dwi Mandini Manessa GeoAI Sentinel-2 machine learning crop tea yield estimation Indonesia's tea production and export volume have fluctuated with a downward trend in the last five years, partly due to the increasingly competitive world tea quality. Crop yield estimation is part of the management of tea plucking, affecting tea quality and quantity. The constraint in estimating crop yields requires technology that can make the process more effective and efficient. Remote sensing technology and machine learning have been widely used in precision agriculture. Recently, big data processing, especially remote sensing data, machine learning, and deep learning have been carried out using a cloud computing platform. Therefore, we propose using GeoAI, a combination of Sentinel-2A imagery, machine learning, and Google Collaboratory, to predict ready for plucking tea leaves at optimal plucking time at Gunung Mas Plantation Bogor. We used selected bands of Sentinel-2A and extracted more features (i.e., NDVI) as a training set. Then we utilized the tea blocks boundary and tea plucking data to generate labels using Random Forest (RF) and Support Vector Machine (SVM). The classification results were further used to estimate the production of crop tea yield. The RF classifier is able to achieve overall accuracy at 51% and SVM at 54%. Meanwhile, accuracy at optimally aged tea blocks is able to achieve at 75.62% for RF and 52.88% for SVM. Thus, the SVM classifier is better in terms of overall accuracy. Meanwhile, the RF classifier is superior in predicting ready for plucking tea at optimally aged tea blocks. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13697 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 133-142 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13697/10653 Copyright (c) 2022 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13698 2025-11-25T04:22:55Z ijreses:ART

HYDRODYNAMICS MODELING IN KENDARI BAY, SOUTHEAST SULAWESI, INDONESIA Imalpen Imalpen Tri Prartono Rastina Alan Frendy Koropitan Amir Yarkhasy Yuliardi 2D hydrodynamic model flow velocity kendari bay sea level elevation wanggu river Kendari Bay is coastal water in the center of the capital city of Southeast Sulawesi province. It is shaped like a pocket with a narrow mouth and there is an estuary of a large river, namely the Wanggu river, which makes the dynamics of its waters very interesting to study. The focus of the study is the hydrodynamic factors in the Kendari Bay and Wanggu River areas. This study aims to examine the hydrodynamic conditions of Kendari Bay, mainly due to the existence of reclamation and the influence of the Wanggu River which has not been studied previously. This research method uses a two-dimensional model based on bathymetric data, tides, and the flow of the Wanggu River with a simulation time of 15 days (1 March to 15 March 2020). The modeling results were then verified with PUSHIDROSAL tidal elevation data showing an RMSE value of 0.07 indicating that the model was well constructed. The mixed tidal type with a tendency to double daily is the tidal type of Kendari Bay waters based on the Formzahl number value of 0.51. The current pattern generally moves in and out from east to west and vice versa with a varying elevation range following spring conditions of 1.75 m. The maximum tidal speed is 0.1784 m/s and the minimum value is 0.0057 m/s which is shown in the sample results of the model when the hing to low tide, and low to high tide. The results of the hydrodynamic modeling show that the current velocity increases when passing through a narrow path, namely the bay estuary and river estuary. The existence of the reclamation area affects the changes in the velocity of the current which is significantly larger and the direction of the current that undergoes a deflection follows the shape of the reclamation area. The current direction is to the southeast and then turns towards the northeast when low to high tide and eastward then turns towards the northeast when the high to low tide spring conditions compared to research before the reclamation BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13698 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 54-65 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13698/10654 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13700 2025-11-25T04:35:06Z ijreses:ART

ENHANCING COASTAL DISASTER MITIGATION MEASURES: VEGETATION BASED FEASIBILITY STUDY FOR SOUTHERN JAVA, INDONESIA Adiguna Rahmat Nugraha Jason R. Parent tsunami coastal protection Pangandaran District mitigation Indonesia is a country that is prone to disaster especially earthquake and volcanic eruption because its located in the ring of fire. The type of disasters can produce another type of disaster which is: tsunami.  The nature of tsunamis that were hard to predict and arrive with little warning, Indonesians can minimize the effect of tsunami by creating coastal protection. In this study we look for the location to create the coastal forest as an enhancement of the mitigation effort. We conducted our study in the Pangandaran district as were a severe tsunami in the 2006 that caused more than 400 deaths. We conducted a suitability analysis to identify tsunami prone area based on the following criteria: should be had elevation <10m, slope gradient <2%, within proximity of 500m from coastline, and <100m from river and should be settlement or urban area. The creation of vulnerability map was using map algebra to calculate the weighted parameter from each class. Based our analysis using GIS analysis, the most vulnerable area in the Pangandaran district is the bay area, where we founded 1,419 acres of coastal area for which coastal forests could be planted to enhance protection against tsunamis.  BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13700 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 143-152 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13700/10655 Copyright (c) 2022 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13702 2025-11-25T04:22:55Z ijreses:ART

PREDICTIVE MAPPING OF CRITICAL LAND IN BENGAWAN SOLO WATERSHED: AN INTEGRATED APPROACH USING LANDSAT IMAGERY AND TERRAIN ANALYSIS Nirmawana Simarmata Dewi Nawang Sari Annisha Bunga Fathya M Sri Harta Critical Land Random Forest Landsat Bengawan Solo Inappropriate land use can have negative impacts, increasing the risk of land becoming critical. Managing critical land and growing human needs is essential to balance land and water resources. This research aims to map necessary land in the Bengawan Solo watershed. The research method integrates remote sensing and geographic information system (GIS) methods. Critical land analysis was conducted based on the Regulation of the Director General of Watershed and Protected Forest Control Number P.3/PDASHL/SET/KUM.1/7/2018, which is used as a reference in determining whether land is categorized as critical land. The regulation uses 4 (four) variables in its processing: land cover variables, slope, erosion hazard level, and forest area. The study results show land criticality in the Bengawan Solo watershed in 2023. Most areas have low slopes (0-8%), considered non-critical, covering 30.50% of the total area. In contrast, the Potentially Critical category (8-15%) dominates with 45.94% of the area, indicating potential risks in moderately steep areas. Areas with steeper slopes fall into the Critical (10.29%) and Very Critical (2.68%) categories. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13702 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 66-82 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13702/10657 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13703 2025-11-25T04:35:05Z ijreses:ART

MAPPING THE AIR MOISTURE CHANGE IN UNDER CANOPY TREES USING A HEMISPHERICAL AND AERIAL PHOTOGRAPH BASED ON MACHINE LEARNING APPROACHES Mochamad Firman Ghazali hemispherical photography trees canopy air humidity spatial distribution aerial photograph The essential roles of trees in controlling the local climatic variation, such as air moisture, are still interesting to observe. Therefore, this study must deliver knowledge of the benefits of growing trees and enhance people's awareness of climate change adaptation. Here, the analysis requires several data fields such as hemispherical photography, an aerial photograph of a UAV, and air temperature collected using a wet and dry bulb thermometer, which has converted to air moisture. All these are considered to understand the air moisture change under the trees' canopy during a day observation. The hemispherical photography and aerial photograph of a UAV are processed to measure the tree's canopy size and then used together with interpolated air moisture to map the variation in air moisture distribution in under-canopy trees using random forest (RF) and Artificial Neural Network (ANN). The result shows that hemispherical photography describes the ability to control the air moisture change. As its size increases, the air moisture level tends to be higher. It was maintained at more than 70% compared to the area with lower canopy cover. This characteristic is similar to the pattern shown by the RF and ANN. However, the SVM has better results as it can separate air humidity in vegetated and non-vegetated areas. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13703 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 153-166 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13703/10658 Copyright (c) 2022 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13705 2025-11-25T04:22:19Z ijreses:ART

AUTOMATION OF DAILY LANDSLIDE POTENTIAL INFORMATION BASED ON REMOTE SENSING SATELLITE IMAGERY USING OPEN-SOURCE SOFTWARE TECHNOLOGY Ahmad Sutanto Anwar Annas Mohammad Ardha Taufik Hidayat Muhammad Rokhis Khomarudin This automation system automatically generated landslide potential information based on daily precipitation data. This system is essential to replace the previous manual processing system with an automated and integrated system. The results of the developed system are the distribution of areas with landslide potential based on daily precipitation data. The system was built using geographic information systems and web service techniques. This allows the automation process to be performed quickly and accurately. The landslide susceptibility map used is from the National Disaster Management Agency, so the information is more reliable. Himawari-8 is used to determine the potential for extreme precipitation in 10 minutes because this satellite has a very high temporal resolution. The system is already in use and has proven to replace manual processing and is faster. Further development will be more challenging if the system can be connected to the sensors installed on site so that the sensors on site can issue a landslide warning in case of extreme precipitation so that the surrounding communities can respond immediately. Opportunities for future development of the system may also be incorporated into landslide potential prediction based on the precipitation forecast model BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13705 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 37-44 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13705/10661 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13706 2025-11-25T04:22:55Z ijreses:ART

SPATIO-TEMPORAL ANALYSIS OF CHANGES IN CORAL REEF AREA USING LANDSAT 8 SATELLITE IMAGERY ON PARI ISLAND, KEPULAUAN SERIBU, DKI JAKARTA Faisal Akmal Bambang Semedi Azura Ulfa Area Change Coral Reef Landsat 8 Pari Island Coral reefs are ecosystems that are sensitive to change. High pressure can cause damage to coral reefs. Monitoring the condition of coral reefs needs to be done to know the current condition. One way that can be used to monitor coral reefs is by utilizing remote sensing. The research was conducted to know the changes in the coral reef area and the factors that influence the changes in the coral reef area in Pari Island, Kepulauan Seribu, DKI Jakarta in the period 2013 to 2022. The research was conducted using Landsat 8 image data from 2013 to 2022. Image data processing was done with an object-based classification method. Coral cover measurements were conducted using the Line Intercept Transect (LIT) method. The results showed a change in coral reef area of 7.02 ha with the condition of live coral cover ranging from 27-43% which is included in the fair category. The results of field measurements show that the condition of water parameters falls into the unsuitable category. The increase in area that occurred was thought to be due to management activities carried out by the Pari Island community and activities carried out by LIPI in 2016, namely conducting coral reef restoration. The decrease in area is partly due to coastal reclamation activities, destructive tourist activities, and parameter conditions. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13706 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 83-95 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13706/10660 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13708 2025-11-25T04:22:55Z ijreses:ART

ASSESSMENT OF FLASH FLOOD HAZARD POTENTIAL IN A SMALL MOUNTAINOUS CIKUNDUL WATERSHED IN CIANJUR, WEST JAVA, INDONESIA Eko Kusratmoko Armila Rista Septina Muhammad Attorik Falensky Cikundul Watershed flash flood flash flood potential index Flash flood is a geomorphic hazard that can cause huge losses in a short period of time. Cianjur regency, especially Cikundul Watershed is a flash flood frequent area. Therefore, flash flood potential mapping is needed to reduce the threat that can be caused by flash flood. In the flash flood potential mapping, Flash Flood Potential Index (FFPI) method is still rarely applied in Indonesia. This study aims to see the comparison of flash flood potential areas based on models developed in the FFPI method which is Smith, Brewster, Krudzlo, and Ceru models. The four models used slope, land use, soil texture, and vegetation cover as variables. Spatial analysis and statistical test was implemented to validate the flash flood potential areas with flash flood affected locations. The result reveals that Cikundul Watershed was dominated by moderate potential areas based on Brewster, Krudzlo, and Ceru model but low by Smith model. The result also reveals that 65% of 68 Sub-Sub Watershed have different potential and 35% have same potential. High potential areas in all four models was distributed in the Upper Cikundul Watershed. The Crosstab Fit Test result shows that Smith model is the closest model to the actual event. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13708 International Journal of Remote Sensing and Earth Sciences; Vol. 21 No. 1 (2024); 96-105 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13708/10662 Copyright (c) 2024 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13712 2025-11-25T04:35:05Z ijreses:ART

DIFFERENCES OF COASTALLINE CHANGES IN THE AREA AFFECTED BY LAND COVER CHANGES AND COASTAL GEOMORPHOLOGICAL SOUTH BALI 1995 - 2021 Muhammad Dimyati Muhamad Rafli Astrid Damayanti The South Bali coast is prone to abrasion due to its geographical position facing the Indian Ocean. High sea waves and currents in the south of Bali will erode beaches whose lithology and morphology are prone to abrasion. Land cover conditions that do not support coastal protection will also affect the high abrasion of the southern coast of Bali. This study aims to analyze the shoreline changes in South Bali from 1995-2021. The analytical method used is the Digital shoreline analysis system (DSAS), with data from Landsat 5 TM, Landsat 7 ETM+, Landsat 8 OLI/TIRS, and Sentinel 2A. The analysis results show that the area directly facing the waves is relatively high, with volcanic rock formations, and there is no mangrove as coastal protection. The lack of good coastal management shows the area with the highest abrasion. It was found in the western part of Tabanan Regency, eastern Gianyar, and southern Badung. Meanwhile, the average coastal accretion was relatively high in the neck of South Bali, in areas where the land cover was mangrove and adjacent to river mouths, which experienced much sedimentation. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13712 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 167-176 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13712/10663 Copyright (c) 2022 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13713 2025-11-25T04:35:05Z ijreses:ART

TEA PLANT HEALTH RESEARCH USING SPECTROMETER Dwi Hastuti Masita Dwi Mandini Manessa Mangapul Parlindungan Tea leaves are the most important part for consumption. Leaves that are healthy have a distinct color, while leaves that are not healthy have a color that is very different from the original. Chlorophyll in leaves effects the reflection of infrared light, allowing healthy plants to reflect more infrared light than unhealthy plants. Leaf color and chlorophyll have an important role in showing the growth and health of tea plants. Remote sensing consists of collecting information about objects and features without contacting the equipment. The Normalized Difference Vegetation Index (NDVI), one of the first remote sensing analysis products used to simplify the complexity of multispectral imaging, is now the most commonly used index for botanical assessment. inconsistencies in NDVI depending on sensor-specific spatial and spectral resolutions. Different parts of the leaf have discolored spots due to health conditions or nutritional stress, so there are different spectral values on different parts of the leaf. Unhealthy tea leaves have low NIR values due to disease, insects, and sunburn, which damage the chloroplast structure of the leaves, weaken the absorption of the appropriate band, and increase reflectance. There is a difference between the measurement results of the NDVI spectrometer and the sentinel image. This is due to the fact that the Sentinel-2 image can only retrieve image pixels with a resolution and not diseased leaf parts, as with the use of a spectrometer, which directly extracts the value of the infected area from the normal part of the plant BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13713 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 177-184 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13713/10664 Copyright (c) 2022 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13714 2025-11-25T04:35:05Z ijreses:ART

TSUNAMI HAZARD MODELING IN THE COASTAL AREA OF KULON PROGO REGENCY Dwiana Putri Setyaningsih Hubertus Ery Cantas Pratama Sutiono Amelia Rizki Gita Paramanandi Ernani Uswatun Khasanah Tri Wahyuni Bernadeta Aurora Edwina Kumala Jati Muhammad Falakh Al Akbar Wirastuti Widyatmanti Totok Wahyu Wibowo tsunami inundation hazard Kulon Progo GIS Kulon Progo Regency is located in the southern part of Java Island, one of Indonesia's areas that is prone to tsunami disasters. Kulon Progo Regency is prone to tsunamis because it faces a subduction zone in the Indian Ocean. Therefore, it is necessary to model tsunami inundation and map the tsunami hazard zone in the Kulon Progo coastal area. This study aims to model tsunami inundation and produce a tsunami hazard map with a tsunami height scenario of 5 meters and 10 meters. The method used in modeling tsunami inundation is using a mathematical calculation developed by Berryman-2006 using the parameters of the coefficient of surface roughness, slope, and the height of the tsunami at the coastline. The estimated tsunami inundation area is classified into a tsunami hazard index using the fuzzy logic method resulting in an index of 0 – 1, which is then divided into three hazard classes. The results of the tsunami hazard mapping with the 5 meters scenario are 15 villages in 4 sub-districts included in the hazard zone with a total area of 20672,34 Ha affected. The results of the tsunami hazard mapping with a 10 meters scenario are 26 villages in 4 sub-districts with a total area of 53042,66 Ha affected. The results of this research can be used as basic information for disaster mitigation. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13714 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 185-196 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13714/10665 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13715 2025-11-25T04:22:19Z ijreses:ART

TSUNAMI DISASTER MODELING FOR NON-MILITARY DEFENSE IN PANGANDARAN REGENCY USING GEOGRAPHIC INFORMATION SYSTEMS Mauliza Fatwa Yusdian Riyan Eko Prasetiyo Asep Adang Supriyadi Yosef Prihanto Tsunami Megathrust winITDB GIS The tsunami disaster is one of the non-military threats to the State of Indonesia. Pangandaran Regency has a coastline of 91 km which is directly opposite the Megathrust of West-Central Java. The coastal area of Pangandaran Regency is an important center of tourism and economic activity and a high risk area for tsunamis due to earthquakes. This study was conducted to model the tsunami and analyze the magnitude of the inundation generated in settlements and tourist attractions in Pangandaran Regency as a form of defensive effort in disaster mitigation. The method used is tsunami modeling based on earthquake parameters using winITDB software. After modeling, it will be continued with H-Loss calculations based on tsunami run-up height data parameters, Digital Elevation Model (DEM) data, land use or cover data, and shoreline data using Geographic Information Systems. The results of the tsunami modeling are that the estimation waves height and estimation time arrival from three tide gauges are 15,34 m and 31,13 minutes. The total inundation area is 31.081 ha. The area of inundation according to the classification of land use is the most crucial and includes life, namely settlements and places of activity covering an area of 2.339,2 ha. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13715 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 45-57 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13715/10666 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13716 2025-11-25T04:35:05Z ijreses:ART

COMPARISON OF MACHINE LEARNING ALGORITHMS FOR LAND USE AND LAND COVER ANALYSIS USING GOOGLE EARTH ENGINE (CASE STUDY: WANGGU WATERSHED) Septianto Aldiansyah Randi Adrian Saputra Google Earth Engine Land Use Land Cover Classification and Regression Tree Random Forest Support Vector Machine Human population growth and land use and land cover (LULC) change have always developed side by side. Considering selection of a good Machine Learning (ML) classifier algorithm is needed considering the high estimation of LULC maps based on remote sensing. This study aims to produce a LULC classification of Landsat-8 and Sentinel-2 images by comparing the accuracy performance of three ML algorithms, namely: Classification and Regression Tree (CART), Random Forest (RF), and Support Vector Machine (SVM). Dataset comparison ratios were also explored to find the LULC classification results with the best accuracy. Sentinel-2 is better than Landsat-8 regarding Overall Accuracy (OA) and Coefficient Kappa. The comparison ratio of the training and testing datasets with a good level of accuracy is 70:30 on both images with the average OA Landsat-8 and Sentinel-2 being 92.09% and 94.21%, respectively. The RF algorithm outperforms CART and SVM in both types of satellite imagery. The mean OA of the CART, RF, and SVM classifiers was 92.03%, 94.74%, 83.54% on Landsat-8, 93.14%, 96.15%, and 93.34% on Sentinel-2, respectively. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13716 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); 197-210 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13716/10667 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13719 2025-11-25T04:22:19Z ijreses:ART

EFFECT OF ATMOSPHERIC CORRECTION ALGORITHM ON LANDSAT-8 AND SENTINEL-2 CLASSIFICATION ACCURACY IN PADDY FIELD AREA Fadila Muchsin Kuncoro Adi Pradono Indah Prasasti Dianovita Kurnia Ulfa Kiki Winda Veronica Dandy Aditya Novresiandi Andi Ibrahim atmospheric correction Landsat-8 Sentinel-2 classification accuracy Landsat-8 and Sentinel-2 satellite imageries are widely used for various remote sensing applications because they are easy to access and free to download. A precise atmospheric correction is necessary to be applied to the optical satellite imageries so that the derived information becomes more accurate and reliable. In this study, the performance of atmospheric correction algorithms (i.e., 6S, FLAASH, DOS, LaSRC, and Sen2Cor) was evaluated by comparing the object's spectral response, vegetation index, and classification accuracy in the paddy field area before and after the implementation of atmospheric correction. Overall, the results show that each algorithm has varying accuracy. Nevertheless, all atmospheric correction algorithms can improve the classification accuracy, whereby those derived by the 6S and FLAASH yielded the highest accuracy. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13719 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 58-66 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13719/10669 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13720 2025-11-25T04:35:05Z ijreses:BP

Back Pages IJReSES Vol. 19, No. 2 (2022) Journal Manager Back Pages IJReSES Vol. 19, No. 1 (2022) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13720 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 2 (2022); I-IV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13720/10668 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13721 2025-11-25T04:22:19Z ijreses:ART

OBSTRUCTION ZONE MODELING AT HALIM PERDANAKUSUMA AIRPORT USING REMOTE SENSING DATA Asep Adang Supriyadi Sentinel 2A NDBI Obstruction Zone KKOP Halim Perdanakusuma Airport Flight safety plays a critical role in both the national economy and military defense. According to the National Transportation Safety Board (NTSB), the highest number of aircraft accidents between 2013 and 2018 occurred during takeoff (24%) and landing (40%). To model the obstruction zone based on building density and its impact on flight safety, this study utilizes remote sensing data from Sentinel 2A in 2022. The data is analyzed using the Normalized Difference Built-up Index (NDBI) algorithm, which serves as the basis for modeling potential aircraft accident zones. Specifically, the study focuses on the growth of buildings within a 15 km extended runway area during takeoff and landing.  The findings reveal that the aircraft takeoff approach area in the Flight Operation Safety Zone (KKOP) at Halim Perdanakusuma Airport exhibits the highest building density. This area demonstrates a moderate level of building density, with a prevailing growth pattern and density that extend predominantly eastward, toward Bekasi city. Furthermore, the study highlights that nearly the entire region falls under the classification of "built-up areas." Consequently, establishing urban planning policies for development around landing and takeoff corridors becomes imperative while considering aviation safety factors.  This research provides valuable insights to aviation authorities and decision-makers involved in infrastructure development and urban planning. By taking into account building density and the growth of surrounding areas along flight paths, appropriate measures can be implemented to ensure optimal flight safety and mitigate the risk of future aircraft accidents BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13721 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 66-76 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13721/10671 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13722 2025-11-25T06:21:20Z ijreses:FP

Front Pages IJReSES Vol. 18, No. 1 (2021) Journal Manager Front Pages IJReSES Vol. 18, No. 1 (2021) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13722 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); I-V 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13722/10670 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13723 2025-11-25T06:21:20Z ijreses:ART

OIL PALM PLANTATION DETECTION IN INDONESIA USING SENTINEL-2 AND LANDSAT-8 OPTICAL SATELLITE IMAGERY (CASE STUDY: ROKAN HULU REGENCY, RIAU PROVINCE) Yunita Nurmasari Arie Wahyu Wijayanto remote sensing oil palm detection Sentinel-2 Landsat-8 supervised machine learning The objective of this work is to assess the capability of multispectral optical Landsat and Sentinel images to detect oil palm plantations in Rokan Hulu, Riau, one of the largest palm oil producers in Indonesia, by combining multispectral bands and composite indices. In addition to comparing two different sets of satellite images, we also ascertain which gives the best performance among the supervised machine learning classifiers CART Decision Tree, Random Forest, Support Vector Machine, and Naive Bayes. With the use of multispectral bands and derived composite indices, the best classifier achieved an overall accuracy of up to 92%. The findings and contributions of the study include: (1) insight into a set of feature combinations that provides the highest model accuracy, and (2) an extensive evaluation of machine learning-based classifiers on two different optical satellite imageries. Our study could further be beneficial for the government in providing more scalable plantation statistics. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13723 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 1-18 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13723/10672 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13725 2025-11-25T06:21:20Z ijreses:ART

MACHINE LEARNING APPLIED TO SENTINEL-2 AND LANDSAT-8 MULTISPECTRAL AND MEDIUM-RESOLUTION SATELLITE IMAGERY FOR THE DETECTION OF RICE PRODUCTION AREAS IN NGANJUK, EAST JAVA, INDONESIA Terry Devara Tri Saadi Arie Wahyu Wijayanto multispectral remote sensing medium-resolution optic machine learning rice detection Statistics Indonesia (BPS) has been introducing the use of Area Sampling Frame (ASF) surveys from 2018 to estimate rice production areas, although the process continues to suffer from the high costs of human and other resources. To support this type of conventional field survey, a more scalable and inexpensive approach using publicly-available remote sensing data, for example from the Sentinel-2 and Landsat-8 satellites, has been explored. In this research, we compare the performance gain from Sentinel-2 and Landsat-8 images using a multiple composite-index enriched machine learning classifier to detect rice production areas located in Nganjuk, East Java, Indonesia as a case study area. We build a detection model from a set of machine learning classifiers, Decision Tree (CART), Support Vector Machine, Logistic Regression, Ensemble Bagging Methods (Random Forest and Extra Trees), and Ensemble Boosting Methods (AdaBoost and XGBoost). The composite indices consist of the NDVI and EVI for agricultural and forest areas, NDWI for water and cloud, and NDBI, NDTI, and BSI for built-up areas, fallows, and asphalt-based roads. Validated by k-fold cross-validation, Sentinel-2 and Landsat-8 achieved F1-scores of 0.930 and 0.919 respectively at the scale of 30 meters per pixel. Using a 10 meter resolution per pixel for the Sentinel-2 imagery showed an increased F1-score of up to 0.971. Our evaluation shows that the higher spatial resolution imagery of Sentinel-2 achieves a better prediction, not only performance-wise, but also as a better representation of actual conditions. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13725 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 19-32 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13725/10673 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13726 2025-11-25T06:21:19Z ijreses:ART

APPLICATION OF LAPAN A3 SATELLITE DATA FOR THE IDENTIFICATION OF PADDY FIELDS USING OBJECT BASED IMAGE ANALYSIS (OBIA) Mukhoriyah Dony Kushardono paddy field LAPAN A3 Landsat 8 object based image analysis (OBIA) supervised classification The role of agriculture is directly related to SDG No.2, which is running a programme until 2030 to reduce national poverty, eradicate hunger by increasing food security and improving nutrition and support sustainable agriculture. Problems faced include the reduction in agricultural land, which results in lower rice production, and the limited information on the monitoring of paddy fields using spatial data. The purpose of this study is to identify paddy fields using LAPAN A3 satellite imagery based on OBIA classification. The data used were from LAPAN A3 multispectral imagery dated 19 June 2017, Landsat 8 imagery dated 17 June 2017, DEM SRTM (BIG), and the Administrative Boundary Map (BIG). The analysis method was segmentation by grouping image pixels, and supervised classification by taking several sample areas based on Random Stratified Sampling. The results will be carried using a confusion matrix. The classification results produced four classes; watery paddy fields, vegetation paddy fields, fallow paddy fields, and non-paddy fields, using of the green, red, and NIR bands for the LAPAN A3 data. From the results of the segmentation process, there remain some oversegmented features in the appearance of the same object. Oversegmentation is due to an inaccurate value assignment to each algorithm parameter when the segmentation process is performed. For example, watery paddy fields appear almost the same as open land (fallow paddy fields), the water object is darker purple. The visual classification results (Landsat 8 data) are considered as the reference for the digital classification results (LAPAN A3). Forty-eight samples were taken and divided into four classes, with each class consisting of 12 samples. The results of the accuracy test show that the total accuracy of the object-based digital classification for visual classification is 62.5% with a Kappa accuracy value of 0.5. The conclusion is that LAPAN A3 data can be used to identify paddy fields based on spectral resolution and to complement Landsat 8 data. To improve the accuracy of the classification results, more samples and the correct RGB composition are needed. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13726 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 33-42 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13726/10674 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13727 2025-11-25T04:22:19Z ijreses:ART

VEGETATION INDICES FROM LANDSAT-8 DATA IN PALABUHANRATU Hermawan Setiawan Masita Dwi Mandini Manessa Hafid Setiadi land cover EVI SAVI Land cover will change due to population pressure, resource use, and human interest in space. Measuring the land area is important to determine how much-converted land is positive and negative. The vegetation on land was determined by how densely the plants were spread out. This study is conducted in Palabuhanratu, Sukabumi Regency. Aims to test and compare how accurate EVI and SAVI are at seeing vegetation density. The images used are from Landsat 8 in 2018 and 2022. Calibration is performed using high-resolution images, followed by field surveys with 98 points from polygon sampling. The average accuracy of the results from EVI is 49%, while the average accuracy of the results from SAVI is 45%. So, we can say that the EVI or SAVI based-input gives a similar result on observing the vegetation density in Palabuhanratu.   BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13727 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 26-36 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13727/10675 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13728 2025-11-25T06:21:19Z ijreses:ART

SPATIO-TEMPORAL ANOMALIES IN SURFACE BRIGHTNESS TEMPERATURE PRECEDING VOLCANO ERUPTIONS DETECTED BY THE LANDSAT-8 THERMAL INFRARED SENSOR (CASE STUDY: KARANGETANG VOLCANO) Suwarsono Djoko Triyono Muhammad Rokhis Khomarudin Rokhmatuloh Surface brightness temperature Karangetang Volcano magmatic eruption Landsat-8 TIRS Indonesia's geological as part of the “ring of fire†includes the consequence that community life could be affected by volcanic activity. The catastrophic incidence of volcanic eruptions in the last ten years has had a disastrous impact on human life. To overcome this problem, it is necessary to conduct research on the strengthening of the early warning system for volcanic eruptions utilising remote sensing technology.  This study analyses spatial and temporal anomalies of surface brightness temperature in the peak area of Karangetang volcano during the 2018-2019 eruption. Karangetang volcano is an active volcano located in North Sulawesi, with a magmatic eruption type that releases lava flow. We analyse the anomalies in the brightness temperature from channel-10 of the Landsat-8 TIRS (Thermal Infrared Scanner) time series during the period in question. The results of the research demonstrate that in the case of Karangetang Volcano the eruptions of 2018-2019 indicate increases in the surface brightness temperature of the crater region. As this volcano has many craters, the method is also very useful to establish in which crater the center of the eruption occurred. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13728 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 43-52 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13728/10676 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13729 2025-11-25T04:22:19Z ijreses:ART

FUTURE SUITABILITY OF TEA PLANTS -CLIMATE ANALYSIS USING REMOTE ANALYSIS IN JAVA, INDONESIA Pramudhian Firdaus Masita Dwi Mandini Manessa Mangapul P. Tambunan Rudy P. Tambunan Tea production is highly dependent on the geographical and climatic conditions of the environment where the plants are grown and on the crisis of climate change from time to time. Therefore, an analysis is needed to determine the impact of climatic conditions on the tea production industry, especially in Indonesia. Precipitation and temperature are the contributing factors to the productivity of tea. This phenomenon can be understood through analysis and projection of climate. This analysis can be utilized for mitigation and adaptation to applied climate in Indonesia's agriculture sector, especially in the industrial production of tea. By comparing the analysis of climate for tea in the past 1991 – 2020 period and the projection of future climate in the period 2051 – 2070, this study explains climate analysis to the production of tea, especially in Gunung Mas and Java Island, Indonesia. The result shows that climate analysis in the past in period 1991 – 2020, obtained existence influence and trend change to bulk available rain and temperature for the region Gunung Mas and its surroundings. Projection suitability land industry plant tea based on scenario future climate seen the impact with decrease suitable area as land growth plant tea. Climate scenarios RCP 4.5 and RCP 8.5 for 2070 show the influence of climate impact on the suitability of the tea plantation land industry. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13729 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); 77-88 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13729/10677 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13730 2025-11-25T04:22:19Z ijreses:BP

Backpages IJReSES Vol. 20, No. 1 (2023) Journal Manager Backpages IJReSES Vol. 20, No. 1 (2023) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13730 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 1 (2023); I-IV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13730/10678 Copyright (c) 2023 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13740 2025-11-25T06:16:15Z ijreses:FP

Front Page Chief Editor We sincerely thank you for reading the International Journal of Remote Sensing and Earth Sciences Vol. 18 No 2, December 2021. In general, this journal is expected to enrich the serial publications on earth sciences. In particular this journal is aimed to present improvement in remote sensing studies and its applications on earth sciences. This journal also serves as the enrichment on earth sciences publication, not only in Indonesia and Asia but also worldwide.This journal consists of papers discussing the particular interest in remote sensing field. Those papers are having remote sensing data for image processing, geosciences, oceanography, environment, disaster, mining activities, etc. A variety of topics are discussed in this seventeen edition. Briefly, the topics discussed in this edition are the studies of remote sensing data processing issues such as bathymetri, tsunami disaster risk, water resource, flood disaster areas, weathers, and peatland. There some new methods, new analysis, and new novelties on this edition.Finally, enjoy your reading of the IJRESES Vol. 18 No. 2 December 2021, and please refer this journal content for your next research and publication. For editorial team members and the journal secretariat, thank you very much for all big supports for this volume publication BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13740 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); I-XVI 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13740/10681 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13741 2025-11-25T06:21:19Z ijreses:ART

FISHING BOAT DISTRIBUTION ESTABLISHED BY COMPARING VMS AND VIIRS DATA AROUND THE ARU ISLANDS IN MALUKU INDONESIA Ruben van Beek Jonson L. Gaol Syamsul B. Agus Led Light Fisheries MPA Vessel Monitoring VIIRS VMS Marine protected areas (MPAs) and no take zones (NTZs) are essential for the preservation of marine ecosystems. However, these important areas can be severely harmed by illegal fishing. All vessels above 30 gross tons are required to use vessel monitoring systems (VMSs) that enable vessel tracking by sending geographic data to satellites in each specific time period. The Visible Infrared Radiometer Suite (VIIRS) is a sensor on the National Oceanic and Atmospheric Administration (NOAA)-20 satellite that can detect the light-emitting diode (LED) light used by fishing vessels from space during the night time. In this research, VMS and VIIRS fishery data were combined in order to identify fishing vessels that were detected by the VIIRS sensor of the NOAA-20 satellite. The research was focused on an area near the Aru Islands in the Arafura Sea in Indonesia. Data on LED light used by the fishing techniques of purse seine and bouke ami were obtained for the whole of 2018. The data were then processed using R software. An R package called LLFI (LED Light Fisheries Identifier) was created, containing several R-functions that calculate VMS vessel position during satellite overpass time and then combine the VMS and VIIRS data attributes, resulting in a dataset comprising vessels identified from the VIIRS dataset. Out of all the estimated VMS fishing vessel positions during the VIIRS satellite overpass, approximately 51% could be assigned to fishing vessels detected from the VIIRS dataset. For bouke ami, the identification rate was approximately 87%, while that for small purse seine was around 39%. Ultimately, the LLFI package created daily paths for each identified fishing vessel, displaying all its movements during the day of its’identification. These daily paths did not show any activity within MPA or NTZ. The LLFI package was successful in combining VMS and VIIRS data, estimating VMS vessel positions during the VIIRS satellite overpass, identifying a percentage of  the vessels, and creating a daily path for each identified vessel. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13741 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 53-62 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13741/10682 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13744 2025-11-25T06:21:19Z ijreses:ART

COASTLINE CHANGE ANALYSIS ON BALI ISLAND USING SENTINEL-1 SATELLITE IMAGERY Suhendra Christopher Ari Setiawan Teja Arief Wibawa Berta Berlian Borneo Bali coastline change Sentinel-1 abrasion accretion Bali is well-known as a popular tourism location for both local and foreign tourists. There are nine areas designated for tourism, eight of which are coastal. However, due to coastal erosion, the coastline of Bali is changing every year. The purpose of this study is to determine the changes that took place between 2015 and 2020 using Sentinel-1 satellite imagery. The study was conducted along the coastline of Bali Island at coordinates 08° 53' 35.5648" S, 114° 24' 41.8359" E and 08° 00' 46.7865" S, 115° 44' 17.5928" E. The coastlines were identified using the Otsu image thresholding method and linear tidal correction was performed. The coastline change analysis was made using the transect method. Ground truths were conducted in representative areas where major changes had occurred, either as a result of abrasion or accretion. According to the Sentinel-1 analysis, the coastline changes in Bali during the period 2015 – 2020 were mainly caused by abrasion, apart from at Buleleng, which were generally caused by accretion. Abrasion in Bali is dominantly affected by strong currents and high waves meanwhile accretion which having weak currents and low waves was more affected by human factor such as the construction in this study area. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13744 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 63-72 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13744/10686 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13745 2025-11-25T06:16:15Z ijreses:ART

A NEW INTERPRETATION OF THE EXISTENCE OF THE PANJANG REGIONAL FAULT BASED ON DEM AND FIELD OBSERVATIONS IN LAMPUNG, SUMATRA, INDONESIAD LAMPUNG, SUMATRA, INDONESIAOBSERVATION AT LAMPUNG, SUMATRA, INDONESIA Luhut Pardamean Siringoringo regional Lampung Panjang fault Sumatra geomorphology Referring to the regional geological map sheet of Tanjung Karang, the existence of the Panjang regional fault in the Sukarame area (the research area) is still debated. This can be seen from the dashed line on the map, which indicates that the existence of the fault is still unclear. The objective of this research is to ascertain the existence of the Panjang Fault, together with information on its type and direction. The method used was to integrate the tectonic geomorphological sections through Digital Elevation Model (DEM) interpretations and field observations result. Field observations were made to confirm the existence of these structures. We found that the Panjang regional fault in the research area does exist. From the south of research area, the fault apparently continues into the research area. It is a normal fault in a northwest-southeast direction. The existence of the fault is also supported by the discovery of water springs during the field observations. The fault has cut aquifers so that the groundwater appears on the surface as water springs. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13745 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 117-124 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13745/10684 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13746 2025-11-25T04:35:55Z ijreses:FP

Front Pages IJReSES Vol. 20, No. 2 (2023) Journal Manager Front Pages IJReSES Vol. 20, No. 2 (2023) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13746 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); I-VI 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13746/10683 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13747 2025-11-25T04:35:55Z ijreses:ART

UTILIZING REMOTE SENSING AND MACHINE LEARNING FOR ECOSYSTEM SERVICES MAPPING AT GUNUNG MAS TEA PLANTATION Annisa Fitria Masita Dwi Mandini Manessa Rudy Parluhutan Tambunan AHP Ecosystem Services Land Use and Land Cover Supervised classification Tea Land use and land cover changes are one of the main factors affecting ecosystems and the services they provide. Conversion from natural vegetation to agricultural and urban land can lead to the degradation of ecosystem services and loss of biodiversity. Puncak area, Bogor, which is a highland area, has become an area that is synonymous with tea plantations because it has an ecosystem that is suitable for being a tea plantation area. Gunung Mas tea plantation managed by PTPN VIII is one of the largest tea plantations and a contributor to foreign exchange in Indonesia. The tourism potential in the plantation and agricultural business sectors has a high selling value as a tourist object and attraction. The purpose of this study is to find out the distribution of ecosystem services for climate regulation, water flow and flood regulation, and ecotourism and cultural recreation services at Gunung Mas tea plantation which is displayed in the form of an Ecosystem Service Map. The land cover classification was extracted from the Sentinel 2A image, which was then scored based on expert judgment. The scoring results are then processed using the AHP Pairwise Comparison method. The results of the study show that the research area has very high climate regulation ecosystem services, very high water flow and flood regulation, and high cultural recreation and ecotourism ecosystem services.   BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13747 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 89-96 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13747/10685 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13749 2025-11-25T06:16:15Z ijreses:ART

ANALYSIS OF THE PENETRATION CAPABILITY OF VISIBLE SPECTRUM WITH AN ATTENUATION COEFFICIENT THROUGH THE APPARENT OPTICAL PROPERTIES APPROACH IN THE DETERMINATION OF A BATHYMETRY ANALYTICAL MODEL Kuncoro Teguh Setiawan Gathot Winarso Muhammad Ulin Nuha Maryani Hartuti Devica Natalia BR Ginting Emi Yati Kholifatul Aziz Fajar Bahari Kusuma Wikanti Asriningrum Analytical Method Benny and Dawson SPOT 6 Karimunjawa The attenuation coefficient (Kd) can be extracted by an apparent optical properties(AOP) approach to determine marine shallow-water habitat bathymetry based on an analytical method. Such a method was employed in the Red Sea by Benny and Dawson in 1983 using Landsat MSS imagery. Therefore, we applied the Benny and Dawson algorithm to extract bathymetry in shallow marine waters off Karimunjawa Island, Jepara, Central Java, Indonesia. We used the SPOT 6 satellite, which has four multispectral bands with a spatial resolution of 6 meters. The results show that three bands of SPOT 6 data (the blue, green, and red bands) can produce bathymetric information up to 30.29, 24.63 and 18.58 meters depth respectively. The determinations of the attenuation coefficients of the three bands are 0.08069, 0.09330, and 0.39641. The overall accuracy of absolute bathymetry of the blue, green, and red bands is 61.12%, 65.73%, and 26.25% respectively, and the kappa coefficients are 0.45, 0.52, and 0.13. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13749 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 125-138 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13749/10689 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13750 2025-11-25T04:35:55Z ijreses:ART

RESIDENTIAL CLASSIFICATION USING GEOBIA IN PART OF JAKARTA SUBURBAN AREA Akmal Hafiudzan Prima Widayani Nurwita Mustika Sari GEOBIA SVM eCognition Google Earth Engine WorldView-2 The increasing of urban population followed by socioeconomic problems leads to emerging various number of researchs in urban area, especially in Jakarta Metropolitan Area. One of them are escalated tension-conflict due to rise of newly Gated Communities residential that sprawl across local residents (Kampung Kota). There is urgency to map all 3 types of residential (Kampung Kota, Perumnas, Cluster) through satellite imagery on a wide-scale. This study uses WorldView-2 imagery data recorded for 2020. The method used is an object-based method, namely GEOBIA using the eCognition Developer 64 software. The GEOBIA process is carried out through three stages, firstly the segmentation to separate residential blocks from surrounding land cover objects (bodies of water, vegetation, open land, non-residential built-up land) as well as exploring the variable values of each object, then sample-based classification using the SVM algorithm on Google Earth Engine application, and accuracy test to evaluate semantic and geometric accuracy levels. The results of the mapping are 3 classes of residential types followed by 4 classes of land cover. The overall accuracy of the three types of residential is 80% which means that the GEOBIA approach is able to show good performance. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13750 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 97-105 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13750/10687 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13751 2025-11-25T06:21:19Z ijreses:ART

HYDRO-METEOROLOGICAL ASPECTS OF THE 2021 SOUTH KALIMANTAN FLOOD: TOPOGRAPHY, TIDES, AND PRECIPITATION Munawir Bintang Pratama Rafida M. Withono Ismail N. Azkiarizqi Natural Disaster Hydrological Hazard Meteorological Hazard Indonesia Extreme Events Precipitation Anomaly The 2021 South Kalimantan flood was recorded as the most serious ever to have taken place in the province. It occurred due to high-intensity rain during the period 10-19 January, accompanied by a spring tide. This study provides an overview of the disaster, with reference to the hydro-meteorological conditions (topography, tides, and precipitation). The method used was the analysis of the precipitation and its monthly rainfall pattern anomalies using remote sensing data. A Digital Elevation Model (DEM) was also analyzed to indicate the most noticeably flood-affected area. In certain areas, total precipitation during the ten days reached 672.8 mm, with daily precipitation peaking at 255 mm on January 14, greater than the 25-year return period value. The flood coincided with a spring tide, which peaked at 1.21 m on the evening of January 15. Using 20- year GPM data, it was found that ENSO and IOD coexisted with both the highest and lowest anomalies. With a La Niña event at the end of 2020,  a positive precipitation anomaly in 2021 was expected. The extreme precipitation is suspected to be the main driver of the  2021 South Kalimantan flood, whose impact was worsened by the spring tides. This  study conducts further research on the correlation between land-use change, rainfall, spring tide and flooding in South Kalimantan. In addition, it is recommended that the government plan flood risk  management by prioritizing areas based on vulnerability to climate hazards. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13751 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 73-90 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13751/10690 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13752 2025-11-25T04:35:54Z ijreses:ART

COMPARISON OF THE MANGROVE FOREST MAPPING ALGORITHMS IN KELABAT BAY USING RANDOM FOREST AND SUPPORT VECTOR MACHINES Rahmadi Raldi Hendrotoro Seputro Koestoer mangrove mapping remote sensing machine learning random forest support vector machine kelabat bay One of the tropical ecosystems is the mangrove forest, which thrives on protected coastlines such as bays, estuaries, lagoons, and rivers. These are usually found in the intertidal zone. Mangroves are a valuable natural resource because they stabilize coastlines, prevent erosion, retain sediment and nutrients, protect against storms, regulate floods and currents, sequester carbon, maintain water quality, serve as spawning grounds for fish and other marine life, and provide food For plankton. With over 59.8% of the total area of mangroves on the planet, Indonesia has some of the largest mangrove forests in the world. With the case study of Kelabat Bay in Bangka Regency and the Bangka Belitung Islands, this study compares the use of random forest (RF) techniques and support vector machines (SVM) for mapping mangrove forests. Landsat-9 imagery from 2022, taken via the Google Earth Engine (GEE), is the data source used in this study. This study utilizes computer programming and accuracy testing. As a result, RF detected mangrove forests covering an area of approximately 67 ha (OA: 0.932), while SVM detected mangrove forests covering an area of approximately 62 ha (OA: 0.912). BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13752 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 106-112 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13752/10688 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13753 2025-11-25T04:35:54Z ijreses:ART

SPATIAL ANALYSIS OF QUANTITATIVE PRECIPITATION FORECAST ACCURACY BASED ON STRUCTURE AMPLITUDE LOCATION (SAL) TECHNIQUE Abdullah Ali Achmad Rifani Supriatna Yunus Subagyo Swarinoto Umi Sa’adah weather radar QPF SAL STEPS Quantitative Precipitation Forecast (QPF) is the final product of a short-term forecasting algorithm (nowcasting) based on weather radar data which is widely used in hydrometeorological aspects. The calculation of the accuracy value using point data on a rainfall gauge often causes a double penalty problem because the QPF prediction results are in the form of spatial objects. This study aims to apply object-based spatial verification in analyzing the accuracy of QPF based on the Short Term Ensemble Prediction System (STEPS) algorithm using the SAL technique. The verification process is carried out by calculating the index value of the structure component (S), amplitude (A), and location (L) in the QPF prediction results based on the results of weather radar observations. The index values for components S and A have a range of -2 to 2, and 0 to 1 for component L with a perfect value of 0. The case study used is the occurrence of heavy rains that caused flooding in Bogor Regency in 2020. SAL verification results from 26 case studies used shows the average value of the components S, A, and L, respectively 0.51, 0.38, and 0.21. As many as 75% of all case studies have S and L component values less than 0.5 which indicate the structure and location of the QPF prediction object is close to the structure and location of the object of observation. A positive value in component A indicates that the QPF prediction results based on the STEPS algorithm tend to be overestimated but on a low scale, namely 0.38 out of 2. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13753 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 113-120 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13753/10691 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13754 2025-11-25T06:16:15Z ijreses:ART

SPATIAL ANALYSIS OF THE TSUNAMI RISK IN PALABUHANRATU SUB-DISTRICT, SUKABUMI REGENCY, INDONESIA BASED ON THE DISASTER CRUNCH MODELSPATIAL ANALYSIS OF THE TSUNAMI RISK IN PALABUHANRATU SUB-DISTRICT, SUKABUMI REGENCY, INDONESIA BASED ON THE DISASTER CRUNCH Inti Raidah Hidayat Sudaryanto tsunami risk level Disaster Crunch model COMCOT V.1.7. Palabuhanratu Sub-District is one of the southern coastal areas of Java that has the potential to be exposed to tsunamis, with an estimated run-up of between 12-20 meters. Accordingly, it is necessary to conduct tsunami disaster mitigation by analysing the level of tsunami risk in the district to reduce potential losses if a tsunami occurs. This study aims to map the level of tsunami risk in Palabuhanratu Sub-District based on the disaster crunch model, which is a risk model that integrates vulnerability and tsunami hazard factors. The tsunami vulnerability analysis uses a weighted overlay quantitive approach, while the tsunami hazard analysis employs simulation of tsunami propagation by COMCOT V.1.7; the tsunami inundation reduction model; cost distance analysis; and fuzzy membership analysis. The results of the tsunami risk analysis show that villages included in the high-, medium-, and low-risk categories are Citepus, Palabuhanratu, and Jayanti. The percentage of high-risk areas in the three villages are 10% (139 hectares), 20.3% (114 hectares), and 0.01% (0.13 hectares) respectively. The higher the risk of a tsunami in an area, the higher the losses that will be incurred by the local population.Palabuhanratu Sub-District is one of the southern coastal areas of Java that has the potential to be exposed to tsunamis, with an estimated run-up of between 12-20 meters. Accordingly, it is necessary to conduct tsunami disaster mitigation by analysing the level of tsunami risk in the district to reduce potential losses if a tsunami occurs. This study aims to map the level of tsunami risk in Palabuhanratu Sub-District based on the disaster crunch model, which is a risk model that integrates vulnerability and tsunami hazard factors. The tsunami vulnerability analysis uses a weighted overlay quantitive approach, while the tsunami hazard analysis employs simulation of tsunami propagation by COMCOT V.1.7; the tsunami inundation reduction model; cost distance analysis; and fuzzy membership analysis. The results of the tsunami risk analysis show that villages included in the high-, medium-, and low-risk categories are Citepus, Palabuhanratu, and Jayanti. The percentage of high-risk areas in the three villages are 10% (139 hectares), 20.3% (114 hectares), and 0.01% (0.13 hectares) respectively. The higher the risk of a tsunami in an area, the higher the losses that will be incurred by the local population. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13754 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 139-152 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13754/10692 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13755 2025-11-25T06:21:18Z ijreses:ART

RADAR-BASED STOCHASTIC PRECIPITATION NOWCASTING USING THE SHORT-TERM ENSEMBLE PREDICTION SYSTEM (STEPS) (CASE STUDY: PANGKALAN BUN WEATHER RADAR) Abdullah Ali Supriatna Umi Sa’adah weather radar nowcasting Short Term Ensemble Prediction Systems (STEPS) Nowcasting, or the short-term forecasting of precipitation, is urgently needed to support the mitigation circle in hydrometeorological disasters. Pangkalan Bun weather radar is single-polarization radar with a 200 km maximum range and which runs 10 elevation angles in 10 minutes with a 250 meters spatial resolution. There is no terrain blocking around the covered area. The Short-Term Ensemble Prediction System (STEPS) is one of many algorithms that is used to generate precipitation nowcasting, and is already in operational use. STEPS has the advantage of producing ensemble nowcasts, by which nowcast uncertainties can be statistically quantified. This research aims to apply STEPS to generate stochastic nowcasting in Pangkalan Bun weather radar and to analyze its advantages and weaknesses. Accuracy is measured by counting the possibility of detection and false alarms under the 5 dBZ threshold and plotting them in a relative operating characteristic (ROC) curve. The observed frequency and forecast probability is represented by a reliability diagram to evaluate nowcast reliability and sharpness. Qualitative analysis of the results showed that the STEPS ensemble produces smoothed reflectivity fields that cannot capture extreme values in an observed quasi-linear convective system (QLCS), but that the algorithm achieves good accuracy under the threshold used, up to 40 minutes lead time. The ROC shows a curved upper left-hand corner, and the reliability diagram is an almost perfect nowcast diagonal line. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13755 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 91-102 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13755/10694 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13757 2025-11-25T04:35:54Z ijreses:ART

EFFECT OF LOW PASS FILTER ON BATHYMETRIC DETECTION IN PULAU PUTRI SHALLOW SEA, KEPULAUAN SERIBU USING PLANETSCOPE SATELLITE IMAGERY Alberto Junior Hutagaol Kuncoro Teguh Setiawan Muhammad Sulaiman Nur Ubay Hastuadi Harsa bathymetry detection stumpf algorithm Putri Island PlanetScope Sea depth measurements are usually only carried out at locations that can be passed by ships, so measurements in shallow waters are often not possible. Along with the development of remote sensing technology, shallow water bathymetry mapping can now be done using satellite imagery. The Stumpf method is a ratio model that compares two bands in order to reduce the effect of water albedo. The purpose of this research is to study the processing of satellite imagery data for the detection of bathymetry in shallow sea waters, to determine the effect of the low pass filter, and to find out the methods for obtaining detection results with high accuracy. In this study, the primary data used was PlanetScope imagery from the NICFI program. Bathymetry detection of shallow marine waters was carried out around the waters of Putri Island, Seribu Islands Regency. The results of the accuracy test for the detection of shallow sea bathymetry without the application of a low pass filter using the confusion matrix method and the RMSE calculation have higher accuracy with an overall accuracy value of 94.17% and an RMSE value of 1.61 BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13757 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 121-130 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13757/10693 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13758 2025-11-25T06:16:15Z ijreses:ART

DETECTING SURFACE WATER AREAS AS ALTERNATIVE WATER RESOURCE LOCATIONS DURING THE DRY SEASON USING SENTINEL-2 IMAGERY (CASE STUDY: LOWLAND REGION OF BEKASI-KARAWANG, WEST JAVA PROVINCE) Jalu Tejo Nugroho Suwarsono Galdita Aruba Chulafak Atriyon Julzarika R Johannes Manalu Sri Harini Argo Suhadha Sayidah Sulma surface water area drought Bekasi-Karawang Sentinel-2 NDWI In Indonesia, drought is a type of disaster that often occurs, especially during the dry season. What is most needed at such times is the availability of sufficient water sources to meet shortages. Therefore, water source locations are vital during the dry season in order to meet needs. To meet this information need, remote sensing data offer a precise solution.  This research proposes a rapid method of detecting surface water areas based on remote sensing image data. It focuses on the use of remote sensing satellite imagery to detect objects and the location of surface water sources. The purpose of the study is to rapidly identify objects and locate surface water sources using Sentinel-2 MSI (MultiSpectral Instrument), one of the latest types of remote sensing satellite data. Several water index (WI) methods were applied before deciding which was most suitable for detecting surface water objects. The lowland region of Bekasi-Karawang, a drought prone area, was designated as the research location. The results of the research show that by using Sentinel-2 MSI imagery, MNDWI (Modified Normalized Water Index) is the appropriate parameter to detect surface water areas in the lowland region of Bekasi-Karawang, West Java Province, Indonesia, during times of drought. The method can be employed as an alternative approach based on remote sensing data for the rapid detection of surface water areas as alternative sources of water during the dry season. The existence of natural water sources (swamps, marshes, ponds) that remain during this time can be used as alternative water resources. Further research is still needed which focuses on different geographical conditions and other regions in Indonesia. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13758 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 153-162 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13758/10697 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13760 2025-11-25T04:35:54Z ijreses:ART

SPATIAL ANALYSIS OF LAND USE AND LAND COVER VARIATIONS AFFECTING TEA PRODUCTION IN GUNUNGMAS PLANTATION THROUGH REMOTE SENSING TECHNIQUES Elok Lestari Paramita Masita Dwi Mandini Manessa Mangapul Parlindungan Tambunan Spatial Analysis Land Use Land Cover (LULC) Change Tea Plantation Remote Sensing NDVI Tea is a manufactured beverage that is popular around the world. In value chain analysis to increase efficiency, remote sensing technology can be developed to monitor the phenomenon of land use land cover (LULC) change and vegetation health conditions. This study aims to identify LULC in tea plantations, identify the health condition of tea plantations, then analyze spatial trends of changes in tea productivity in Gunungmas Afdeling-1 due to changes in tea area or tea vegetation health condition. Identification of changes in LULC in tea plantations can be carried out using remote sensing technology and machine learning, in this study, Google Earth Engine (GEE) LULC identification was generated using a supervised classification with the random forest algorithm on the GEE. Tea productivity trends decreased from 2019 to 2020, but increased from 2020 to 2021. They show that the trend of changes in the area of tea plantation classification is decreasing. According to the NDVI result, most of the reduced area of tea plantations is in areas with healthy vegetation. The trends in tea productivity changes are not in line with changes in the LULC area of tea plantation classification class and tea vegetation health condition. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13760 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 131-140 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13760/10695 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13761 2025-11-25T06:21:18Z ijreses:ART

ESTIMATION OF ABOVEGROUND CARBON STOCK USING SAR SENTINEL-1 IMAGERY IN SAMARINDA CITY Bayu Elwanto Bagus Dewanto Retnadi Heru Jatmiko stands vegetation carbon stock estimation remote sensing Sentinel-1 imagery Samarinda City Estimation of aboveground carbon stock on stands vegetation, especially in green open space, has become an urgent issue in the effort to calculate, monitor, manage, and evaluate carbon stocks, especially in a massive urban area such as Samarinda City, Kalimantan Timur Province, Indonesia. The use of Sentinel-1 imagery was maximised to accommodate the weaknesses in its optical imagery, and combined with its ability to produce cloud-free imagery and minimal atmospheric influence. The study aims to test the accuracy of the estimated model of above-ground carbon stocks, to ascertain the total carbon stock, and to map the spatial distribution of carbon stocks on stands vegetation in Samarinda City. The methods used included empirical modelling of carbon stocks and statistical analysis comparing backscatter values and actual carbon stocks in the field using VV and VH polarisation. Model accuracy tests were performed using the standard error of estimate in independent accuracy test samples. The results show that Samarinda Utara subdistrict had the highest carbon stock of 3,765,255.9 tons in the VH exponential model. Total carbon stocks in the exponential VH models were 6,489,478.1 tons, with the highest maximum accuracy of 87.6 %, and an estimated error of 0.57 tons/pixel. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13761 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); 103-116 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13761/10698 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13762 2025-11-25T04:35:54Z ijreses:ART

ASSESSING THE POSSIBILITY OF LAND SUBSIDENCE DUE TO GEOTHERMAL PRODUCTION IN SARULLA GEOTHERMAL FIELD USING SENTINEL-1 Mochamad Iqbal Panggea Ghiyats Sabrian geothermal Sarulla subsidence PS-InSAR Sarulla geothermal field is one of the largest geothermal fields in the world which has a 330 MW installed capacity. The field consists of three areas, namely Namora Langit (NIL)-1, NIL-2, and Silangkitang (SIL) which operated from 2017 and 2018. It is situated precisely at the Sarulla graben which is an active tectonic area composed of Quaternary Toba tuff and intermediate lava and extrusive felsic pyroclastic Toru. This study aims to see whether land subsidence may emerge in the Sarulla geothermal field and its environs in addition to determining whether the geothermal activity or anthropogenic is responsible for the deformation. We used the persistent scatterer (PS) interferometry synthetic aperture radar (InSAR) method to calculate the rate of subsidence in the area. 30 ascending images from Sentinel-1 were gathered from 5 January to 18 December 2020 with a separation of 12 days to run the analysis. The results demonstrate that Sarulla is undergoing subsidence occurring at NIL and SIL with a velocity of 0 to -32.9 mm/year. Although negative deformation occurs in the geothermal area, there is no solid evidence indicating geothermal fluid extraction is the cause of subsidence. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13762 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 141-150 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13762/10696 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13763 2025-11-25T06:16:14Z ijreses:ART

SPECTRAL CHARACTERISTICS OF FLASH FLOOD AREAS FROM MEDIUM SPATIAL OPTICAL IMAGERY Muhammad Priyatna Muhammad Rokhis Khomarudin Galdita Aruba Chulafak Sastra Kusuma Wijaya Reflectance flash flood disaster bush settlement This study aims to investigate surface reflectance changes over flash flood areas in Nusa Tenggara Timur, Indonesia. Fifteen sample points from Sentinel-2 satellite imagery were used to analyse the differences in reflectance of areas before and after flash flood events. The method used involved analysis of the significant differences in the dreflectance values of each Sentinel-2 channel. The analysis results show that channels 6, 7, and 8A displayed significant differences compared to the others with regard to reflectance before and after flooding, for both settlements and shrubs. The results could be used for further research in building a reflectance index for the rapid detection of affected areas, with a focus on these channels. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13763 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 163-176 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13763/10699 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13764 2025-11-25T04:35:54Z ijreses:ART

THE RELATIONSHIP BETWEEN LAND USE AND LAND COVER TO RUN-OFF COEFFICIENT VALUE IN BRANTAS WATERSHED AREA, TULUNGAGUNG - EAST JAVA, INDONESIA Bowo Eko Cahyono Asih Sumarlin Nurul Priyantari Katsunoshin Nishi watershed land cover Brtantas’ rainfall runoff The Ngrowo-Ngasinan sub-watershed is a part of Brantas Watershed which has an important role for the aquatic ecosystems in the Brantas watershed. Land cover changes in this sub-watershed can be identified by utilizing remote sensing technology. The use of remote sensing technology by applying Landsat 8 image data can be done by classifying several classes of land cover in the study area. Land cover affected the flow rate of a watershed because of its association with several problems due to the conversion of land. Land cover which influences the watershed ecosystems is forest. In addition to land cover, regional rainfall also affects the flow rate (runoff) in the area BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13764 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 151-159 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13764/10700 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13766 2025-11-25T06:16:14Z ijreses:ART

COMPARISON OF THE RADIOMETRIC CORRECTION LANDSAT-8 IMAGE BASED ON OBJECT SPECTRAL RESPONSE AND VEGETATION INDEX Fadila Muchsin Supriatna Adhi Harmoko Indah Prasasti Mulia Inda Rahayu Liana Fibriawati Kuncoro Adi Pradhono Landsat-8 atmospheric correction, spectral response NDVI Landsat-8 standard level (level 1T) data received by users still in digital form can be used directly for land cover/land use mapping. These data have low radiometric accuracy when used to produce information such as vegetation indices, biomass, and land cover/land use classification. In this study, radiometric/atmospheric correction was conducted using FLAASH, 6S, DOS, TOA+BRDF and TOA method to eliminate atmospheric disturbances and compare the results with field measurements based on object spectral response and NDVI values. The results of the spectral measurements of objects in paddy fields at harvest time in the Cirebon Regency, West Java, Indonesia show that the FLAASH and 6S method have spectral responses that are close to those of objects in the field compared to the DOS, TOA and TOA+BRDF methods. For the NDVI value, the 6S method has the same tendency as the object's NDVI value in the field. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13766 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 177-188 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13766/10703 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13769 2025-11-25T04:35:53Z ijreses:ART

ENVIRONMENT QUALITY IDENTIFICATION USING LANDSAT-8 IN THE PERIOD OF COVID-19 LOCKDOWN IN JAKARTA Khalifah Insan Nur Rahmi Mangapul Parlindungan Tambunan Rudy P. Tambunan Landsat-8 environment quality index Covid-19 lockdown PM10 The quality of the urban environment during the Covid-19 lockdown became a concern because it was reported that it had improved but the spatial studies were still limited. Spatial information at regional scale can be extracted from Landsat-8 imagery. This study aims to spatially and temporally analyze environmental quality variables from Landsat-8 Imagery and compare environmental quality indices before, during and after the Covid-19 lockdown in Jakarta. Environmental quality variables extracted from Landsat-8 imagery are PM10, LST, NDVI, NDWI, NDMI. Radiometric correction and masking were applied to obtain Landsat-8 reflectance and radian values. PM10 concentrations were estimated using linear regression between station data and visible-near infrared (VNIR) reflectance band values. The variable land surface temperature (LST) is obtained from the brightness temperature band 10 extraction. NDVI, NDWI, and NDMI are extracted from the transformation of the reflectance band index. The environmental quality index is extracted from a weighted linear combination method where each variable has a weighted value of 50% PM10, 31% LST, 11% NDVI, 5% NDWI, and 3% NDMI. The results of the distribution of the environmental quality index before, during and after the Covid-19 lockdown show changes. Before the lockdown, some areas in Jakarta had a poor environmental quality index, while during the lockdown, only a few areas were still of poor quality, including the reclamation island and the Cilincing industrial area, North Jakarta. After the lockdown, the environmental quality index decreased again i.e. good, medium and bad categories but the distribution was not as wide as before the lockdown. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13769 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); 160-170 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13769/10701 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13770 2025-11-25T04:35:53Z ijreses:BP

Back Pages IJReSES Vol. 20, No. 2 (2023) Journal Manager Back Pages IJReSES Vol. 20, No. 2 (2023) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13770 International Journal of Remote Sensing and Earth Sciences; Vol. 20 No. 2 (2023); I-IV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13770/10702 Copyright (c) 2023 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13774 2025-11-25T06:21:18Z ijreses:BP

Backpages Vol.18 No.1 (2021) Journal Editor Backpages Vol.18 No.1 (2021) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13774 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 1 (2021); I-III 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13774/10704 Copyright (c) 2021 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13775 2025-11-25T07:04:52Z ijreses:FP

Front Pages IJReSES Vol. 19, No. 1 (2022) Journal Manager Front Pages IJReSES Vol. 19, No. 1 (2022) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13775 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); I-XI 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13775/10705 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13776 2025-11-25T06:16:14Z ijreses:ART

PRELIMINARY STUDY OF A RADIO FREQUENCY INTERFERENCE FILTER FOR NON-POLARIMETRIC C-BAND WEATHER RADAR IN INDONESIA (CASE STUDY: TANGERANG WEATHER RADAR) Abdullah Ali Iddam Hairuly Umam Hidde Leijnse Umi Sa’adah weather radar radio frequency interference filtering algorithm C-Band weather radar that operates at a frequency of 5 GHz is very vulnerable to radio frequency interference (RFI) because it is located on a free used frequency. RFI can cause image misinterpretation and precipitation echo distortion. The new allocation for free spectrum recommended by the World Radio Conference 2003 and weather radar frequency protection in Indonesia controlled by the Balai Monitoring Spektrum Frekuensi (BALMON) have not provided permanent protection against weather radar RFI. Several RFI filter methods have been developed for polarimetric radars, but there have been no studies related to RFI filters on non-polarimetric radars in Indonesia. This research aims to conduct an initial study of RFI filters on such radars. Four methods were applied in the initial study. The Himawari 8 cloud mask was used to eliminate interference echo based on VS, IR, and I2 channels, while the nature of false echo interference that does not have a radial velocity value was used as the basis for the application of the Doppler velocity filter. Another characteristic in the form of consistent echo interference up to the maximum range was used as the basis for applying a beam filling analysis filter with reflectivity thresholds of 5 dBZ and 10 dBZ, with beam filling of more than 75%. Finally, supervised learning Random Forest (RF) was also used to identify interference echo based on the characteristics of the sampling results on reflectivity, radial velocity, and spectral width data. The results show that the beam filling analysis method with a threshold of 5 dBZ provides the best RFI filter without eliminating echo precipitation. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13776 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 189-202 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13776/10707 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13777 2025-11-25T07:04:52Z ijreses:ART

LAND USE/COVER CHANGE ON POTENTIAL LOSS OF SUMATRAN TIGERS IN KERINCI SEBLAT NATIONAL PARK BASED ON REMOTE SENSING DATA Muhammad Ardha Muhammad Rokhis Khomarudin Gatot Nugroho Sumatran Tigers landuse/cover change habitat suitability level Kerinci Seblat National Park The Sumatran tiger is an animal whose life is threatened due to land use changes and human activities. This study described the correlations between land cover/use change and the potential loss of Sumatran tigers in Kerinci Seblat National Park (KSNP) based on remote sensing data. Remote sensing technology was used due to the good historical data, and it can be used for land cover change analysis. The results of the land change analysis can be used to the analysis of the changes in the suitability level of the Sumatran tiger habitat. The analysis of land change in 2000 and 2020 with the random forest classification method and changes in the level of suitability of the Sumatran Tiger habitat has been carried out. The results of the analysis of land cover/use changes showed a very significant reduction in the area of primary forest, namely 282.58 km2, while the increase in the area of plantations and secondary forests was 186.52 km2 and 101.68 km2. This change affects the suitability level of the Sumatran tiger habitat from a very suitable level decreased from 164.42 km2 to suitable and not suitable. The declining suitability level class indicated the potential loss of Sumatran tigers in the Kerinci Seblat National Park. The increasing of plantation and settlement areas will increase the activity of humans. The conflict of human activity with Sumatran tigers’ life will impact the loss of Sumatran Tigers in KSNP BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13777 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 1-10 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13777/10706 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13778 2025-11-25T06:54:34Z ijreses:ART

DETECTING THE SURFACE WATER AREA IN CIRATA DAM UPSTREAM CITARUM USING A WATER INDEX FROM SENTINEL-2 Suwarsono Fajar Yulianto Hana Listi Fitriana Udhi Catur Nugroho Kusumaning Ayu Dyah Sukowati Muhammad Rokhis Khomarudin Surface water area NDWI Sentinel-2 Cirata dam Upstream Citarum This paper describes the detection of the surface water area in Cirata dam,  upstream Citarum, using a water index derived from Sentinel-2. MSI Level 1C (MSIL1C) data from 16 November 2018 were extracted into a water index such as the NDWI (Normalized Difference Water Index) model of Gao (1996), McFeeters (1996), Roger and Kearney (2004), and Xu (2006). Water index were analyzed based on the presence of several objects (water, vegetation, soil, and built-up). The research resulted in the ability of each water index to separate water and non-water objects. The results conclude that the NDWI of McFeeters (1996) derived from Sentinel-2 MSI showed the best results in detecting the surface water area of the reservoir. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13778 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 1-8 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13778/10710 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13779 2025-11-25T07:04:51Z ijreses:ART

ANALYSIS OF CLASSIFICATION METHODS FOR MAPPING SHALLOW WATER HABITATS USING SPOT-7 SATELLITE IMAGERY IN NUSA LEMBONGAN ISLAND, BALI Kuncoro Teguh Setiawan Gathot Winarso Andi Ibrahim Anang Dwi Purwanto I Made Parsa object-based pixel-based coral seagrass macroalgae Lyzenga 2006 Shallow water habitat maps are crucial for the sustainable management purposes of marine resources. The use of a better digital classification method can provide shallow water habitat maps with the best accuracy rate that is able to indicate actual conditions. Experts use the object-based classification method as an alternative to the pixel-based method. However, the pixel-based classification method continues to be relied upon by experts in obtaining benthic habitat conditions in shallow water. This study aims to analyze the classification results and examine the accuracy rate of shallow-water habitats distribution using SPOT-7 satellite imagery in Nusa Lembongan Island, Bali. Water column correction by Lyzenga 2006 was opted, while object-based and pixel-based classification was used in this study. The benthic habitat classification scheme uses four classes: substrate, seagrass, macroalgae, and coral. The results show different accuracy is obtained between pixel-based classification with maximum likelihood models and object-based classification with decision tree models. Mapping benthic habitats in Nusa Lembongan, Bali, with object-based classification and decision tree models, has higher accuracy than the other with 68%. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13779 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 10-20 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13779/10708 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13780 2025-11-25T06:16:14Z ijreses:ART

GROUNDWATER LEVEL ESTIMATION MODEL ON PEATLANDS USING SAR SENTINEL-1 DATA IN PART OF RIAU, INDONESIA Ardila Yananto Junun Sartohadi Hero Marhaento Awaluddin Forest and Land Fires Peatlands Ground Water Level Sentinel-1 The character of peatlands has the ability to store large amounts of water, but the surface of the peatlands dries quickly and easy to burn during the dry season. Research aims to build a model to estimate groundwater level of peatland. Statistical analysis of Karl Pearson Product Moment correlation test was used to determine the relationship between the back scatter values and the Surface Soil Moisture (SSM) values from the Sentinel-1 SAR data processing with the groundwater level values measured using the Sipalaga instrument. Regression analysis was used to determine the model that could be used to estimate the groundwater level of peatlands in the study area based on the results of Sentinel-1 SAR data processing. The results showed that the Sentinel-1 SAR data with the Sigma_0 format in decibel (db) units with VV polarization had the highest correlation value with the groundwater level data of peatlands measured using the Sipalaga instrument, with a value of r -0.648 (moderate correlation). Model to estimate water level of peatlands was Y = -101.629 + (-7.414 x), where 'Y' was the groundwater level of peatlands in the study area and 'x' was the Sentinel-1 SAR data with Sigma_0 format in decibel (db) units with VV polarization. The spatial and temporal patterns of peatlands groundwater level in the study area from Sentinel-1 SAR data showed peatlands that to survive at a water level <40 cm was in the area around of the Rokan River and also in plantation areas, especially Acacia plantations, where canals were made to irrigate and land management. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13780 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 203-216 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13780/10712 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13781 2025-11-25T07:04:51Z ijreses:ART

COMPARISON OF MACHINE LEARNING MODELS FOR LAND COVER CLASSIFICATION Bambang H. Trisasongko Dyah R. Panuju Nur Etika Karyati Rizqi I’anatus Sholihah artificial neural networks classification and regression trees extreme gradient boosting random forests Sentinel-2 support vector machines Land cover data remain one of crucial information for public use.  With rapid human-associated land alteration, this information needs to be frequently updated. Remotely-sensed data provide the best option to construct land cover maps with numerous methods available in the literature. While disagreement exists to select the robust one, further exploration should be made to extend the understanding on the behavior of machine learners, in particular, for classification problems. This article discusses performance of pixel-based machine learning algorithms, frequently used in research or implementation. Five popular algorithms were evaluated to distinguish five rural land cover classes, i.e. built-ups, crops, mixed garden, oil palm plantations and rubber estates, from Sentinel-2 data. This research found that the benchmark, classification and regression tree, was unable to differentiate woody vegetation, although the overall accuracy was sufficiently moderate. This suggested that overall accuracy cannot be seen as the only measure for assessing the quality of the thematic output. Meanwhile, support vector machines and random forest competed to yield the highest accuracy and class detection capability, although the latter was in favor with 98% accuracy level. A newly developed model, like extreme gradient boosting, achieved a similar level of accuracy. This research implies that modern machine learning approaches would be invaluable for land cover classification; hence, access to these modeling toolkits is substantial. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13781 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 21-29 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13781/10709 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13782 2025-11-25T07:04:51Z ijreses:ART

ESTIMATION OF OIL PALM PLANT PRODUCTIVITY USING SENTINEL-2A IMAGERY AT CIKASUNGKA PLANATION PTPN VIII, BOGOR, WEST JAVA Afifah Nur Rahmasari Supriatna Andry Rustanto estimated productivity oil palm plants vegetation index algorithm sentinel-2A imagery Palm oil is one of the commodities that is growing well in Indonesia with a high commercial value which makes the demand for processed palm oil products increase, it is necessary to have data and technology to estimate the productivity of oil palm plantations more efficiently. Remote sensing technology is one of the technologies that can be used to decision problems spatially and accurately, efficiently, and dynamically. One of them is remote sensing using Sentinel-2A imagery. This study aims to analyze the distribution and the accuracy of the NDVI and ARVI algorithms for the estimation of oil palm productivity at the Cikasungka Plantation PTPN VIII. The estimated productivity of oil palm plantations at Cikasungka Plantation varies in each block with an estimated productivity of oil palm plantations of 35,061 Kg/Ha/Month using the algorithm NDVI and ARVI algorithm is 35,431 Kg/Ha/Month. Oil palm productivity was regressed by vegetation index and plant age to generate a model. Based on modeling with these two algorithms, the accuracy of the ARVI algorithm model has a lower RMSE value than NDVI, so it can be said that it is better in estimation of oil palm plant productivity  at the Cikasungka Plantation. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13782 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 31-38 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13782/10711 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13783 2025-11-25T06:54:34Z ijreses:ART

ANALYSIS OF POTENTIAL FISHING ZONES IN COASTAL WATERS: A CASE STUDY OF NIAS ISLAND WATERS Anang Dwi Purwanto Teguh Prayogo Sartono Marpaung Argo Galih Suhada Potential Fishing Zones Coastal ZPPI GHRSST Single Image Edge Detection (SIED) Nias Island The need for information on potential fishing zones based on remote sensing satellite data (ZPPI) in coastal waters is increasing. This study aims to create an information model of such zones in coastal waters (coastal ZPPI). The image data used include GHRSST, SNPP-VIIRS and MODIS-Aqua images acquired from September 1st-30th, 2018 and September 1st-30th, 2019, together with other supporting data. The coastal ZPPI information is based on the results of thermal front SST detection and overlaying this with chlorophyll-a. The method of determining the thermal front sea surface temperature (SST) used Single Image Edge Detection (SIED). The chlorophyll-a range used was in the mesotropic area (0.2-0.5 mg/m3). Coastal ZPPI coordinates were determined using the polygon centre of mass, while the coastal ZPPI information generated was only for coastal areas with a radius of between 4-12 nautical miles and was divided into two criteria, namely High Potential (HP) and Low Potential (LP). The results show that the coastal ZPPI models were suitable to determine fishing locations around Nias Island. The percentage of coastal ZPPI information generated was around 90% information monthly. In September 2018, 27 days of information were produced, consisting of 11 HP sets of coastal ZPPI information and 16 sets of LP information, while in September 2019 it was possible to produce 29 days of such information, comprising 11 sets of HP coastal ZPPI information and 18 LP sets. The use of SST parameters of GHRSST images and the addition of chlorophyll-a parameters to MODIS-Aqua images are very effective and efficient ways of supporting the provision of coastal ZPPI information in the waters of Nias Island and its surroundings. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13783 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 9-24 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13783/10714 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13785 2025-11-25T07:04:51Z ijreses:ART

COMPARISON OF DATA ASSIMILATION USING SURFACE OBSERVATION, UPPER AIR, AND SATELLITE RADIATION DATA ON RAINFALL PREDICTION IN THE JAMBI REGION (CASE STUDY OF HEAVY RAIN OCTOBER 20TH, 2020) Saveira Fairuz I. Nindya Pradita Danurahni Aryashta Gandhi Mahendra heavy rain parameterization data assimilation WRF Weather Research and Forecasting (WRF) is a mesoscale numerical weather prediction model that can provide good rainfall prediction information. The accuracy of the initial conditions and the accuracy of the parameterization scheme used in the WRF model affect the quality of the resulting rainfall prediction. Therefore it is necessary to assimilate to optimize the accuracy of the initial conditions in the model using the Three Dimensional Variational (3DVAR) assimilation technique. The purpose of this study was to determine the effect of applying the 3DVAR assimilation technique with the surface, upper air, and satellite radiation observations in predicting the occurrence of heavy rain on October 20th, 2020, in the Jambi region by first conducting a parameterization test of the cumulus and microphysical schemes. In this study, four experimental schemes were used, namely no assimilation (NON), observation data assimilation (OBS), satellite radiation data assimilation (SAT), and satellite radiation and observation data assimilation (BOTH). Each experimental model result was then verified statistically and spatially to determine the effect of the applied data assimilation. The results of this study indicate that the combination of Grell-3D and Thompson scheme shows the best performance in predicting rainfall. Then based on the spatial analysis of the SAT experiment, it is known that it can improve the model's initial conditions on the temperature and pressure parameters. Meanwhile, based on statistical verification, the SAT experiment improved the accuracy of rainfall predictions with a better forecast skill score than other experiments tested. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13785 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 39-52 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13785/10713 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13786 2025-11-25T06:16:14Z ijreses:ART

HAIL IDENTIFICATION BASED ON WEATHER FACTOR ANALYSIS AND HIMAWARI 8 SATELLITE IMAGERY (CASE STUDY OF HAIL ON 2ND MARCH 2021 IN MALANG INDONESIA) Marinda Nur Auliya Aditya Mulya hail cumulonimbus Himawari-8 A hail phenomenon occurred in Malang, Sumbermanjing Wetan District (8°6’S and 112°24’E) on March 2, 2021. According to the Regional National Disaster Management Agency, it was accompanied by heavy rain and strong winds, which caused several trees to fall, resulting in damage to people's houses (BNPBD, 2021). Hail is precipitation in the form of ice, usually an irregular round shape produced by cumulonimbus convective clouds (AMS, 2019). The research was conducted by examining global, regional, and local weather factors and analysing the cloud characteristics from satellite image data during hail events. Based on the analysis, it was found that ENSO, sea surface temperature anomalies, and MJO had no effect on the incidence of the hail. The streamline map showed the presence of shearlines and tropical cyclones around the Malang area, and the temperature significantly decrease from 07.00 UTC to 08.00 UTC of 4.4°C and from 08.00 UTC to 09.00 UTC of 3.6°C with significant increase in humidity from 07.00 UTC to 08.00 UTC of 10%. The cloud top temperature was analysed to be at the ripe stage at 07.40 UTC and 8.40 UTC, at -68.2°C. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13786 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); 217-228 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13786/10715 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13787 2025-11-25T07:04:51Z ijreses:ART

CARBON MONOXIDE SPATIAL PATTERN BASED ON VEHICLE VOLUME DISTRIBUTION IN TANGERANG CITY Arfani Priyambodo Adi Wibowo M. Dadang Basuki Vehicle Volume Air Pollution Carbon Monoxide Spatial Pattern Air pollution conditions in urban areas continue to increase due to the volume of vehicles every year. This volume increases sources of pollution such as motor vehicles which account for 60-70% of pollution. This study aims to analyze the distribution of vehicle volume and spatial pattern of CO in Tangerang City and see the relationship. The analysis used is descriptive and statistical spatial analysis. The results showed the distribution of vehicle volume in the morning ranged from <800-1600 vehicles on primary collector roads, while in the afternoon, there were 800 to >2000 vehicles on primary arterial roads. The spatial pattern of CO that formed on primary and collector arterial roads with residential land uses, industrial areas, and warehouses, then the CO concentration tends to be high. Meanwhile, other primary collector roads have low to moderate CO concentrations. The Spearman test and linear regression results showed a significant effect between vehicle volume on the Tangerang City CO pattern, with a strength value of 0.689 and an R Square of 0.476. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13787 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 53-68 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13787/10717 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13788 2025-11-25T06:54:33Z ijreses:ART

ANALYSIS OF WATER PRODUCTIVITY IN THE BANDA SEA BASED ON REMOTE SENSING SATELLITE DATA Sartono Marpaung Rizky Faristyawan Anang Dwi Purwanto Wikanti Asriningrum Argo Galih Suhadha Teguh Prayogo Jansen Sitorus PFZ point density chlorophyll-a water fertility Hovmoller Banda Sea This study examines the density of potential fishing zone (PFZ) points and chlorophyll-a concentration in the Banda Sea. The data used are those on chlorophyll-a from the Aqua MODIS satellite, PFZ points from ZAP and the monthly southern oscillation index. The methods used are single image edge detection, polygon center of mass, density function and a Hovmoller diagram. The result of the analysis show that productivity of chlorophyll-a in the Banda Sea is influenced by seasonal factors (dry season and wet season) and ENSO phenomena (El Niño and La Niña). High productivity of chlorophyll-a  occurs during in the dry season with the peak in August, while low productivity occurs in the wet season and the transition period, with the lowest levels in April and December. The variability in chlorophyll-a production is influenced by the global El Niño and La Niña phenomena; production increases during El Niño and decreases during La Niña. Tuna conservation areas have as lower productivity of chlorophyll-a and PFZ point density compared to the northern and southern parts of the Banda Sea. High density PFZ point regions are associated with regions that have higher productivity of chlorophyll-a, namely the southern part of the Banda Sea, while low density PFZ point areas  are associated with regions that have a low productivity of chlorophyll-a, namely tuna conservation areas. The effect of the El Niño phenomenon in increasing chlorophyll-a concentration is stronger in the southern part of study area than in the tuna conservation area. On the other hand, the effect of La Niña phenomenon in decreasing chlorophyll-a concentration is stronger in the tuna conservation area than in the southern and northern parts of the study area. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13788 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 25-34 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13788/10718 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13789 2025-11-25T06:16:14Z ijreses:BP

back page Chief Editor back page BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13789 International Journal of Remote Sensing and Earth Sciences; Vol. 18 No. 2 (2021); I-IX 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13789/10716 Copyright (c) 2021 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13790 2025-11-25T06:32:53Z ijreses:ART

VARIABILITY OF SEA SURFACE TEMPERATURE AT FISHERIES MANAGEMENT AREA 715 IN INDONESIA AND ITS RELATION TO THE MONSOON, ENSO AND FISHERY PRODUCTION Komang Iwan Suniada SST FMA 715 ENSO monsoon Tomini Bay Sea surface temperature (SST) is one of the important oceanographic and climateparameters. Its variability and anomalies often influence the environment and organisms, both in theoceans and on land. This study aims to identify the variability of SST and help the fisheriescommunity to understand how climate phenomena such as ENSO and monsoonal phases (representedby wind speed) are related to SST and fishery production in Fisheries Management Area (FMA) 715.SST was measured at Parimo, which represents conditions in the western part of the area insideTomini Bay, and at Bitung, which represents SST in the open ocean, with a more exposuredgeographical position. SST was derived from MODIS satellite imagery, downloaded from the oceancolordatabase (https://oceancolor.gsfc.nasa.gov/) with a 4 km spatial resolution, from January 2009 toDecember 2018. Wind speed data, historical El Niño or La Niña events, and fish production data werealso used in the study. Pearson’s correlation (Walpole, 1993) was used to test the relationshipbetween SST variability or anomaly and ENSO and monsoons. The results show that the SSTcharacteristics and variability of the Parimo and Bitung waters are very different, although they bothlie in the same FMA 715. SST in Parimo waters is warmer, but with lower variability than in Bitungwaters. SST in Parimo has a low correlation with ENSO (r=0.06, n=66), low correlation with windspeed (r=-0.29, n=120), with also a low correlation between SST anomaly and ENSO (r=0.05, n=66).SST in Bitung has a higher, but inverse, correlation with ENSO (r=-0.53, n=66), high correlation withwind speed (r=-0.60, n=119), with also a high correlation between SST anomaly and ENSO (r=-0.74,n=66). Unlike in other parts of Indonesia, fishery production in Parimo, or the western part insideTomini Bay, is not affected by ENSO events. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13790 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 99-114 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13790/10720 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13791 2025-11-25T07:04:51Z ijreses:ART

LOCAL CLIMATE ZONE (LCZ) IN BANDAR LAMPUNG CITY Farhan Anfasa Putra Adi Wibowo Iqbal Putut Ash Sidiq Bandar Lampung Building Density Vegetation Density Local Climate Zone Land Surface Temperature The rapid growth of the population in Bandar Lampung has led to a change in the land's usage from vegetation to built-up land. In the end, less vegetation will be present, which also results in higher temperatures in urban. This study intends to identify the state of the city's building density, vegetation density, land surface temperature, and Local Climate Zone (LCZ) in Bandar Lampung. Local Climate Zone (LCZ) maps can provide information on the physical structure of urban planning based on building density, and vegetation density, and are useful in the mitigation and public monitoring of increasing urban temperatures. The data was collected using images from Landsat 8 OLI/TIRS and high-resolution satellite imagery from Maxar Technologies downloaded using Google Earth Pro. Additionally, a field survey was used to measure the air temperature. The LCZ Generator WUDAPT is used to process LCZ data. The findings revealed that Bandar Lampung was dominated by medium-density buildings in the city's canter and medium-density vegetation in its western. The highest LST in residential areas is 35°C, while forest areas have the lowest LST at 15,68°C. There are 14 LCZ classifications, covering seven building types and seven land cover types. The dense tree zone has the highest vegetation density, the open low-rise zone has the highest land surface temperature, and the compact low-rise zone has the highest building density.   BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13791 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 69-78 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13791/10719 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13792 2025-11-25T06:54:33Z ijreses:ART

ASSESSMENT OF THE ACCURACY OF DEM FROM PANCHROMATIC PLEIADES IMAGERY (CASE STUDY: BANDUNG CITY. WEST JAVA) Rian Nurtyawan Nadia Fiscarina Pleiades Digital Elevation Model Stereo Accuracy Pleiades satellite imagery is very high resolution. with 0.5 m spatial resolution in the panchromatic band and 2.5 m in the multispectral band. Digital elevation models (DEM) are digital models that represent the shape of the Earth's surface in three-dimensional (3D) form. The purpose of this study was to assess DEM accuracy from panchromatic Pleaides imagery. The process conducted was orthorectification using ground control points (GCPs) and the rational function model with rational polynomial coefficient (RFC) parameters. The DEM extraction process employed photogrammetric methods with different parallax concepts. Accuracy assessment was made using 35 independent check points (ICPs) with an RMSE accuracy of ± 0.802 m. The results of the Pleaides DEM image extraction were more accurate than the National DEM (DEMNAS)  and  SRTM DEM. Accuracy testing of DEMNAS results showed an RMSE of ± 0.955 m. while SRTM DEM accuracy was ± 17.740 m. Such DEM extraction from stereo Pleiades panchromatic images can be used as an element on base maps with a scale of 1: 5.000. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13792 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 35-44 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13792/10722 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13793 2025-11-25T07:04:50Z ijreses:ART

SPATIAL DISTRIBUTION OF GREEN OPEN SPACES AND RELATION TO LAND SURFACE TEMPERATURE IN BANDAR LAMPUNG CITY Rizky Cahaya Meikatama Adi Wibowo Iqbal Putut Ash Sidiq Green Open Space Land Surface Temperature Land Cover Bandar Lampung Remote sensing Bandar Lampung City, the capital city of Lampung Province in Indonesia, became the number three city on the island of Sumatra, with enormous population growth from 2000 to 2015. Population growth resulted in increasing built-up land affecting several aspects, one of which was the increase in surface temperature in urban areas. This study aims to determine changes in green open space, land surface temperature (LST), and the spatial pattern of changes in Bandar Lampung City. Data processing uses Landsat 8 imagery for green space and Google Earth Engine for LST. The results of this study indicate that the distribution of changes in green open space the east to west experienced a change in green open space to non-green open space which resulted in an increase in temperature in the east, southeast, and west, from 25-30oC the temperature increased to >30oC. The change in green open space in the west and some areas found that a change from non-RTH to a public or private green open space resulted in a decrease in temperature starting from 25-30oC decreased to 20-25oC. The spatial pattern of changes in green open space in Bandar Lampung City has a clustered pattern in the west and east of the area following the topography (100-500 masl). At the same time, the land surface temperature pattern (LST) in Bandar Lampung City has a clustered pattern at temperatures <20oC, 20-25oC (found at an altitude of 100-500 masl), and >30oC (following an altitude of 25-100 masl) while for temperatures 25-30oC has a scattered pattern (following an altitude of 25-100 masl) in Bandar Lampung City. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13793 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 79-90 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13793/10721 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13794 2025-11-25T06:32:53Z ijreses:ART

DETECTION AND ANALYSIS OF SURFACE URBAN COOL ISLAND USING THERMAL INFRARED IMAGERY OF SALATIGA CITY, INDONESIA Bayu Elwantyo Bagus Dewantoro Panji Mahyatar Wafiq Nur Hayani Thermal Remote Sensing,Land Surface Temperature Urban Microclimate Surface Urban Cool Island The detection and monitoring of the dynamics of urban micro-climatesneeds to be performedeffectively, efficiently, consistently and sustainably inan effort to improve urban resilience to suchphenomena. Thermal remote sensing posesses surface thermal energy detection capabilities which can be converted into surface temperatures and utilised to analyse the urban micro-climate phenomenon overlarge areas, short periods of time, and at low cost. This paper studies the surface urban cool island (SUCI) effect, the reverse phenomenon of the surface urban heat island (SUHI) effect, in an effort to provide cities with resistance to the urban microclimate phenomenon.The study also aims to detect urban micro-climate phenomena, and to calculate the intensity and spatial distribution of SUCI. The methods used include quantitative-descriptive analysis of remote sensing data, including LST extraction, spectral transformation, multispectral classification for land cover mapping, and statistical analysis. The results show that the urban micro-climate phenomenon in the form of SUHI in the middle of the city of Salatiga is due to the high level of building density in the area experiencing the effect, which mostly has a normal surface temperature based on the calculation of the threshold, while the relative SUCI occurs at the edge of the city. SUCI intensity in Salatiga ranges between -6.71°C and0°C and is associated with vegetation. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13794 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 115-126 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13794/10723 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13795 2025-11-25T07:04:50Z ijreses:ART

BIOMASS ESTIMATION MODEL AND CARBON DIOXIDE SEQUESTRATION FOR MANGROVE FOREST USING SENTINEL-2 IN BENOA BAY, BALI A. A. Md. Ananda Putra Suardana Nanin Anggraini Kholifatul Aziz Muhammad Rizki Nandika Azura Ulfa Agung Dwi Wijaya Abd. Rahman As-syakur Gathot Winarso Wiji Prasetio Ratih Dewanti Mangroves remote sensing vegetation indices biomass CO2 sequestration Remote sensing technology can be used to find out the potential of mangrove forests information. One of the potentials is to be able to absorb three times more CO2 than other forests. CO2 absorbed during the photosynthesis process, produces organic compounds that are stored in the mangrove forest biomass. Utilization of remote sensing technology is able to detect mangrove forest biomass using the density level of the vegetation index. This study focuses on determining the best AGB model based on the vegetation index and the ability of mangrove forests to absorb CO2. This research was conducted in Benoa Bay, Bali Province, Indonesia. The satellite image used is Sentinel-2. Classification of mangroves and non-mangroves using a multivariate random forest algorithm. Furthermore, the mangrove forest biomass model using a semi-empirical approach, while the estimation of CO2 sequestration using allometric equations. Mean Absolute Error (MAE) is used to evaluate the validation of the model results. The classification results showed that the detected area of Benoa Bay mangrove forest reached 1134 ha (OA: 0.98, kappa: 0.95). The best AGB estimation result is the DVI-based AGB model (MAE: 23,525) with a value range of 0 to 468.38 Mg/ha. DVI-based AGB derivatives are BGB with a value range of 0 to 79.425 Mg/ha, TAB with a value range of 0 to 547.8 Mg/ha, TCS with a value range of 0 to 257.47 Mg/ha, and ACS with a value range of 0 to 944.912 Mg/ha. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13795 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); 91-100 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13795/10724 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13796 2025-11-25T06:54:33Z ijreses:ART

SPATIAL AND TEMPORAL ANALYSIS OF LAND SURFACE TEMPERATURE CHANGE ON NEW BRITAIN ISLAND Rafika Minati Devi Tofan Agung Eka Prasetya Diah Indriani Land Surface Temperature New Britain Island Climate change Cubic Spline Land Surface Temperature (LST) is a parameter to estimate the temperature of the Earth’s surface and to detect climate change. Papua New Guinea is a tropical country with rainforests, the greatest proportion of which are located on the island of New Britain. Hectares of rainforests have been logged and deforested because of infrastructure construction. This study aims to investigate the change in land surface temperatures on the island from 2000 to 2019. The temperature data were taken from National Aeronautics and Space Administration (NASA) Terra satellites and were analysed using two statistical models: spatial and temporal. The spatial model used multivariate regression, while the temporal one used autoregression (AR). In this study, a cubic spline fitted curve was employed because this has the advantage of being smoother and providing good visuals. The results show that almost all the sub-regions of New Britain have experienced a significant increase in land surface temperature, with a Z value of 7.97 and a confidence interval (CI) of 0.264 – 0.437. The study only investigated land surface temperature change on New Britain Island using spatial and temporal analysis, so further analysis is needed which takes into account other variables such as vegetation and land cover, or which establishes correlations with other variables such as human health. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13796 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 45-56 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13796/10725 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13797 2025-11-25T06:32:53Z ijreses:ART

MONITORING CHANGES IN CORAL REEF HABITAT COVER ON BERALAS PASIR ISLAND USING SPOT 4 AND SPOT 7 IMAGERY FROM 2011 AND 2018 Rosaria Damai Viv Djanat Prasita Kuncoro Teguh Setiawan Monitoring Coral Reefs SPOT 4 SPOT 7 Beralas Pasir Island Beralas Pasir is part of the Regional Marine Conservation Area (KKLD), which was established by the Bintan Regency Government with Bintan Regent Decree No. 261 / VIII / 2007. Water tourism activities undertaken by tourists on the island have had an impact on the condition of the coral reefs, as have other factors, such as bauxite, granite and land sand mining activities around the island. This research aims to determine changes in the coral reef habitat cover and the condition of the coral reefs around Beralas Pasir Island with a remote sensing function, using SPOT 4 imagery acquired on June 1, 2011 and SPOT 7 imagery from April 5, 2020. Data collection of environmental parameters related to the coral reefs was also made. The image processing used the Lyzenga algorithm to simplify the image classification process. The percentage of coral live cover around the island ranges from 26% -53%; this has experienced a significant change, from 67,560 hectares in 2011 to 38,338 hectares in 2018, a total decrease in the area of 29,222 hectares. Some of the natural factors found in the research which have caused damage to the reefs were Drupella snails, the abundance of Caulerpa racemosaalgae, and sea urchins. The majority of the coral reef types consist of Non-Acropora: Coral Massive, Coral, Coral Foliose, Coral Encrusting, Acropora: Acropora Tabulate, Acropora Encrusting, and Acropora Digitate BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13797 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 127-148 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13797/10727 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13798 2025-11-25T07:04:50Z ijreses:BP

Back Pages IJReSES Vol. 19, No. 1 (2022) Journal Manager Back Pages IJReSES Vol. 19, No. 1 (2022) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13798 International Journal of Remote Sensing and Earth Sciences; Vol. 19 No. 1 (2022); I-IV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13798/10726 Copyright (c) 2022 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13802 2025-11-25T07:11:57Z ijreses:FP

Front Pages IJReSES Vol. 16, No. 2 (2019) Journal Editor Front Pages IJReSES Vol. 16, No. 2 (2019) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13802 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); I-XV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13802/10728 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13803 2025-11-25T06:32:53Z ijreses:ART

MULTITEMPORAL ANALYSIS FOR TROPHIC STATE MAPPING IN BATUR LAKE AT BALI PROVINCE BASED ON HIGH-RESOLUTION PLANETSCOPE IMAGERY Rahma Nafila Fitri Sabrina Sudaryatno Freshwater Lakes Ultraoligotrophic TSI Carlson Sulfur Bursts Remote Sensing Remote sensing data for analyzing and evaluating trophic state ecosystem problems seen in Batur Lake isan approach that is suitable for water parameters that cannot be observed terrestrially. As the multitemporal spatial data used in this study were extensive, it was necessary to consider the effectiveness and efficiency of the processing and analysis, therefore R Studio was used as a data processing tool. Theresearch aims to(1) map the trophic state of Batur Lake multitemporally usingPlanetScope Imagery;(2) assess the accuracy of the trophic state model and applyitto anothertemporal data as a SpatialBigData;and (3) understand the trophic state impacton the water quality of Batur Lake based on physical factors andthelake’s chemical concentration (sulfur concentration). Theresearch showsthatthetrophic state of Batur Lake isin good condition,with an ultraoligotrophic state as the majority class,based on the mean Trophic State Index (TSI) value of9.49. The standard errorsof each trophic state parameter were0.010 for total phosphor, 0.609 for chlorophyll-a, and 0.225 for Secchi Disk Transparency (SDT). The multitemporal model demonstratesthat the correlation between the increase oftrophic state and mass fish death cases in Batur Lake is existent. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13803 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 149-162 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13803/10730 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13804 2025-11-25T07:11:57Z ijreses:ART

ROLLING MOSAIC METHOD TO SUPPORT THE DEVELOPMENT OF POTENTIAL FISHING ZONE FORECASTING FOR COASTAL AREAS Komang Iwan Suniada Eko Susilo Wingking Era Rintaka Siwi Nuryani Widagti rolling mosaic potential fishing zone forecast coastal area SST cloud cover The production of the Indonesian Institute for Marine Research and Observation’s mapping of forecast fishing areas (peta prakiraan daerah penangkapan ikan or PPDPI) based on passive satellite imagery is often constrained by high-cloud-cover issues, which lead to sub-optimal results. This study examines the use of the rolling mosaic method for providing geophysical variables, in particular, seasurface temperature (STT) together with minimum cloud cover, to enable clearer identification of oceanographic conditions. The analysis was carried out in contrasting seasons: dry season in July 2018 and rainy season in December 2018. In general, the rolling mosaic method is able to reduce cloud cover for sea-surface temperature (SST) data. A longer time range will increase the coverage percentage (CP) of SST data. In July, the CP of SST data increased significantly, from 15.3 % to 30.29% for the reference 1D mosaic and up to 84.19 % to 89.07% for the 14D mosaic. In contrast, the CP of SST data in December tended to be lower, from 4.93 % to 13.03% in the 1D mosaic to 41.48 % to 51.60% in the14D mosaic. However, the longer time range decreases the relationship between the reference SST data and rolling mosaic method data. A strong relationship lies between the 1D mosaic and 3D mosaics, with correlation coefficients of 0.984 for July and 0.945 for December. Furthermore, a longer time range will decrease root mean square error (RMSE) values. In July, RMSE decreased from 0.288°C (3D mosaic) to 0.471°C (14D mosaic). The RMSE value in December decreased from 0.387°C (3D mosaic) to 0.477°C (14D mosaic). Based on scoring analysis of CP, correlation coefficient and RMSE value, results indicate that the 7D mosaic method is useful for providing low-cloud-coverage SST data for PPDPI production in the dry season, while the 14D mosaic method is suitable for the rainy season. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13804 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 107-120 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13804/10729 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13805 2025-11-25T06:54:33Z ijreses:ART

MAPPING BURNT AREAS USING THE SEMI-AUTOMATIC OBJECT-BASED IMAGE ANALYSIS METHOD Hana Listi Fitriana Suwarsono Eko Kusratmoko Supriatna Burned area Landsat 8 OBIA Forest and land fires in Indonesia take place almost every year, particularly in the dry season and in Sumatra and Kalimantan. Such fires damage the ecosystem, and lower the quality of life of the community, especially in health, social and economic terms. To establish the location of forest and land fires, it is necessary to identify and analyse burnt areas. Information on these is necessary to determine the environmental damage caused, the impact on the environment, the carbon emissions produced, and the rehabilitation process needed. Identification methods of burnt land was made both visually and digitally by utilising satellite remote sensing data technology. Such data were chosen because they can identify objects quickly and precisely. Landsat 8 image data have many advantages: they can be easily obtained, the archives are long and they are visible to thermal wavelengths. By using a combination of visible, infrared and thermal channels through the semi-automatic object-based image analysis (OBIA) approach, the study aims to identify burnt areas in the geographical area of Indonesia. The research concludes that the semi-automatic OBIA approach based on the red, infrared and thermal spectral bands is a reliable and fast method for identifying burnt areas in regions of Sumatra and Kalimantan. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13805 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 57-64 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13805/10731 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13806 2025-11-25T07:11:57Z ijreses:ART

VERTICAL LAND MOTION AND INUNDATION PROCESSES BASED ON THE INTEGRATION OF REMOTELY SENSED DATA AND IPCC AR5 SCENARIOS IN COASTAL SEMARANG, INDONESIA Muhammad Rizki Nandika Setyo Budi Susilo Vincentius Siregar relative sea-level rise interferometry remote sensing InSAR Vertical land motion (VLM) is an important indicator in obtaining information about relative sea-level rise (SLR) in the coastal environment, but this remains an area of study poorly investigated in Indonesia. The purpose of this study is to investigate the significance of the influence of VLM and SLR on inundation. We address this issue for Semarang, Central Java, by estimating VLM using the small baseline subset time series interferometry SAR method for 24 Sentinel-1 satellite data for the period March 2017 to May 2019. The interferometric synthetic aperture radar (InSAR) method was used to reveal the phase difference between two SAR images with two repetitions of satellite track at different times. The results of this study indicate that the average land subsidence that occurred in Semarang between March 2017 and May 2019 was from (-121) mm/year to + 24 mm/year. Through a combination of VLM and SLR scenario data obtained from the Intergovernmental Panel on Climate Change (IPCC), it was found that the Semarang coastal zone will continue to shrink due to inundation (forecast at 7% in 2065 and 10% in 2100). BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13806 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 121-130 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13806/10732 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13807 2025-11-25T06:32:53Z ijreses:ART

MONITORING MODEL OF LAND COVER CHANGE FOR THE INDICATION OF DEVEGETATION AND REVEGETATION USING SENTINEL-2 Samsul Arifin Tatik Kartika Dede Dirgahayu Gatot Nugroho Model Monitoring. Land Cover Sentinel-2 devegetation revegetation IInformation on land cover change is very important for various purposes, including the monitoring of changes for environmental sustainability. The objective of this study is to create a monitoring model of land cover change for the indication of devegetation and revegetation usingdata fromSentinel-2 from 2017 to 2018 of the Brantas watershed.This is one of the priority watersheds in Indonesia, so it is necessary to observe changes in its environment, including land cover change. Such change can be detected using remote sensing data. The method used is a hybrid between Normalized Difference Vegetation Index(NDVI) and Normalized Burn Ratio (NBR) which aims to detect land changes with a focus on devegetationand revegetation by determining the threshold value for vegetation index (ΔNDVI) and open land index (ΔNBR).The study found that the best thresholds to detect revegetation were ΔNDVI > 0.0309 and ΔNBR < 0.0176 and to detect devegetation ΔNDVI < -0.0206 and ΔNBR > 0.0314.It is concluded that Sentinel-2 data can be used to monitor land changes indicating devegetation and revegetation with established NDVI and NBR threshold conditions. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13807 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 163-174 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13807/10735 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13808 2025-11-25T06:54:32Z ijreses:ART

AN ENHANCEMENT TO THE QUANTITATIVE PRECIPITATION ESTIMATION USING RADAR-GAUGE MERGING Abdullah Ali Gumilang Deranadyan Iddam Hairuly Umam Quantitative Precipitation Estimation radar-gauge merging Mean Field Bias Method Quantitative Precipitation Estimation (QPE) is quite important information for the hydrology fields and has many advantages for many purposes. Its dense spatial and temporal resolution can be combined with the surface observation to enhance the accuracy of the estimation. This paper presents an enhancement to the QPE product from BMKG weather radar network at Surabaya by adjusting the estimation value form radar to the real data observation from rain gauge. A total of 58 rain gauge is used. The Mean Field Bias (MFB) method used to determine the correction factor through the difference between radar estimation and rain gauge observation value. The correction factor obtained at each gauge points are interpolated to the entire radar grid in a multiplicative adjustment. Radar-gauge merging results a significant improvement revealed by the decreasing of mean absolute error (MAE) about 40% and false alarm ratio (FAR) as well an increasing of possibility of detection (POD) more than 50% at any rain categories (light rain, moderate rain, heavy rain, and very heavy rain). This performance improvement is very beneficial for operational used in BMKG and other hydrological needs. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13808 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 65-74 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13808/10734 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13809 2025-11-25T07:11:57Z ijreses:ART

FISHING-VESSEL DETECTION USING SYNTHETIC APERTURE RADAR (SAR) SENTINEL-1 (CASE STUDY: JAVA SEA) Sarah Putri Fitriani Jonson Lumban Gaol Dony Kushardono Fishing vessels detection synthetic aperture radar (SAR) Sentinel-1 Java Sea vessel monitoring system (VMS) The synthetic aperture radar (SAR) instrument of Sentinel-1 is a remote sensing technology being developed to enable the detection of vessel distribution. The purpose of this research is to study fishing-vessel detection using SAR Sentinel-1 data. In this study, the constant false alarm rate method (CFAR) for Sentinel-1 data is used for the detection of fishing vessels in Indramayu sea waters. The data used to detect ships includes SAR Sentinel-1A images and vessel monitoring system (VMS) data acquired on 8 March and 20 March 2018. SAR Sentinel-1 imagery data is obtained through pre-processing and object identification using Sentinel Application Platform (SNAP) software. Overlay analysis is then used to enable discrimination of immovable and movable objects and validation of ships detected from SAR Sentinel-1 imagery is performed using VMS data. From overlay analysis, 46 ships were detected on 8 March 2018 and 39 ships on 20 March 2018. Of all the ship points detected using SAR Sentinel-1, 7.06% could be detected by VMS data while 92.94% could not. The number of ships detected by SAR Sentinel-1 is greater than those detected by VMS because not all ships use VMS devices.  BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13809 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 131-142 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13809/10733 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13811 2025-11-25T06:54:32Z ijreses:ART

OPTIMIZATION OF RICE FIELD CLASSIFICATION MODEL BASED ON THRESHOLD INDEX OF MULTITEMPORAL LANDSAT IMAGES Made Parsa Dede Dirgahayu Sri Harini Dony Kushardono multitemporal EVI threshold optimizaton The development of rice land classification models in 2018 has shown that the phenology-based threshold of rice crops from the multi-temporal Landsat image index can be used to classify rice fields relatively well. The weakness of the models was the limitations of the research area, which was confined to the Subang region, West Java, so it is was deemed necessary to conduct further research in other areas. The objective of this study is to obtain optimal parameters of classification model of rice and land based on multi-temporal Landsat image indexes. The study was conducted in several districts of rice production centers in South Sulawesi and West Java (besides Subang). The threshold method was employed for the Landsat Image Enhanced Vegetation Index (EVI). Classification accuracy was calculated in two stages, the first using detailed scale reference information on rice field base, and the second using field data (from a survey). Based on the results of the analysis conducted on several models, the highest accuracy is generated by the three index parameter models (EVI_min, EVI_max, and EVI_range) and adjustable threshold with 94.8% overall accuracy. Therefore this model was acceptable for used for nationally rice fields mapping. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13811 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 75-84 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13811/10737 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13812 2025-11-25T07:11:56Z ijreses:ART

HOTSPOT VALIDATION OF THE HIMAWARI-8 SATELLITE BASED ON MULTISOURCE DATA FOR CENTRAL KALIMANTAN Khalifah Insan Nur Rahmi Sayidah Sulma Indah Prasasti hotspot Himawari-8 validation Landsat 8 forest/land fire The Advanced Himawari Imager (AHI) is the sensor aboard the remote-sensing satellite Himawari-8 which records the Earth’s weather and land conditions every 10 minutes from a geostationary orbit. The imagery produced known as Himawari-8 has 16 bands which cover visible, near infrared, middle infrared and thermal infrared wavelength potentials to monitor forestry phenomena. One of these is forest/land fires, which frequently occur in Indonesia in the dry season. Himawari-8 can detect hotspots in thermal bands 5 and band 7 using absolute fire pixel (AFP) and possible fire pixel (PFP) algorithms. However, validation has not yet been conducted to assess the accuracy of this information. This study aims to validate hotspots identified from Himawari images based on information from Landsat 8 images, field surveys and burnout data. The methodology used to validate hotspots comprises AFP and PFP extraction, determining firespots from Landsat 8, buffering at 2 km from firespots, field surveys, burnout data, and calculation of accuracy. AFP and PFP hotspot validation of firespots from Landsat-8 is found to have higher accuracy than the other options. In using Himawari-8 hotspots to detect land/forest fires in Central Kalimantan, the AFP algorithm with 2km radius has accuracy of 51.33% while the PFP algorithm has accuracy of 27.62%. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13812 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 143-156 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13812/10736 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13813 2025-11-25T06:32:52Z ijreses:ART

INTERSEASONAL VARIABILITY IN THE ANALYSIS OF TOTAL SUSPENDED SOLIDS(TSS) IN SURABAYA COASTAL WATERS USING LANDSAT-8 SATELLITE DATA Bela Karbela Pingkan Mayestika Afgatiani Ety Parwati LRainfall Rate Total Suspended Solids Seasonal Total Suspended Solids Surabaya The spatial and temporal capabilities of remote sensing data are very effective for monitoring the value of total suspended solids(TSS) in water using optical sensors. In this study,TSS observations were conductedin the westseason, transition season 1, east season, and transition season 2 in 2018 and 2019. Landsat 8 image data wereused,extracted into TSS values using a semi-analytic model developed in the Mahakam Delta, East Kalimantan, Indonesia. The TSS data obtained were then analysed for distribution patterns in each season. The sample points were randomly scattered throughout the study area. The TSS distribution pattern in the west season showeda high concentration spread over the coastal area to theoff sea, while the pattern in the east season only showeda high concentration inthecoastal areas. Transitional seasons1 and 2 showed different patterns of TSS distribution in 2018 and 2019, with more varied values. The distribution of TSS is strongly influenced by the season. Observation of each cluster resultedin the conclusion thathuman activity and the rainfall rate can affect the concentration of TSS.   BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13813 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 175-188 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13813/10738 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13815 2025-11-25T06:32:52Z ijreses:ART

A COMPARISON OF RAINFALL ESTIMATION USING HIMAWARI-8 SATELLITE DATA IN DIFFERENT INDONESIAN TOPOGRAPHIES Nadine Ayasha Rainfall Estimation Himawari-8 Satellite Google Maps API The Himawari-8 satellite can be used to derive precipitation data for rainfall estimation. This study aims to test several methods for suchestimation employing the Himawari-8 satellite. The methods are compared in three regions with different topographies, namely Bukittinggi, Pontianak and Ambon. The rainfall estimation methods that are tested are auto estimator, IMSRA, non-linear relation and non-linear inversion approaches. Based on the determination of the statistical verification(RMSE, standard deviation and correlation coefficient) of the amount of rainfall, the best method in Bukittinggi and Pontianak was shown to be IMSRA, while for the Ambon region was the non-linear relations. The best methods from each research area were mapped using the Google Maps Application Programming Interface (API). BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13815 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 189-200 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13815/10741 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13816 2025-11-25T06:54:32Z ijreses:ART

UTILISATION OF NASA - GFWED AND FIRMS SATELLITE DATA IN DETERMINING THE PROBABILITY OF HOTSPOTS USING THE FIRE WEATHER INDEX (FWI) IN OGAN KOMERING ILIR REGENCY, SOUTH SUMATRA Hermanto Asima Nainggolan Desak Putu Okta Veanti Dzikrullah Akbar FWI Hotspots Forest Fires Conditional Probability Prevention and mitigation of forest and land fires have important roles considering its various negative impacts. Throughout 2018, in Ogan Komering Ilir District, 864 hectares of land burned. This data increased significantly compared to the burned area in the previous year. Lack of field meteorological observation is still a problem in solving the problem of forest fire in the region. Consequently, we utilize NASA - GFWED and FIRMS satellite data to analyze the hotspots probabilities in Ogan Komering Ilir District, South Sumatra. Conditional probability analysis will be used to find out the likelihood of hotspots based on FWI and FFMC from 2001 to 2016. More than 50 percent of hotspots appear during extreme FFMC class and high to extreme FWI class. The probability of hotspots for extreme FFMC class and extreme FWI class varied between 0.3 to 10.4 % and 0.1 to 3.8 % respectively. Meanwhile, fire-prone areas with the highest density of fires are in the sub-district of Tulung Selapan, and the safest region is the Cengal sub-district. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13816 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 1 (2020); 85-98 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13816/10739 Copyright (c) 2020 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13817 2025-11-25T07:11:56Z ijreses:ART

CLOUD IDENTIFICATION FROM MULTITEMPORAL LANDSAT-8 USING K-MEANS CLUSTERING Wismu Sunarmodo Anis Kamilah Hayati cloud identification Landsat-8 K-means clustering In the processing and analysis of remote-sensing data, cloud that interferes with earth-surface data is still a challenge. Many methods have already been developed to identify cloud, and these can be classified into two categories: single-date and multi-date identification. Most of these methods also utilize the thresholding method which itself can be divided into two categories: local thresholding and global thresholding. Local thresholding works locally and is different for each pixel, while global thresholding works similarly for every pixel. To determine the global threshold, two approaches are commonly used: fixed value as threshold and adapted threshold. In this paper, we propose a cloud-identification method with an adapted threshold using K-means clustering. Each related multitemporal pixel is processed using K-means clustering to find the threshold. The threshold is then used to distinguish clouds from non-clouds. By using the L8 Biome cloud-cover assessment as a reference, the proposed method results in Kappa coefficient of above 0.9. Furthermore, the proposed method has lower levels of false negatives and omission errors than the FMask method. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article https://ejournal.brin.go.id/ijreses/article/view/13817 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 157-164 2549-516X 0216-6739 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13818 2025-11-25T07:11:56Z ijreses:ART

TENDENCY FOR CLIMATE-VARIABILITY-DRIVEN RISE IN SEA LEVEL DETECTED IN THE ALTIMETER ERA IN THE MARINE WATERS OF ACEH, INDONESIA Guntur Adhi Rahmawan Ulung Jantama Wisha Sea level rise altimeter Aceh waters Indian Ocean Dipole sea level anomaly Long-term sea level rise (SLR) leads to increasing frequency in overtopping events resulting from polar ice liquefaction triggered by rising global temperatures. Aceh province is directly bordered by the Indian Ocean, and is subject to the influence of ocean–atmosphere interactions which have a role in triggering temperature and sea level anomalies. Elevated sea level is possibly caused by temperature-induced water mass redistributions. This study aimed to prove that the Indian Ocean Dipole (IOD) and El-Nino–Southern Oscillation (ENSO) had an influence on sea level change in Aceh waters over the six years 2009–2015. Sea level anomaly (SLA) was identified using Jason-2 satellite data for the 2009–2015 period, to enable the mathematical prediction of SLR rate for further years. We found that SLR was approximately 0.0095 mm/year with an upward trend during the six years of observation. Overall, negative mode of IOD and positive phase of ENSO tend to trigger anomalies of sea level at certain times, and have a stronger influence on increasing SLA and sea surface temperature anomaly (SSTA) which takes place in a ‘see-saw’ fashion. Over the period of observation, the strongest evidence of IOD-correlated SLA, ENSO-correlated SLA and SSTA-correlated SLA were identified in second transitional seasons, with more than 50% of R2 value. The upward trend in SLA is influenced by climatic factors that successively control ocean–atmosphere interactions in Aceh’s marine waters.  BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13818 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 165-178 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13818/10740 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13819 2025-11-25T07:11:56Z ijreses:ART

APPLICATION OF LAND SURFACE TEMPERATURE DERIVED FROM ASTER TIR TO IDENTIFY VOLCANIC GAS EMISSION AROUND BANDUNG BASIN Zaki Hilman Asep Saepuloh Very Susanto Gas emission in volcanic areas is one of the features that can be used for geothermal exploration and to monitor volcanic activity. Volcanic gases are usually emitted in permeable zones in geothermal fields. The use of thermal infrared radiometers (TIR) onboard of advanced spaceborne thermal emission and reflection radiometers (ASTER) aims to detect thermal anomalies at the ground surface related to gas emissions from permeable zones. The study area is located around Bandung Basin, West Java (Indonesia), particularly the Papandayan and Domas craters. This area was chosen because of the easily detected land surface temperature (LST) following emissivity and vegetation corrections (Tcveg). The ASTER TIR images used in this study were acquired by direct night and day observation, including observations made using visible to near-infrared radiometers (VNIR). Field measurements of volcanic gases composed of SO2 and CO2 were performed at three different zones for each of the craters. The measured SO2 concentration was found to be constant over time, but CO2 concentration showed some variation in the craters. We obtained results suggesting that SO2 gas measurements and Tcveg are highly correlated. At Papandayan crater, the SO2 gas concentration was 334.34 ppm and the Tcveg temperature was 35.67 °C,  results that are considered highly anomalous. The same correlation was also found at Domas crater, which showed an increased SO2 gas concentration of 35.39 ppm located at a high-anomaly Tcveg of 30.65 °C. Therefore, the ASTER TIR images have potential to identify volcanic gases as related to high Tcveg. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13819 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 179-186 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13819/10742 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13820 2025-11-25T06:32:52Z ijreses:ART

SHORELINE CHANGES AFTER THE SUNDA STRAIT TSUNAMI ON THE COAST OF PANDEGLANG REGENCY, BANTEN Fandi Dwi Julianto Cahya Riski Fathurohman Salsabila Diyah Rahmawati Taufiq Ihsanudin Landsat-8 Google Earth Engine Abrasion Tanjung Jaya MNDWI The Sunda Strait tsunami occurred on the coast of west Banten and South Lampung at 22nd December 2018, resulting in 437 deaths, with10 victims missing. The disaster had various impacts on the environment and ecosystem, with this area suffering the greatest effects from the disaster. The utilisation of remote sensing technology enables the monitoring of coastal areas in an effective and low-cost manner. Shoreline extraction using the Google Earth Engine, which is an open-source platform that facilitates the processing of a large number of data quickly. This study used Landsat-8 Surface Reflectance Tier 1 data that was geometrically and radiometrically corrected, with processing using the Modification of Normalized Difference Water Index (MNDWI) algorithm. The results show that 30.1% of the coastline in Pandeglang Regency occurred suffered abrasion, 20.2% suffered accretion,while 40.7% saw no change. The maximum abrasion of 130.2 meters occurred in the village of Tanjung Jaya. Moreover, the maximum shoreline accretion was 43.3 meters in the village of Panimbang Jaya. The average shorelinechange in Pandeglang Regencywas 3.9 meters. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13820 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 201-208 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13820/10745 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13821 2025-11-25T07:11:56Z ijreses:ART

CLASSIFICATION OF RICE-PLANT GROWTH PHASE USING SUPERVISED RANDOM FOREST METHOD BASED ON LANDSAT-8 MULTITEMPORAL DATA Dwi Wahyu Triscowati Bagus Sartono Anang Kurnia Dede Dirgahayu Arie Wahyu Wijayanto rice-plant classification temporal autocorrelation temporal features engineering random forest Landsat-8 Data on rice production is crucial for planning and monitoring national food security in a developing country such as Indonesia, and the classification of the growth phases of rice plants is important for supporting this data. In contrast to conventional field surveys, remote sensing technology such as Landsat-8 satellite imagery offers more scalable, inexpensive and real-time solutions. However, utilising Landsat-8 for classification of rice-plant phase required spectral pattern information from one season, because these spectral patterns show the existence of temporal autocorrelation among features. The aim of this study is to propose a supervised random forest method for developing a classification model of rice-plant phase which can handle the temporal autocorrelation existing among features. A random forest is a machine learning method that is insensitive to multicollinearity, and so by using a random forest we can make features engineering to select the best multitemporal features for the classification model. The experimental results deliver accuracy of 0.236 if we use one temporal feature of vegetation index; if we use more temporal features, the accuracy increases to 0.7091. In this study, we show that the existence of temporal autocorrelation must be captured in the model to improve classification accuracy. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13821 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 187-196 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13821/10746 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13822 2025-11-25T07:14:34Z ijreses:FP

Front Pages IJReSES Vol. 15, No. 1(2018) Journal Editor Front Pages IJReSES Vol. 15, No. 1(2018) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13822 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); I-III 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13822/10743 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13823 2025-11-25T07:14:34Z ijreses:ART

MAPPING APATITE-ILMENITE RARE EARTH ELEMENT MINERALIZED ZONE USING FUZZY LOGIC METHOD IN SIJUK DISTRICT, BELITUNG Muhamad Iqbal Januadi Putra Sobirin Apatite-ilmenite fuzzy logic Landsat 8 Rare earth elements District of Sijuk located in Belitung Island is rich with non-lead mineral content. As the part of Southeast Asia’s Lead Belt, the presence of Apatite-Ilmenite Rare Earth Element formed by the region’s geological condition is very likely. However, there has not been any activity to map and identify the apatite-ilmenite distribution in this region. Therefore, the objective of this study was to map the mineralized apatite-ilmenite in Sijuk District. Using remote sensing technology, Landsat 8 OLI were utilized to map the distribution of mineralized apatite-ilmenite rare earth element. Alteration mineral carrier, geological structure, and lithology data were all used as variables. Landsat-8 was pre-processed using band ratio and Directed Principal Component Analysis (DPCA) method for gaining alteration variable. The fuzzy logic method was then deployed for integrating all data. The result of this research showed the potential distribution of mineralized apatite-ilmenite with a total area of 1,617 ha. The most prioritized areas for apatite-ilmenite mineral exploitation are located in Air Seruk Village’s IUP (Izin Usaha Pertambangan/Mining Business License), Sijuk Village’s IUP, and Batu Itam Village’s IUP. This study also illustrates the orientation of the metal utilization of apatite-ilmenite in district Sijuk. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13823 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 1-14 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13823/10747 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13824 2025-11-25T06:32:52Z ijreses:ART

BATHYMETRIC EXTRACTION USING PLANETSCOPE IMAGERY (CASE STUDY: KEMUJAN ISLAND, CENTRAL JAVA) Asih Sekar Sesama Kuncoro Teguh Setiawan Atriyon Julzarika marine resources activity Stumpf algorithm Karimun Jawa Island remote sensing water characteristics Bathymetry refers to the depth of the seabed relative to the lowest water level. Depth information is essential for various studies of marine resource activities, for managing port facilities and facilities, supporting dredging operations, and predicting the flow of sediment from rivers into the sea. Bathymetric mapping using remote sensing offers a more flexible, efficient,and cost-effective method and covers a largearea. This study aims to determine the ability of Planet Scope imagery to estimate and map bathymetry and to as certain its accuracy using the Stumpf algorithm on the in-situ depth data. PlanetScope level 3B satellite imagery and tide-corrected survey dataare employed; satellite images are useful in high-precision bathymetry extraction.The bathymetric extraction method used the Stumpf algorithm. The research location was Kemujan Island, Karimunjawa Islands, Central Java. The selection of this region wasbased on its water characteristics, which have a reasonably high variation in depth. Based on the results of the data processing, it was found that the PlanetScope image data were able to estimate depths of up to 20 m. In the bathymetric results, the R2 accuracy value was 0.6952, the average RMSE value was 2.85 m,and the overall accuracy rate was 71.68%. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13824 International Journal of Remote Sensing and Earth Sciences; Vol. 17 No. 2 (2020); 209-216 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13824/10749 Copyright (c) 2020 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13825 2025-11-25T07:11:55Z ijreses:ART

MONITORING OF MANGROVE GROWTH AND COASTAL CHANGES ON THE NORTH COAST OF BREBES, CENTRAL JAVA, USING LANDSAT DATA Tri Muji Susantoro Ketut Wikantika Lissa Fajri Yayusman Alex Tan M. Firman Ghozali abrasion accretion NDVI GNDVI Severe abrasion occurred in the coastal area of Brebes Regency, Central Java between 1985 and 1995. Since 1997, mangroves have been planted around the location as a measure intended to prevent further abrasion. Between 1996 and 2018, monitoring has been carried out to assess coastal change in the area and the growth and development of the mangroves. This study aims to monitor mangrove growth and its impact on coastal area changes on the north coast of Brebes, Central Java Province using Landsat series data, which has previously proven suitable for wetland studies including mangrove growth and change. Monitoring of mangrove growth was analysed using the normalised difference vegetation index (NDVI) and the green normalised difference vegetation index (GNDVI) of the Landsat data, while the coastal change was analysed based on the overlaying of shoreline maps. Visual field observations of WorldView 2 images were conducted to validate the NDVI and GNDVI results. It was identified from these data that the mangroves had developed well during the monitoring period. The NDVI results showed that the total mangrove area increased between 1996 and 2018 about 9.82 km2, while the GNDVI showed an increase of 3.20 km2. Analysis of coastal changes showed that the accretion area about 9.17 km2 from 1996 to 2018, while the abrasion being dominant to the west of the Pemali River delta about 4.81 km2. It is expected that the results of this study could be used by government and local communities in taking further preventative actions and for sustainable development planning for coastal areas. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13825 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); 197-214 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13825/10748 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13829 2025-12-19T06:51:02Z ijreses:FP

Front Pages IJReSES Vol. 16, No. 1 (2019) Editor Journal Front Pages IJReSES Vol. 16, No. 1 (2019) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13829 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); I-V 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13829/10750 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13830 2025-12-19T06:51:02Z ijreses:ART

THE UTILIZATION OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS FOR ANALYSIS OF LAND SUITABILITY FOR THE GROWING OF CIPLUKAN (PHYSALIS ANGULATA L.) Nur Adliani Nirmawana Simarmata Heriansyah remote sensing aerial photos GIS Physalis angulata L. land suitability Remote sensing data and geographic information systems are widely used for land suitability analysis for crops such as coffee and corn. This study aims to analyze and map suitable land for the plant known locally as ciplukan (Physalis angulata L.).  As the cultivation of this plant is expected to be developed by the Institute of Technology of Sumatra, analysis of this type is needed. The parameters used in this study were slope, land use, rainfall and soil type. Information extraction from remote sensing data was carried out via visual interpretation of aerial photography used to create land-cover maps. Shuttle RADAR Topographic Mission (SRTM) data was converted from digital surface model (DSM) to digital terrain model (DTM) to provide elevation information. Land suitability analysis was performed using a scoring method and overlay analysis. The results obtained from the analysis identified several classes of land suitability for Physalis angulata L., categorized as suitable, less suitable, and not suitable. The less suitable class, scored at 9 to 11, comprised a total area of 180.96 ha, while the suitable area, scored at 12, comprised a total area of 49.1 ha. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13830 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 1-12 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13830/10752 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13832 2025-11-25T07:14:33Z ijreses:ART

SPECTRAL ANALYSIS OF THE HIMAWARI-8 DATA FOR HOTSPOT DETECTION FROM LAND/FOREST FIRES IN SUMATRA Hana Listi Fitriana Sayidah Sulma Any Zubaidah Suwarsono Indah Prasasti Himawari-8 hotspot spectral Himawari-8 is the last generation of the low spatial resolution satellite imagery that has capability to detect the thermal variation on the earth of every 10 minute. This must be very potential to be used for detecting land/forest fire. This paper has explored the spectral prospective of the Himawari-8 for detecting land/forest fire hotspot. The main objective for this study is to identify the potential use of Himawari-8 for detecting of land forest fire hotspot. The study area was performed in Ogan Komering Ilir, South of Sumatra, which on 2015 occur great forest/land fire event. The main process included in this study are image projection, training sample collection and spectral statistical analysis measured by calculate statistic, they are average values, standard deviation values from reflectance visible band value and brightness temperature value, beside that validation of data obtained from medium resolution data of Landsat 8 with the similar acquisition time. The study found that the Himawari-8 has good capacity to identify land/forest fire hotspot as expressed for high accuracy assessment using band 3 and band 7. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13832 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 15-24 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13832/10754 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13833 2025-12-19T06:51:02Z ijreses:ART

RETRIEVING COASTAL SEA SURFACE TEMPERATURE FROM LANDSAT-8 TIRS FOR WANGI-WANGI ISLAND, WAKATOBI, SOUTHEAST SULAWESI, INDONESIA Eko Susilo Rizki Hanintyo Adi Wijaya Landsat-8 single-band algorithm split-window algorithm The new Landsat generation, Landsat-8, is equipped with two bands of thermal infrared sensors (TIRS). The presence of two bands provides for improved determination of sea surface temperature (SST) compared to existing products. Due to its high spatial resolution, it is suitable for coastal zone monitoring. However, there are still significant challenges in converting radiance measurements to SST, resulting from the limitations of in-situ measurements. Several studies into developing SST algorithms in Indonesia waters have provided good performance. Unfortunately, however, they have used a single-band windows approach, and a split-windows approach has yet to be reported. In this study, we investigate both single-band and split-window algorithms for retrieving SST maps in the coastal zone of Wangi-Wangi Island, Wakatobi, Southeast Sulawesi, Indonesia. Landsat-8 imagery was acquired on February 26, 2016 (01: 51: 44.14UTC) at position path 111 and and row 64. On the same day, in-situ SST was measured by using Portable Multiparameter Water Quality Checker – 24. We used the coefficient of correlation (r) and root mean square error (RMSE) to determine the best algorithm performance by incorporating in-situ data and the estimated SST map. The results showed that there were differences in brightness temperature retrieved from TIRS band10 and band 11. The single-band algorithm based on band 10 for Poteran Island clearly showed superior performance (r = 69.28% and RMSE = 0.7690°C). This study shows that the split-window algorithm has not yet produced a accurate result for the study area. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13833 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 13-22 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13833/10753 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13834 2025-12-19T06:51:01Z ijreses:ART

BATHYMETRY EXTRACTION FROM SPOT 7 SATELLITE IMAGERY USING RANDOM FOREST METHODS Kuncoro Teguh Setiawan Nana Suwargana Devica Natalia BR Ginting Masita Dwi Mandini Manessa Nanin Anggraini Syifa Wismayati Adawiah Atriyon Julzarika Surahman Syamsu Rosid Agustinus Harsono Supardjo bathymetry random forest SPOT 7 The scope of this research is the application of the random forest method to SPOT 7 data to produce bathymetry information for shallow waters in Indonesia. The study aimed to analyze the effect of base objects in shallow marine habitats on estimating bathymetry from SPOT 7 satellite imagery. SPOT 7 satellite imagery of the shallow sea waters of Gili Matra, West Nusa Tenggara Province was used in this research. The estimation of bathymetry was carried out using two in-situ depth-data modifications, in the form of a random forest algorithm used both without and with benthic habitats (coral reefs, seagrass, macroalgae, and substrates). For bathymetry estimation from SPOT 7 data, the first modification (without benthic habitats) resulted in a 90.2% coefficient of determination (R2) and 1.57 RMSE, while the second modification (with benthic habitats) resulted in an 85.3% coefficient of determination (R2) and 2.48 RMSE. This research showed that the first modification achieved slightly better results than the second modification; thus, the benthic habitat did not significantly influence bathymetry estimation from SPOT 7 imagery BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13834 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 23-30 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13834/10755 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13835 2025-11-25T07:14:33Z ijreses:ART

THREE-WAY ERROR ANALYSIS OF SEA SURFACE TEMPERATURE (SST) BETWEEN HIMAWARI-8, BUOY, AND MUR SST IN SAVU SEA Bambang Sukresno Rizki Hanintyo Denny Wijaya Kusuma Dinarika Jatisworo Ari Murdimanto Sea surface temperature (SST) Himawari-8 Buoy data MUR SST Validation Variance errors of Himawari-8, buoy, and Multi-scale Ultra-high Resolution (MUR) SST in Savu Sea have been investigated. This research used level 3 Himawari-8 hourly SST, in situ measurement of buoy, and daily MUR SST in the period of December 2016 to July 2017. The data were separated into day time data and night time. Skin temperature of Himawari-8 and subskin tempertaure of MUR SST were corrected with the value of 15∆Tdept">  before compared with buoy data. Hourly SST of Himawari-8 and buoy data were converted to daily format by averaging process before collocated with MUR SST data. The number of 2,264 matchup data are obtained. Differences average between Himawari-8, buoy and MUR SST were calculated to get the value of variance (Vij).  Using three-way error analysis, variance errors of each observation type can be known. From the analysis results can be seen that the variance error of Himawari-8, buoy and MUR SST are 2.5 oC, 0.28oC and 1.21oC respectively. The accuracy of buoy data was better than the other. With a small variance errors, thus buoy data can be used as a reference data for validation of SST from different observation type. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13835 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 25-36 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13835/10756 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13836 2025-12-19T06:51:01Z ijreses:ART

THE USE OF C-BAND SYNTHETIC APERTURE RADAR SATELLITE DATA FOR RICE PLANT GROWTH PHASE IDENTIFICATION Anugrah Indah Lestari Dony Kushardono remote sensing satellite SAR C-band texture feature rice plant growth phase Identification of the rice plant growth phase is an important step in estimating the harvest season and predicting rice production. It is undertaken to support the provision of information on national food availability. Indonesia’s high cloud coverage throughout the year means it is not possible to make optimal use of optical remote sensing satellite systems. However, the Synthetic Aperture Radar (SAR) remote sensing satellite system is a promising alternative technology for identifying the rice plant growth phase since it is not influenced by cloud cover and the weather. This study uses multi-temporal C-Band SAR satellite data for the period May–September 2016. VH and VV polarisation were observed to identify the rice plant growth phase of the Ciherang variety, which is commonly planted by farmers in West Java. Development of the rice plant growth phase model was optimized by obtaining samples spatially from a rice paddy block in PT Sang Hyang Seri, Subang, in order to acquire representative radar backscatter values from the SAR data on the age of certain rice plants. The Normalised Difference Polarisation Index (NDPI) and texture features, namely entropy, homogeneity and the Grey-Level Co-occurrence Matrix (GLCM) mean, were included as the samples. The results show that the radar backscatter value (σ0) of VH polarisation without the texture feature, with the entropy texture feature and GLCM mean texture feature respectively exhibit similar trends and demonstrate potential for use in identifying and monitoring the rice plant growth phase. The rice plant growth phase model without texture feature on VH polarisation is revealed as the most suitable model since it has the smallest average error. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13836 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 31-44 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13836/10758 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13837 2025-11-25T07:11:55Z ijreses:BP

Back Pages IJReSES Vol. 16, No. 2 (2019) Journal Editor Back Pages IJReSES Vol. 16, No. 2 (2019) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13837 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 2 (2019); I-VII 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13837/10759 Copyright (c) 2019 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13838 2025-12-19T06:51:01Z ijreses:ART

DETECTING DEFORMATION DUE TO THE 2018 MERAPI VOLCANO ERUPTION USING INTERFEROMETRIC SYNTHETIC APERTURE RADAR (INSAR) FROM SENTINEL-1 TOPS Suwarsono Indah Prasasti Jalu Tejo Nugroho Jansen Sitorus Rahmat Arief Khalifah Insan Nur Rahmi Djoko Triyono Vertical displacement Landsat-8 TIRS InSAR Sentinel-1 TOPS SAR This paper describes the application of Sentinel-1 TOPS (Terrain Observation with Progressive Scans), the latest generation of SAR satellite imagery, to detect displacement of the Merapi volcano due to the May–June 2018 eruption. Deformation was detected by measuring the vertical displacement of the surface topography around the eruption centre. The Interferometric Synthetic Aperture Radar (InSAR) technique was used to measure the vertical displacement. Furthermore, several Landsat-8 Thermal Infra Red Sensor (TIRS) imageries were used to confirm that the displacement was generated by the volcanic eruption. The increasing temperature of the crater was the main parameter derived using the Landsat-8 TIRS, in order to determine the increase in volcanic activity. To understand this phenomenon, we used Landsat-8 TIRS acquisition dates before, during and after the eruption. The results show that the eruption in the May–June 2018 period led to a small negative vertical displacement. This vertical displacement occurred in the peak of volcano range from -0.260 to -0.063 m. The crater, centre of eruption and upper slope of the volcano experienced negative vertical displacement. The results of the analysis from Landsat-8 TIRS in the form of an increase in temperature during the 2018 eruption confirmed that the displacement detected by Sentinel-1 TOPS SAR was due to the impact of volcanic activity. Based on the results of this analysis, it can be seen that the integration of SAR and thermal optical data can be very useful in understanding whether deformation is certain to have been caused by volcanic activity. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13838 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 45-54 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13838/10763 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13840 2025-11-25T07:14:33Z ijreses:ART

BIOMASS ESTIMATION MODEL FOR MANGROVE FOREST USING MEDIUM-RESOLUTION IMAGERIES IN BSN CO LTD CONCESSION AREA, WEST KALIMANTAN Sendi Yusandi I Nengah Surati Jaya Fairus Mulia mangrove forests biomass model score NDVI Mangrove forest is one of the forest ecosystem types that have the highest carbon stock in the tropics. Mangrove forests have a good assimilation capability with their environmental elements as well as on carbon sequestration. However, the availability of data and information on carbon storage, especially on tree biomass content of mangrove is still limited. Conventionally, an accurate estimation of biomass could be obtained from terrestrial measurements, but those methods are very costly and time-consuming. This study offered an alternative solution to overcome these limitations by using remote sensing technology, i.e. by using Landsat 8 and SPOT 5. The objective of this study is to formulate the biomass estimation model using medium resolution satellite imagery, as well as to develop a biomass distribution map based on the selected model. The study found that the NDVI of Landsat 8 and SPOT 5 have considerably high correlation coefficients with the standing biomass with a value of higher than 0.7071. On the basis of the values of aggregation deviation, mean deviation, bias, RMSE, χ², R², and s, the best model for estimating the mangrove stand biomass for Landsat 8 is B=0.00023404 e(20 NDVI) with the R² value of 77.1% and B=0.36+25.5 NDVI² with the R² value of 49.9% for SPOT 5. In general, the concession area of Bina Silva Nusa (BSN) Group (PT Kandelia Alam and PT Bina Ovivipari Semesta) have the potential of biomass ranging from 45 to 100 ton per ha. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13840 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 37-50 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13840/10762 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13841 2025-11-25T07:19:23Z ijreses:FP

Front Pages IJReSES Vol. 15, No. 2 (2018) Editor Journal Front Pages IJReSES Vol. 15, No. 2 (2018) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13841 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); I-XV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13841/10765 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13842 2025-12-19T06:51:01Z ijreses:ART

VARIABILITY OF SEA SURFACE TEMPERATURE (SST) AND CHLOROPHYLL-A (CHL-A) CONCENTRATIONS IN THE EASTERN INDIAN OCEAN DURING THE PERIOD 2002–2017 Michelia Mashita Jonson Lumban-Gaol sea surface temperature chlorophyll-a eastern Indian ocean aqua MODIS monsoon upwelling IOD We analysed the variability of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) in the eastern Indian Ocean (EIO). We used monthly mean Chl-a and SST data with a 4-km spatial resolution derived from Level-3 Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) distributed by the Asia-Pacific Data-Research Center (APDRC) for the period 2002–2017. Wavelet analysis shows the annual and interannual variability of SST and Chl-a concentration in the EIO. The annual variability of SST and Chl-a is influenced by monsoon systems. During a southeast monsoon, SST falls while Chl-a increases due to upwelling. The annual variability of SST and Chl-a is also influenced by the Indian Ocean Dipole (IOD). During positive phases of the IOD (2006, 2012 and 2015), there was more intense upwelling in the EIO caused by the negative anomaly of SST and the positive anomaly of Chl-a concentration. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13842 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 55-62 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13842/10764 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13843 2025-11-25T07:14:33Z ijreses:ART

STUDY ON POTENTIAL FISHING ZONES (PFZ) INFORMATION BASED ON S-NPP VIIRS AND HIMAWARI-8 SATELLITES DATA Sartono Marpaung Teguh Prayogo Ety Parwati Kuncoro Teguh Setiawan Orbita Roswintiarti Potential fishing zones S-NPP VIIRS Himawari-8 satellite coordinate points Sea surface temperature (SST) data from S-NPP VIIRS satellite has different spatial resolution with SST data from Himawari-8 satellite. In this study comparative analysis of potential fishing zones information from both satellites has been conducted. The analysis was conducted on three project areas (PA 7, PA 13, PA 19) as a representation Indonesian territorial waters. The data used were daily  for both satellites with a period  time from August 2016 to December 2016. The method used was Single Image Detection (SIED) to detect thermal fronts. Method of mass center point for determining potential fishing zones coordinate point from result thermal front detection. Furthermore, an analysis of overlapping was done to compare the coordinate point information from both satellites. Based on data analysis that had been done, the result showed that potential fishing zones coordinate points of Himawari-8 satellite was mostly far from potential fishing zones coordinate point of S-NPP VIIRS. The coordinate points whose positionswere close together or nearly same from both satellites was only about 20 %. Differences in potential fishing zones coordinate positions occur due to the effect of different spatial resolutions of both satellite data and the size of the front thermal events that had high variability. The ideal potential fishing zones coordinate points information was probably a combination of the potential fishing zones coordinate points of S-NPP VIIRS and Himawari-8 by making two adjacent coordinate points to be a single coordinate point. Field validation testing was required to prove the accuracy of the coordinate point. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13843 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 51-62 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13843/10766 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13844 2025-12-19T06:51:01Z ijreses:ART

IDENTIFICATION OF MANGROVE FORESTS USING MULTISPECTRAL SATELLITE IMAGERIES Anang Dwi Purwanto Wikanti Asriningrum Mangrove OIF Landsat 8 Sentinel 2A SPOT 6 Combinations The visual identification of mangrove forests is greatly constrained by combinations of RGB composite. This research aims to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using the Optimum Index Factor (OIF) method. The OIF method uses the standard deviation value and correlation coefficient from a combination of three image bands. The image data comprise Landsat 8 imagery acquired on 30 May 2013, Sentinel 2A imagery acquired on 18 March 2018 and images from SPOT 6 acquired on 10 January 2015. The results show that the band composites of 564 (NIR+SWIR+Red) from Landsat 8 and 8a114 (Vegetation Red Edge+SWIR+Red) from Sentinel 2A are the best RGB composites for identifying mangrove forest, in addition to those of 341 (Red+NIR+Blue) from SPOT 6. The near-infrared (NIR) and short-wave infrared (SWIR) bands play an important role in determining mangrove forests. The properties of vegetation are reflected strongly at the NIR wavelength and the SWIR band is very sensitive to evaporation and the identification of wetlands. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13844 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 63-86 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13844/10767 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13845 2025-11-25T07:19:23Z ijreses:ART

ACCURACY EVALUATION OF STRUCTURE FROM MOTION THERMAL MOSAICING IN THE CENTER OF TOKYO Atik Nurwanda Nobumitsu Tsunematsu Hitoshi Yokoyama accuracy evaluation the center of Tokyo georeferencing structure from motion land surface temperature orthogonal In the airborne and high-resolution measurement of Land Surface Temperature (LST) over large area, capturing and synthesizing of many images are necessary. In the conventional method, the process of georeferencing a large number of LST images is necessary to make one large image. Structure from Motion (SfM) technique was applied to automized the georeferencing process. We called it “SfM Thermal Mosaicingâ€. The objective of this study is to evaluate the accuracy of SfM thermal mosaicing in making an orthogonal LST image. By using airborne thermal images in the center of Tokyo, the LST image with the 2m resolution was created by using SfM thermal mosaicing. Its accuracy was then analyzed. The result showed that in the whole examined area, the mean error distance was 4.22m and in the small parts of the examined area, the mean the error distance was about 2m. Considering the image resolution, the error was minimal indicating good performance of the SfM thermal mosaicing. Another advantage of SfM thermal mosaicing is that it can make precise orthogonal LST image. With the progress of UAV and thermal cameras, the proposed method will be a powerful tool for the environmental researches on the LST. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13845 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 103-112 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13845/10769 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13847 2025-11-25T07:14:33Z ijreses:ART

WATERMARKING METHOD OF REMOTE SENSING DATA USING STEGANOGRAPHY TECHNIQUE BASED ON LEAST SIGNIFICANT BIT HIDING Destri Yanti Hutapea Octaviani Hutapea Steganography least significant bit security Remote sensing satellite imagery is currently needed to support the needs of information in various fields. Distribution of remote sensing data to users is done through electronic media. Therefore, it is necessary to make security and identity on remote sensing satellite images so that its function is not misused. This paper describes a method of adding confidential information to medium resolution remote sensing satellite images to identify the image using steganography technique. Steganography with the Least Significant Bit (LSB) method is chosen because the insertion of confidential information on the image is performed on the rightmost bits in each byte of data, where the rightmost bit has the smallest value. The experiment was performed on three Landsat 8 images with different area on each composite band 4,3,2 (true color) and 6,5,3 (false color). Visually the data that has been inserted information does not change with the original data. Visually, the image that has been inserted with confidential information (or stego image) is the same as the original image. Both images cannot be distinguished on histogram analysis.  The Mean Squared Error value of stego images of  all three data less than 0.053 compared with the original image. Â This means that information security with steganographic techniques using the ideal LSB method is used on remote sensing satellite imagery. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13847 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 63-70 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13847/10768 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13848 2025-12-19T06:51:00Z ijreses:ART

DETECTING AND COUNTING COCONUT TREES IN PLEIADES SATELLITE IMAGERY USING HISTOGRAM OF ORIENTED GRADIENTS AND SUPPORT VECTOR MACHINE Yudhi Prabowo Kenlo Nishida Nasahara coconut trees Pleiades imagery tree detection histogram of oriented gradient support vector machine This paper describes the detection of coconut trees using very-high-resolution optical satelliteimagery. The satellite imagery used in this study was a panchromatic band of Pleiades imagery with aspatial resolution of 0.5 metres. The authors proposed the use of a histogram of oriented gradients(HOG) algorithm as the feature extractor and a support vector machine (SVM) as the classifier for thisdetection. The main objective of this study is to find out the parameter combination for the HOGalgorithm that could provide the best performance for coconut-tree detection. The study shows that thebest parameter combination for the HOG algorithm is a configuration of 3 x 3 blocks, 9 orientation bins,and L2-norm block normalization. These parameters provide overall accuracy, precision and recall ofapproximately 80%, 73% and 87%, respectively. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13848 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 87-98 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13848/10770 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13849 2025-11-25T07:19:23Z ijreses:ART

ANALYSIS OF ANTENNA SPECIFICATION FOR VERY HIGH RESOLUTION SATELLITE DATA ACQUISITION THROUGH DIRECT RECEIVING SYSTEM (DRS) Muchammad Soleh Ali Syahputra Nasution Arif Hidayat Hidayat Gunawan Ayom Widipaminto VHRSI Optic SAR Direct Receiving System (DRS) Antenna Very High Resolution Satellite Image (VHRSI) data for Indonesian Government license is required by ministries/agencies, TNI, police, and local government to support national programs. But Indonesia did not have a VHRSI data recipient facility to directly acquire this data. In accordance with Law 21/2013 on Space, LAPAN is mandate to provide high resolution satellite data, and based on a roadmap for provision of satellite data in 2017, LAPAN will provide a VHRSI data reception facility through direct receiving system (DRS). This will be more efficient than other methods in providing the data. Priority provision of satellite data is for acquiring Pleiades and TerraSAR-X operating in the frequency range 8 GHz (X-Band). Therefore, to receive both data, it requires antenna subsystem with optimum coverage throughout Indonesia. Parameters to obtain the minimum antenna specifications include Free Space Loss (FSL), Carrier to Noise Ratio (C/No) and Antenna Gain to Noise Temperature (G/T). The calculation of G/T antenna is done for both satellites based on satellite parameters and analysis of antenna product availability in the market. Based on the calculation of satellite parameters shows that the minimum G/T value with the elevation of 5 degrees is 27.71 dB/K for Pleiades data reception and the minimum G/T value of 26.10 dB/K for the TerraSAR-X data reception. In general, the minimum G/T value for receiving the Pleiades and TerraSAR-X data is at 28 dB/K. While based on the calculation of antenna products availability in the market is require G/T value of 33.45 dB /K for the elevation of 5 degrees with a diameter of 7.5 mm antenna. This can be conclude that the antenna products meets the minimum requirements specification and to receive both satellite data.  However, both calculation for the antenna subsystem still will be evaluated further in order to be directly installed at Parepare Remote Earth Station (SPBJ), South Sulawesi. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13849 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 113-130 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13849/10771 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13851 2025-12-19T06:51:00Z ijreses:ART

INTEGRATION OF GIS AND REMOTE SENSING FOR HOTSPOT DISTRIBUTION ANALYSIS IN BERBAK SEMBILANG NATIONAL PARK Andita Minda Mora Bambang Hero Saharjo Lilik Budi Prasetyo Berbak Sembilang National Park Getis-Ord-Gi hotspot fire distribution land use and land cover Abstract. Remote sensing is composed of many interrelated processes to be able to consider physical objects such as buildings, land, and plants which are objects that can be discussed by applications discussed in various disciplines that discuss geology, forestry, soil science, and geography. The use of GIS and remote sensing for fire monitoring has been widely used. However, this study is the first study conducted in the TNBS area after the Berbak National Park (TNB) in Jambi to join the Sembilang National Park (TNS) in South Sumatra. Hotspot distribution in this study was obtained using Getis-Ord-Gi * statistics, hotspot data collected from 2000-2018 in the TNBS area. The results of the hotspot distribution during the 2000-2018 recorded by MODIS satellites with time acquisition and statistical analysis using Gi* show the results that the hotspots gathered (80% confidence level) outside the TNBS area, which is a mixed fields area. Further studies on causes of fire in terms of socio-economic and cultural needs to be done to get the right advice in reducing the risk of loss of forest cover and diversity in TNBS. Keywords: mitigation, hydrology, DAS BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13851 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); 99-106 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13851/10773 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13852 2025-11-25T07:19:23Z ijreses:ART

OBSERVING THE INUNDATED AREA USING LANDSAT-8 MULTITEMPORAL IMAGES AND DETERMINATION OF FLOOD-PRONE AREA IN BANDUNG BASIN Fajar Yulianto Suwarsono Sayidah Sulma Muhammad Rokhis Khomarudin inundated area flood-prone area Bandung basin Landsat-8 MNDWI Flood is the most frequent hydro-meteorological disaster in Indonesia. Flood disasters in the Bandung basin result from increasing population density, especially in the Citarum riverbank area, accompanied by land use changes in upstream of the Citarum catchment area which has disrupted the river’s function. One of the basic issues that need to be investigated is which areas of the Bandung basin are prone to flooding. This study offers an effective and efficient method of mapping flood-prone areas based on flood events that have occurred in the past through the use of historical remote sensing image data. In this research, Landsat-8 imagery was used to observe the inundated area in the Bandung basin in the past (2014–2018) using an improved algorithm, the modified normalized water index (MNDWI). The results of the study show that MNDWI is the appropriate parameter to be used to detect flooded areas in the Bandung basin area that have heterogeneous land surface conditions. The flood-prone area was determined based on flood events for 2014 to 2018, identified as inundated areas in the images. The estimation of the flood-prone area in the Bandung basin is 11,886.87 ha. Most of the flood-prone areas are in the subdistricts of Rancaekek, Bojongsoang, Solokan Jeruk, Ciparay, Cileunyi, Bale Endah and Cikancung. This area geographically or naturally is a water habitat area. Therefore, if the area will be used for residential, this will have consequences that flood will always be a threat to the area.  BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13852 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 131-140 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13852/10772 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13854 2025-11-25T07:19:22Z ijreses:ART

MANGROVE FOREST CHANGE IN NUSA PENIDA MARINE PROTECTED AREA, BALI - INDONESIA USING LANDSAT SATELLITE IMAGERY August Daulat Widodo Setiyo Pranowo Syahrial Nur Amri mangrove changes Nusa Penida MPA remote sensing NDVI Nusa Penida, Bali was designated as a Marine Protected Area (MPA) by the Klungkung Local Government in 2010 with support from the Ministry of Marine Affairs and Fisheries, Republic of Indonesia. Mangrove forests located in Nusa Lembongan Island inside the Nusa Penida MPA jurisdiction have decreased in biomass quality and vegetation cover. It’s over the last decades due to influences from natural phenomena and human activities, which obstruct mangrove growth. Study the mangrove forest changes related to the marine protected areas implementation are important to explain the impact of the regulation and its influence on future conservation management in the region. Mangrove forest in Nusa Penida MPA can be monitored using remote sensing technology, specifically Normalized Difference Vegetation Index (NDVI) from Landsat satellite imagery combined with visual and statistical analysis. The NDVI helps in identifying the health of vegetation cover in the region across three different time frames 2003, 2010, and 2017. The results showed that the NDVI decreased slightly between 2003 and 2010. It’s also increased significantly by 2017, where a mostly positive change occurred landwards and adverse change happened in the middle of the mangrove forest towards the sea. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13854 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 141-156 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13854/10777 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13856 2025-12-19T06:51:00Z ijreses:BP

Back Pages IJReSES Vol. 16, No. 1 (2019) Editor Journal Back Pages IJReSES Vol. 16, No. 1 (2019)   BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13856 International Journal of Remote Sensing and Earth Sciences; Vol. 16 No. 1 (2019); I-III 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13856/10774 Copyright (c) 2019 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13857 2025-11-25T07:14:33Z ijreses:ART

LAPAN-A3 SATELLITE DATA ANALYSIS FOR LAND COVER CLASSIFICATION (CASE STUDY: TOBA LAKE AREA, NORTH SUMATRA) Jalu Tejo Nugroho Dony Kushardono Zylshal LAPAN-A3 micro satellite land cover pixel-based classification LAPAN-A3 is the 3rdgeneration satellite for remote sensing developed by National Institute of Aeronautics and Space (LAPAN). The camera provides imagery with 15 m spatial resolution and able to view a swath 120 km wide. This research analyzes the performance of LAPAN-A3 satellite data to classify land cover in Toba Lake area, North Sumatera. Data processing starts from the selection of region of interest up to the assessment of accuracy. Supervised classification with maximum likelihood approach and confusion matrix method was applied to classify and evaluate the assessment results. The land cover is classified into five classes; water, bare land, agriculture, forest and secondary forest. The result of accuracy test is 93.71%. It proves that LAPAN-A3 data could classify the land cover accurately. The data is expected to complement the need of the satellite data with medium spatial resolution. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13857 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 71-80 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13857/10775 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13858 2025-11-25T07:06:58Z ijreses:FP

Front Pages IJReSES Vol. 13, No. 2(2016) Editorial Journal Front Pages IJReSES Vol. 13, No. 2(2016)    *Note: This cover is a revision of the Peer Reviewers section of the cover that was uploaded on May 26, 2017 BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13858 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); I-XV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13858/10776 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13860 2025-11-25T07:06:58Z ijreses:ART

BATHYMETRY DATA EXTRACTION ANALYSIS USING LANDSAT 8 DATA Kuncoro Teguh Setiawan Syifa Wismayati Adawiah Yennie Marini Gathot Winarso bathymetry Landsat 8 reflectance Van Hengel and Spitzer algorithm The remote sensing technique can be used to produce bathymetric map. Bathymetric mapping is important for the coastal zone and watershed management. In the previous study conducted in Menjangan Island of Bali, bathymetric extractin information from the top of the atmosphere (TOA) reflectance image of Landsat ETM+  data has R2 = 0.620. Not optimal  correlation value produced is highly influenced by the reflectance image of Landsat ETM+ data, were used, hence the lack of the research which became the basis of the present study. The study was on the Karang Lebar water of Thousand Islands, Jakarta. And the aim was to determine whether there was an increased correlation coefficient value of bathymetry extraction information generated from Surface reflectance and TOA reflectance imager of Landsat 8 data acquired on August 12, 2014. The method of extraction was done using algorithms Van Hengel and Spitzer (1991). Extraction   absolute depth information obtained from the model logarithm of Landsat 8 surface reflectance images and pictures TOA produce a correlation value of R2 = 0.663 and R2 = 0.712. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13860 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 79-86 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13860/10778 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13861 2025-11-25T07:19:22Z ijreses:ART

DETECTING THE LAVA FLOW DEPOSITS FROM 2018 ANAK KRAKATAU ERUPTION USING DATA FUSION LANDSAT-8 OPTIC AND SENTINEL-1 SAR Suwarsono Indah Prasasti Jalu Tejo Nugroho Jansen Sitorus Djoko Triyono lava flow Anak Krakatau data fusion Landsat-8 Sentinel-1 SAR The increasing volcanic activity of Anak Krakatau volcano has raised concerns about a major disaster in the area around the Sunda Strait. The objective of the research is to fuse Landsat-8 OLI (Operational Land Imager) and Sentinel-1 TOPS (Terrain Observation with Progressive Scans), an integration of SAR and optic remote sensing data, in observing the lava flow deposits resulted from Anak Krakatau eruption during the middle 2018 eruption. RGBI and the Brovey transformation were conducted to merge (fuse) the optical and SAR data.  The results showed that optical and SAR data fusion sharpened the appearance of volcano morphology and lava flow deposits. The regions are often constrained by cloud cover and volcanic ash, which occurs at the time of the volcanic eruption.  The RGBI-VV and Brovey RGB-VV methods provide better display quality results in revealing the morphology of volcanic cone and lava deposits. The entire slopes of Anak Krakatau Volcano, with a radius of about 1 km from the crater is an area prone to incandescent lava and pyroclastic falls. The direction of the lava flow has the potential to spread in all directions. The fusion method of optical Landsat-8 and Sentinel-1 SAR data can be used continuously in monitoring the activity of Anak Krakatau volcano and other volcanoes in Indonesia both in cloudy and clear weather conditions. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13861 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 157-166 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13861/10779 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13862 2025-11-25T07:06:58Z ijreses:ART

UTILIZATION OF NEAR REAL-TIME NOAA-AVHRR SATELLITE OUTPUT FOR EL NIÑO INDUCED DROUGHT ANALYSIS IN INDONESIA (CASE STUDY: EL NIÑO 2015 INDUCED DROUGHT IN SOUTH SULAWESI) Amsari Mudzakir Setiawan Yonny Koesmaryono Akhmad Faqih Dodo Gunawan drought near real-time monitoring NOAA-AVHRR VHI VCI TCI El Niño Drought is becoming one of the most important issues for government and policy makers. National food security highly concerned, especially when drought occurred in food production center areas. Climate variability, especially in South Sulawesi as one of the primary national rice production centers is influenced by global climate phenomena such as El Niño Southern Oscillation or ENSO. This phenomenon can lead to drought occurrences. Monitoring of drought potential occurrences in near real-time manner becomes a primary key element to anticipate the drought impact. This study was conducted to determine potential occurrences and the evolution of drought that occurred as a result of the 2015 El Niño event using the Vegetation Health Index (VHI) from the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) satellite products. Composites analysis was performed using weekly Smoothed and Normalized Difference Vegetation Index (or smoothed NDVI) (SMN), Smoothed Brightness Temperature Index (SMT), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), and  Vegetation Health Index (VHI).  This data were obtained from The Center for Satellite Applications and Research (STAR) - Global Vegetation Health Products (NOAA) website during 35-year period (1981-2015). Lowest potential drought occurrences (highest VHI and VCI value) caused by 2015 El Niño is showed by composite analysis result. Strong El Niño induced drought over the study area indicated by decreasing VHI value started at week 21st. Spatial characteristic differences in drought occurrences observed, especially on the west coast and east coast of South Sulawesi during strong El Niño. Weekly evolution of potential drought due to the El Niño impact in 2015 indicated by lower VHI values (VHI < 40) concentrated on the east coast of South Sulawesi, and then spread to another region along with the El Nino stage.    BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13862 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 87-94 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13862/10781 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13863 2025-11-25T07:19:22Z ijreses:ART

GEOMETRIC ASPECTS EVALUATION OF GNSS CONTROL NETWORK FOR DEFORMATION MONITORING IN THE JATIGEDE DAM REGION Made Ditha Ary Sanjaya T. Aris Sunantyo Nurrohmat Widjajanti Jatigede dam control network IGS GNSS Many factors led to dam construction failure so that deformation monitoring activities is needed in the area of the dam. Deformation monitoring is performed in order to detect a displacement at the control points of the dam. Jatigede Dam deformation monitoring system has been installed and started to operate, but there has been no evaluation of the geometry quality of control networks treated with IGS points for GNSS networks processing. Therefore, this study aims to evaluate the geometric quality of GNSS control networks on deformation monitoring of Jatigede Dam area. This research data includes the GNSS measurements of five CORS Jatigede Dam stations (R01, GG01, GCP04, GCP06, and GCP08) at doy 233 with network configuration scenarios of 12 IGS points on two quadrants (jat1), three quadrants (jat2), and four quadrants (jat3 and jat4). GNSS networks processing was done by GAMIT to obtain baseline vectors, followed by network processing usingparameter method of least squares adjustment. Networks processing with least squares adjustment aims to determine the most optimal  by precision and reliability criterion. Results of this study indicate that network configuration with 12 IGS stations in the two quadrants provides the most accurate coordinates of CORS dam stations. Standard deviations value of CORS station given by jat1 configuration are in the range of 2.7 up to 4.1 cm in X-Z components, whereas standard deviations in the Y component are in the range 5.8 up to 6.9 cm. An optimization assessment based on network strength, precision, and reliability factors shows optimum configuration by jat1. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13863 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 167-176 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13863/10780 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13864 2025-11-25T07:19:22Z ijreses:ART

PRELIMINARY STUDY OF HORIZONTAL AND VERTICAL WIND PROFILE OF QUASI-LINEAR CONVECTIVE UTILIZING WEATHER RADAR OVER WESTERN JAVA REGION, INDONESIA Abdullah Ali Riris Adriyanto Miming Saepudin horizontal and vertical wind profile QLCS doppler weather radar Western Java Region Indonesia One of the weather phenomena that potentially cause extreme weather conditions is the linear-shaped mesoscale convective systems, including squall lines. The phenomenon that can be categorized as a squall line is a convective cloud pair with the linear pattern of more than 100 km length and 6 hours lifetime. The new theory explained that the cloud system with the same morphology as squall line without longevity threshold. Such a cloud system is so-called Quasi-Linear Convective System (QLCS), which strongly influenced by the ambient dynamic processes, include horizontal and vertical wind profiles. This research is intended as a preliminary study for horizontal and vertical wind profiles of QLCS developed over the Western Java region utilizing Doppler weather radar. The following parameters were analyzed in this research, include direction pattern and spatial-temporal significance of wind speed, divergence profile, vertical wind shear (VWS) direction, and intensity profiles, and vertical velocity profile. The subjective and objective analysis was applied to explain the characteristics and effects of those parameters to the orientation of propagation, relative direction, and speed of the cloud system’s movement, and the lifetime of the system. Analysis results showed that the movement of the system was affected by wind direction and velocity patterns. The divergence profile combined with the vertical velocity profile represents the inflow which can supply water vapor for QLCS convective cloud cluster. Vertical wind shear that effect QLCS system is only its direction relative to the QLCS propagation, while the intensity didn’t have a significant effect. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13864 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 177-186 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13864/10782 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13865 2025-11-25T07:06:57Z ijreses:ART

COMPARATIVE TEST OF SEVERAL RAINFALL ESTIMATION METHODS USING HIMAWARI-8 DATA Nanda Alfuadi Agie Wandala estimation rainfall satellite Palangka Raya Muarateweh Indonesian society needs information on potential hydrometeorological disasters, therefore the development of rainfall estimation methods becomes an important research activities to support disaster risk reduction. Central Kalimantan were selected as research location for comparative test of rainfall estimation methods based on Himawari-8 IR1 (11μm) data, because it has area with cloud cover fairly intensive throughout the year. Some rainfall estimation methods tested in this research are AE, CST, CSTM, IMSRA. Non Linear Relation, and Non Linear Inversion. Each of these methods tends to have a weakness in the value of accuracy, so this research aims to determine the most accurate method to be applied in Palangkaraya (27 meters above sea level) city and Muratewe (60 meters above sea level) district in Central Kalimantan. The experiment was conducted during the period of highest rainfall in January and February 2016 by converting the temperature data cloud tops (IR1) into a precipitation with AE, CST, CSTM, IMSRA, Non Linear Relation and Non Linear Inversion method. Based on the results of quantitative analysis, it was known that IMSRA was the best method which can be applied in rainfall estimation in Muarateweh’s and Palangka Raya’s winter period. The Accuracy of all estimation methods decreased when it was applied in Palangka Raya at afternoon and in Muarateweh at night until early morning. The estimation method with the lowest score was the AE with an average MSE value > 90 and the best estimation method was IMSRA with MSE value <12. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13865 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 95-104 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13865/10784 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13867 2025-11-25T07:19:21Z ijreses:ART

PRELIMINARY DETECTION OF GEOTHERMAL MANIFESTATION POTENTIAL USING MICROWAVE SATELLITE REMOTE SENSING Atriyon Julzarika Udhi Catur Nugroho The Northern of Inverse Arc of Sulawesi geothermal manifestation remote sensing gravity model The satellite technology has developed significantly. The sensors of remote sensing satellites are in the form of optical, Microwave, and LIDAR. These sensors can be used for energy and mineral resources applications. The example of those applications are height model and the potential of geothermal manifestation detection. This study aims to detect the potential of geothermal manifestation using remote sensing. The study area is the Northern of the Inverse Arc of Sulawesi. The method used is remote sensing approach for its preliminary detection with 4 steps as follow (a) mining land identification, (b) geological parameter extraction, (c) preparation of standardized spatial data, and (d) geothermal manifestation. Mining lands identification is using Vegetation Index Differencing method. Geological parameters include structural geology, height model, and gravity model. The integration method is used for height model. The height model integration use ALOS PALSAR data, Icesat/GLAS, SRTM, and X SAR. Structural geology use dip and strike method. Gravity model use physical geodesy approach. Preparation of standardized spatial data with re-classed and analyzed using Geographic Information System between each geological parameter, whereas physical geodesy methods are used for geothermal manifestation detection. Geothermal manifestation using physical geodesy approach in Barthelmes method. Grace and GOCE data are used for gravity model. The geothermal manifestation detected from any parameter is analyzed by using geographic information system method. The result of this study is 10 area of geothermal manifestation potential. The accuracy test of this research is 87.5 % in 1.96 σ. This research can be done efficiently and cost-effectively in the process. The results can be used for various geological and mining applications. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13867 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 187-198 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13867/10783 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13869 2025-11-25T07:19:21Z ijreses:ART

THE UTILIZATION OF REMOTE SENSING DATA TO SUPPORT GREEN OPEN SPACE MAPPING IN JAKARTA, INDONESIA Hana Listi Fitriana Sayidah Sulma Nur Febrianti Jalu Tejo Nugroho Nanik Suryo Haryani green open space NDVI Remote sensing Green open space becomes critical in maintaining the balance of the environment and improving the quality of urban living for a healthy life. The use of remote sensing data for calculation of green open space has been done notably using NDVI (Normalized Difference Vegetation Index) method from Landsat 8 and SPOT data. This research aims to calculate the accuracy of the green open space classification from multispectral data of Landsat 8 and SPOT 6 using the NDVI methods. Green open space could be assessed from the value NDVI. The value of NDVI generated from Landsat 8 and SPOT 6’s Red and NIR channels. The accuracy of NDVI values is then examined by comparing with Pleiades data. Pleiades data which has 50 cm panchromatic resolution and 2 m multispectral with 4 bands (B, G, R, NIR) can precisely visualize objects. So, it can be used as the reference in the calculation of the green open space based on NDVI. The results of the accuracy testing of Landsat 8 and SPOT 6 image could be used to identify the green open space by using NDVI SPOT of 6 can increase the accuracy of 5.36% from Landsat 8. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13869 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); 199-208 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13869/10785 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13870 2025-11-25T07:06:57Z ijreses:ART

COMPARING ATMOSPHERIC CORRECTION METHODS FOR LANDSAT OLI DATA Esthi Kurnia Dewi Bambang Trisakti Landsat atmospheric correction QUAC FLAASH DOS surface reflectance Landsat data used for monitoring activities to land cover because it has spatial resolution and high temporal. To monitor land cover changes in an area, atmospheric correction is needed to be performed in order to obtain data with precise digital value picturing current condition. This study compared atmospheric correction methods namely Quick Atmospheric Correction (QUAC), Dark Object Subtraction (DOS) and Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH). The correction results then were compared to Surface Reflectance (SR) imagery data obtained from the United States Geological Survey (USGS) satelite. The three atmospheric correction methods were applied to Landsat OLI data path/row126/62 for 3 particular dates. Then, sample on vegetation, soil and bodies of water (waterbody) were retrieved from the image. Atmospheric correction results were visually observed and compared with SR sample on the absolute value, object spectral patterns, as well as location and time consistency. Visual observation indicates that there was a contrast change on images that had been corrected by using FLAASH method compared to SR, which mean that the atmospheric correction method was quite effective. Analysis on the object spectral pattern, soil, vegetation and waterbody of images corrected by using FLAASH method showed that it was not good enough eventhough the reflectant value differed greatly to SR image. This might be caused by certain variables of aerosol and atmospheric models used in Indonesia. QUAC and DOS made more appropriate spectral pattern of vegetation and water body than spectral library. In terms of average value and deviation difference, spectral patterns of soil corrected by using DOS was more compatible than QUAC. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13870 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 105-120 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13870/10786 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13871 2025-11-25T07:19:21Z ijreses:BP

Back Pages IJReSES Vol. 15, No. 2 (2018) Editor Journal Back Pages IJReSES Vol. 15, No. 2 (2018) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13871 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 2 (2018); I-VI 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13871/10787 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13874 2025-11-25T07:06:57Z ijreses:ART

TECHNIQUE FOR IDENTIFYING BURNED VEGETATION AREA USING LANDSAT 8 DATA Bambang Trisakti Udhi Catur Nugroho Any Zubaidah burned area Landsat 8 bare area hotspot distribution During the last two decades, forest and land fire is a catastrophic event that happens almost every year in Indonesia.  Therefore, it is necessary to develop a technic to monitor forest fires using satellite data to obtain the latest information of burned area in a large scale area. The objective of this research is to develop a method for burned area mapping that happened between two Landsat 8 data recording on August 13rd and September 14th 2015. Burned area was defined as a burned area of vegetation. The hotspot distribution during the period August - September 2015 was used to help visual identification of burned area on the Landsat image and to verify the burned area resulted from this research. Samples were taken at several land covers to determine the spectral pattern differences among burned area, bare area and other land covers, and then the analysis was performed to determine the suitable spectral bands or indices and threshold values that will be used in the model. Landsat recorded on August 13rd before the fire was extracted for soil, while Landsat recorded on September 14th after the fire was extracted for burned area. Multi-temporal analysis was done to get the burned area occurring during the certain period. The results showed that the clouds could be separated using combination of ocean blue and cirrus bands, the burned area was extracted using a combination of NIR and SWIR band, while soil was extracted using ratio SWIR / NIR. Burned area obtained in this study had high correlation with the hotspot density of MODIS with the accuracy was around 82,4 %. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13874 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 121-130 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13874/10788 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13875 2025-11-25T07:06:57Z ijreses:ART

TECHNIQUE TO RECONSTRUCT BAND 6 REFLECTANCE INFORMATION OF AQUA MODIS Andy Indradjad Noriandini Dewi Salyasari Rahmat Arief data reconstruction MODIS band 6 Aqua Remote sensing data could experience damage due to sensor failure or atmospheric condition. Reconstruction technique to retrieve the missing information had been widely developed in the past few years. This writing aimed to provide a technique to recover reflectance information of Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Band 6. Since Band 6 Aqua MODIS experienced sensor failure, lots of information would be missing. There were three kinds of methods used in repairing such damage. Two of which were categorized as spatial-based methods, i.e. NaN interpolation method and tensor completion method. Whereas, another method was a spectral-based one. NaN was an interpolation method to reconstruct missing value; while tensor completion method utilized low rank approximation, and spectral method used correlation between Band 6 and Band 7 which had near wavelength. Implementation of these methods was resulted in reconstruction of Aqua Modis Band 6 data which was damaged due to detector disfunction on Aqua Satellite. Peak Signal to Noise Ratio (PSNR) value of this method was 41 dB, meaning that reconstruction technique provided positive impacts for data improvement. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13875 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 131-138 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13875/10789 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13876 2025-11-25T07:06:57Z ijreses:ART

IDENTIFICATION AND CLASSIFICATION OF FOREST TYPES USING DATA LANDSAT 8 IN KARO, DAIRI, AND SAMOSIR DISTRICTS, NORTH SUMATRA Heru Noviar Tatik Kartika identification classification forest types Landsat 8 Forests have important roles in terms of carbon storage and other values. Various studies have been conducted to identify and distinguish the forest from non-forest classes. Several forest types classes such as secondary forests and plantations should be distinguished related to the restoration and rehabilitation program for dealing with climate change. The study was carried out to distinguish several classes of important forests such as the primary dryland forests, secondary dryland forest, and plantation forests using Landsat 8 to develop identification techniques of specific forests classes. The study areas selected were forest areas in three districts, namely Karo, Dairi, and Samosir of North Sumatera Province. The results showed that using composite RGB 654 of Landsat 8 imagery based on test results OIF for the forest classification, the forests could be distinguished with other land covers. Digital classification can be combined with the visual classification known as a hybrid classification method, especially if there are difficulties in border demarcation between the two types of forest classes or two classes of land covers. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13876 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 139-150 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13876/10790 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13877 2025-11-25T07:06:57Z ijreses:ART

HAZE REMOVAL IN THE VISIBLE BANDS OF LANDSAT 8 OLI OVER SHALLOW WATER AREA Kustiyo Kamilah Hayati haze removal shallow water Landsat 8 Haze is one of radiometric quality parameters in remote sensing imagery. With certain atmospheric correction, haze is possible to be removed. Nevertheless, an efficient method for haze removal is still a challenge. Many methods have been developed to remove or to minimize the haze disruption. While most of the developed methods deal with removing haze over land areas, this paper tried to focus to remove haze from shallow water areas. The method presented in this paper is a simple subtraction algorithm between a band that reflected by water and a band that absorbed by water. This paper used data from Landsat 8 with visible bands as a band that reflected by water while the band that absorbed by water represented by NIR, SWIR-1, and SWIR-2 bands. To validate the method, a reference data which relatively clear of cloud and haze contamination is selected. The pixel numbers from certain points are selected and collected from data scene, results scene and reference scene. Those pixel numbers, then being compared each other to get a correlation number between data scene to reference scene and between result scene and reference scene. The comparison shows that the method using NIR, SWIR-1, and SWIR-2 all significantly improved correlations numbers between result scene with reference scene to higher than 0.9. The comparison also indicates that haze removal result using NIR band had the highest correlation with reference data. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13877 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); 151-157 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13877/10791 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13878 2025-11-25T07:06:57Z ijreses:BP

Back Pages IJReSES Vol. 13, No. 2(2016) Editorial Journal Back Pages IJReSES Vol. 13, No. 2(2016) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13878 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 2 (2016); I-IX 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13878/10792 Copyright (c) 2016 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13879 2025-11-25T07:14:32Z ijreses:ART

COMPARISON OF MODEL ACCURACY IN TREE CANOPY DENSITY ESTIMATION USING SINGLE BAND, VEGETATION INDICES AND FOREST CANOPY DENSITY (FCD) BASED ON LANDSAT-8 IMAGERY (CASE STUDY: PEAT SWAMP FOREST IN RIAU PROVINCE) Faisal Ashaari Muhammad Kamal Dede Dirgahayu Tree canopy density single band vegetation indices FCD Identification of a tree canopy density information may use remote sensing data such as Landsat-8 imagery. Remote sensing technology such as digital image processing methods could be used to estimate the tree canopy density. The purpose of this research was to compare the results of accuracy of each method for estimating the tree canopy density and determine the best method for mapping the tree canopy density at the site of research. The methods used in the estimation of the tree canopy density are Single band (green, red, and near-infrared band), vegetation indices (NDVI, SAVI, and MSARVI), and Forest Canopy Density (FCD) model. The test results showed that the accuracy of each method: green 73.66%, red 75.63%, near-infrared 75.26%, NDVI 79.42%, SAVI 82.01%, MSARVI 82.65%, and FCD model 81.27%. Comparison of the accuracy results from the seventh methods indicated that MSARVI is the best method to estimate tree canopy density based on Landsat-8 at the site of research. Estimation tree canopy density with MSARVI method showed that the canopy density at the site of research predominantly 60-70% which spread evenly. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13879 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 81-92 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13879/10793 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13880 2025-11-25T07:14:32Z ijreses:ART

ANALYSIS OF LAND USE SPATIAL PATTERN CHANGE OF TOWN DEVELOPMENT USING REMOTE SENSING Samsul Arifin Mukhoriyah Dipo Yudhatama Analysis Spatial Remote Sensing Pattern Development The Assessment of the physical character of a city is considered relatively easier than the social-cultural aspects. It is important to recognize the type of city form and to predict the behavior of people in the city and its surrounding. Due to those characteristics, the study of the pattern of physical development of the city is required. The objective of research is to analyze the change of spatial pattern of the city due to the city growing by remote sensing. The multitemporal data of Landsat 5/7/8 year 2000, 2006 and 2015 in Jabodetabek area were used. The classification technique had been done and it produced five classes of land uses. Those are water, built-up area, vegetation, other land use and no data. The results of the analysis in Jabodetabek area (Jakarta, Bogor, Depok, Tangerang and Bekasi) show that there was land use changes from vegetation and other land use area to built-up area with an average accuracy of 78% in each year. The pattern of physical development of the city looks linear from year 2000 until year 2006, which is confirmed as concentric pattern from year 2006 to 2015. Based on those analysis, it confirmed that the city development in Jakarta as the center was influenced by the spatial land development of the surrounding cities of Depok, Bogor, Bekasi and Tangerang. The pattern of spatial development from 2000 to 2006 in Bogor, Bekasi and Depok areas is Linear pattern, whereas from 2006 - 2015 the pattern of spatial development shows Propagation Concentric pattern. For Tangerang Region in 2000-2015 its development is patterned Propagation Concentric. BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13880 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); 93-102 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13880/10794 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13881 2025-11-25T07:14:32Z ijreses:BP

Back Pages IJReSES Vol. 15, No. 1(2018) Journal Editor Back Pages IJReSES Vol. 15, No. 1(2018) BRIN 2025-11-25 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13881 International Journal of Remote Sensing and Earth Sciences; Vol. 15 No. 1 (2018); I-III 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13881/10795 Copyright (c) 2018 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13882 2025-11-26T01:17:07Z ijreses:FP

Front Pages IJReSES Vol. 13, No. 1(2016) Editorial Journal Front Pages IJReSES Vol. 13, No. 1(2016)     *Note: This cover is a revision version of the Editorial Committee Preface section cover that was uploaded on May 26, 2017 BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13882 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); II-III 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13882/10796 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13883 2025-11-26T01:17:07Z ijreses:ART

DETECTION OF GREEN OPEN SPACE USING COMBINATION INDEX OF LANDSAT 8 DATA (CASE STUDY: DKI JAKARTA) Sayidah Sulma Jalu Tejo Nugroho Any Zubaidah Hana Listi Fitriana Nanik Suryo Haryani green open space NDVI NDWI NDBI NDBaI Landsat 8 Spatial information about the availability and presence of green open space in urban areas to be up to date and transparent was a necessity. This study explained the technique to get the green open spaces of spatial information quickly using an index approach of Landsat 8. The purpose of this study was to evaluate the ability of the method to detect the green open spaces, especially using Landsat 8 with a combination of several indices, namely Normalized Difference Build-up Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Build-up Index (NDBI) and Normalized Difference Bareness Index (NDBaI) with a study area of Jakarta. This study found that the detection and identification of green open space classes used a combination of index and band gave good results with an accuracy of 81%. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13883 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 1-8 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13883/10797 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13884 2025-11-26T01:17:07Z ijreses:ART

ANALYSIS OF SCENE COMPATIBILITIES FOR MOSAIC OF LANDSAT 8 MULTI-TEMPORAL IMAGES BASED ON RADIOMETRIC PARAMETER Haris Suka Dyatmika Liana Fibriawati Landsat 8 mosaic histogram Scattergram Cloud free mosaic simplified the remote sensing imagery. Multi-temporal image mosaic needed to make a cloud free mosaic i.e. in the area covered by cloud throughout year like Indonesia. One of the satellite imagery that was widely used for various purposes was Landsat 8 image due to the temporal, spatial and spectral resolution which was suitable for many utilization themes. Landsat 8 could be used for multi-temporal image mosaic of the entire region in Indonesia. Landsat 8 had 16 days temporal resolution which allowed a region (scene image) acquired in a several times one year. However, not all the acquired Landsat 8 scene was proper when used for multi-temporal mosaic. The purpose of this work was observing radiometric parameters for scene selection method so a good multi-temporal mosaic image could be generated and more efficient processing. This study analyzed the relationship between radiometric parameters from image i.e. histogram and Scattergram with scene selection for multi-temporal mosaic purposes. Histogram and Scattergram representing radiometric imagery context such as mean, standard deviation, median and mode which was displayed visually. The data used were Landsat 8 imagery with the Area of Interest (AOI) in Kalimantan and Lombok. Then the histogram and Scattergram of the image AOI was analyzed. From the histogram and Scattergram analysis could be obtained that less shift between the data’s histogram and the more Scattergram forming 45 degree angle for distribution of the data then indicated more similar to radiometric of the image. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13884 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 9-18 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13884/10798 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13885 2025-11-26T01:17:07Z ijreses:ART

DETERMINATION OF FOREST AND NON-FOREST IN SERAM ISLAND MALUKU PROVINCE USING MULTI-YEAR LANDSAT DATA Tatik Kartika Ita Carolita Johannes Manalu Landsat data missing data index equation forest probability Seram Island is one of the islands in Maluku Province. Forest in Seram Island still exists because there is Manusela National Park, but they should be monitored. The forest and non-forest information is usually obtained through the classification process from single remote sensing data, but in certain places in Indonesia it is difficult enough to get  single Landsat data with cloud free, so annual mosaic was used. The aim of this research was to analyze the stratification zone, their indices and thresholds to get spatial information of annual forest area in Seram Island using multi-year Landsat Data. The method consists of four stages: 1) analyzing the base probability result for determination of stratification zone 2) determining the annual forest probability by applying indices from stage-I, 3) determining the spatial information of forest and non-forest annual phase-I by searching the lowest boundary of forest probability, and 4) determining the spatial information of forest and non-forest annual phase-II using the method of permutation of three data and multi-year forest rules. The results of this study indicated that Seram Island  could be coumpond into one stratification zone with three indices. The index equations were B2+B3-2B for index-1, B3+B4 for index-2, and -B3+B4 for index-3.   The threshold  of  index 1, 2, and 3 ranged between -60 and 0, 61 and 104, and 45 and 105, respectively. The lowest boundary  of forest probability in Seram Island since 2006 to 2012 have a range between 46% and 60%. The last result was the annual forest spatial information phase II where the missing data on the forest spatial information phase I decreased. The information is very important to analyze forest area change, especially in Seram Island.  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13885 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 19-26 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13885/10799 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13886 2025-11-26T01:17:07Z ijreses:ART

DEVELOPMENT OF PUSHBROOM AIRBORNE CAMERA SYSTEM USING MULTISPECTRUM LINE SCAN INDUSTRIAL CAMERA Ahmad Maryanto Nugroho Widijatmiko Wismu Sunarmodo Muhammad Soleh Rahmat Arief airborne camera industry camera multispectrum pushbroom One of the steps on mastery the remote sensing technology (inderaja) for satellite was the development of aerial camera prototype that could be an alternative for LAPAN light cargo aircraft mission (LAPAN Surveillance Aircraft, LSA-01). This system was expected could be operated to fulfill the emptiness or change the remote sensing data of optical satellite as the observer of vegetation covered by cloud. On this research, it was developed a prototype of pushbroom airborne camera 4-channels spectrum with very high resolution that worked on wavelength range seem near infra-red/ NIR used simple components that were available in the commercial market (commercial off-the-shelf/ COTS components). This research also developed georeference imagery software module used method of direct georeference rigorous model that had been applied on SPOT satellite. For this one, it was installed supported sensory for GPS and IMU as the writer of location coordinate and camera behavior while doing the imagery exposure or acquisition. The testing result gave confirmation that COTS components, such as industry camera LQ-200CL, and lower class GPS and IMU could be integrated became a cheaper remote sensing system, which its imagery product could be corrected systematically. The corrected data product showed images with GSD 0.4m still had positioning mistakes on average 157m (400 pixel) from the original position on GoogleEarth. On spectro-radiomatic aspect, the used camera had much higher sensitivity of NIR channel than the looked-channel so it caused bored faster. On the future, this system needed to be fixed by increasing the rate of GPS/ IMU data updates, and increased enough time resolution system so that the synchronization process and the availability supported data for completing more accurate georeference process. Besides, the sensitivity of NIR channel needed to be lower down to make it balance to the looked-channel. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13886 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 27-38 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13886/10800 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13887 2025-11-26T01:17:06Z ijreses:ART

SPATIAL PATTERN OF HYDROLOGIC RESPONSE UNIT (HRU) EFFECT ON FLOW DISCHARGE OF CI RASEA WATERSHED USING LANDSAT TM IN 1997 TO 2009 Emiyati Eko Kusratmoko Sobirin Ci Rasea watershed HRU surface runoff SWAT model landcover Hydrologic Response Unit (HRU) is a unit formed of hydrological analysis based on geology and soil type, slope, and land cover. This paper discussed the spatial pattern of Hydrologic Response Unit (HRU) in 1997-2009 and its impact on flow Ci Rasea watershed temporally. In this study, SWAT (Soil and Water Assessment Tool) model, based on land cover changed, was used to get HRU and flow in spatially and temporally. This method used Landsat TM 1997, 2003 and 2009 data for land cover and daily rainfall 1997-2009 for flow modeling. The results showed the spatial pattern of HRU in temporally was affected by landcover based on the changing of HRU. The majority of HRU spatial pattern at Ci Rasea watershed were clustered. During 1997-2009, accumulated surface runoff and the changing of flow discharge were affected by changes of HRU spatial pattern. The biggest accumulated surface runoff in Ci Rasea watershed influenced by HRU of agricultural cropland in area of clay soil type with slope slightly obliquely. While the smallest accumulated surface runoff in Ci Rasea watershed influenced by HRU of paddy field in the area of sandy loam soil type with a gentle slope. The changes of HRU agriculture cropland become HRU mixed cropland in area clay soil type with slope at a slight angle and HRU agriculture cropland become HRU paddy field in area, sandy loam soil type with a gentle slope could be decreasing the accumulation of surface runoff in Ci Rasea watershed. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13887 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 39-50 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13887/10801 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13888 2025-11-26T01:17:06Z ijreses:ART

DEVELOPMENT OF ANNUAL LANDSAT 8 COMPOSITE OVER CENTRAL KALIMANTAN, INDONESIA USING AUTOMATIC ALGORITHM TO MINIMIZE CLOUD Kustiyo Landsat 8 composite cloud-free Since January 2013, Landsat 8 data can be freely accessed from LAPAN, making it possible to use the all available Landsat 8 data to  produce the cloud-free Landsat 8 composite images. This study used Landsat 8 archive images in 2015,  Operational Land Imager (OLI) sensor in 30 meter resolution, geometric correction level of L1T. The eight data in L1T of 118-062, southern part of Central Kalimantanwere used to produce a cloud-free composite image. Radiometric correction using Top of Atmosphere (TOA) and Bidirectional Reflectance Distribution Function (BRDF) algorithm to produce reflectance images have been applied, and then the most cloud-free pixels were selected in composite result. Six composite methods base on greens, open area and haze indices were compared, and the best one was selected  using visual analysis. The analysis shows that the composite algorithm using Max (Max (NIR, SWIR1)/Green) produces the best image composite. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13888 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 51-58 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13888/10802 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13889 2025-11-26T01:17:06Z ijreses:ART

VARIATION AND TREND OF SEA LEVEL DERIVED FROM ALTIMETRY SATELLITE AND TIDE GAUGE IN CILACAP AND BENOA COASTAL AREAS Amelius Andi Mansawan Jonson Lumban-Gaol James P. Panjaitan altimetry sea level rise tide satellite Observation of sea levels continuously is very important in order to adapt the disasters in the coastal areas. Conventionally observations of sea level using tide gauge, but the number of tide gauge installed along the coast of Indonesia is still limited. Altimetry satellite data is one solution; therefore it is necessary to assess the potential and accuracy of altimetry satellite data to complement the sea level data from tide gauges. The study was conducted in the coastal waters of Cilacap and Bali by analysis data Envisat satellite altimetry for period 2003 to 2010 and data compiled from a variety of satellite altimetry from 2006 to 2014. Data tidal was used as a comparison of altimetry satellite data. The altimetry satellite data in Cilacap and Benoa waters more than 90% could be used to assess the variation and the sea level rise during the period 2003-2010. The rate of sea level rise both the data of tidal and satellite altimetry data indicates the same rate was 3.5 mm/year in Cilacap. in Benoa are 4.7 mm/year and 5.60 mm/year respectively. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13889 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 59-66 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13889/10803 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13890 2025-11-26T01:17:06Z ijreses:ART

LINEAMENT DENSITY INFORMATION EXTRACTION USING DEM SRTM DATA TO PREDICT THE MINERAL POTENTIAL ZONES Udhi C. Nugroho Arum Tjahjaningsih geology remote sensing lineament density mineral DEM Utilization of remote sensing in geology is based on some identification of main parameters. They were the relief or morphology, flow patterns, and lineament. So it was necessary to study extraction method based on those parameters. This study aimed to obtain lineament density zone in the Geumpang area, Aceh, associated with mineral resource potential. Information of lineament density using remote sensing data was expected to help solve the problems that arised in the activities of early exploration, the difficulty of finding the prospect areas, so that the activities of pre-exploration always required a wide area and required a long time to determine the location of mineral prospect areas, it would have a direct impact on the financial of exploration activities. The used data was Landsat 8 and DEM SRTM of 30 m. The used method was processing of shaded relief on DEM data with the azimuth angle 0o, 45o, 90o, and 135o, then the result of hill shade process was done overlay, so DEM seen from all different azimuth angles. The results of the overlay were processed using the algorithm LINE with parameters such as the radius of the filter in pixels (RADI) 60, the threshold for edge gradient (GTHR) 120, the threshold for the curve length (LTHR) 100, the threshold for line fitting error (FTHR) 3, threshold for angular (ATHR) 30, and the threshold for linking distance (DTHR) 100. Vector lineament data from LINE algorithm process then performed density analysis to obtain lineament density zoning. Results from the study showed that the area has a high density lineament associated with mineral potency, so it was useful for exploration activities to minimize the survey area. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13890 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 67-74 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13890/10804 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13891 2025-11-26T01:17:06Z ijreses:BP

Back Pages IJReSES Vol. 13, No. 1(2016) Editorial Journal Back Pages IJReSES Vol. 13, No. 1(2016) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13891 International Journal of Remote Sensing and Earth Sciences; Vol. 13 No. 1 (2016); 75-78 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13891/10805 Copyright (c) 2016 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13892 2025-11-26T02:42:59Z ijreses:FP

Front Pages IJReSES Vol. 14, No. 2(2017) Journal Editor Front Pages IJReSES Vol. 14, No. 2(2017) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13892 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); I-XIII 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13892/10806 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13893 2025-11-26T02:42:59Z ijreses:ART

CAN THE PEAT THICKNESS CLASSES BE ESTIMATED FROM LAND COVER TYPE APPROACH? Bambang Trisakti Atriyon Julzarika Udhi C. Nugroho Dipo Yudhatama Yudi Lasmana Peat thickness Landsat 8 image land cover Merauke Regency shallow peatlands Indonesia has been known as a home of the tropical peatlands. The peatlands are mainly in Sumatera, Kalimantan and Papua Islands. Spatial information on peatland depth is needed for the planning of agricultural land extensification. The research objective was to develop a preliminary estimation model of peat thickness classes based on land cover approach and analyse its applicability using Landsat 8 image. Ground data, including land cover, location and thickness of peat, were obtained from various surveys and peatlands potential map (Geology Map and Wetlands Peat Map). The land cover types were derived from Landsat 8 image. All data were used to build an initial model for estimating peat thickness classes in Merauke Regency. A table of relationships among land cover types, peat potential areas and peat thickness classes were made using ground survey data and peatlands potential maps of that were best suited to ground survey data. Furthermore, the table was used to determine peat thickness classes using land cover information produced from Landsat 8 image. The results showed that the estimated peat thickness classes in Merauke Regency consist of two classes, i.e., very shallow peatlands and shallow peatlands. Shallow peatlands were distributed at the upper part of Merauke Regency with mainly covered by forest. In comparison with Indonesia Peatlands Map, the number of classes was the two classes. The spatial distribution of shallow peatlands was relatively similar for its precision and accuracy, but the estimated area of shallow peatlands was greater than the area of shallow peatlands from Indonesia Peatlands Map. This research answered the question that peat thickness classes could be estimated by the land cover approach qualitatively. The precise estimation of peat thickness could not be done due to the limitation of insitu data.   BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13893 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 83-94 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13893/10808 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13894 2025-11-26T01:11:12Z ijreses:FP

Front Pages IJReSES Vol. 11, No. 1(2014) Editorial Secretariat Front Pages IJReSES Vol. 11, No. 1(2014) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13894 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); I-VII 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13894/10807 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13895 2025-11-26T01:11:12Z ijreses:ART

DIGITAL IMAGE PROCESSING OF SPOT-4 FOR SHORELINE EXTRACTION IN LAMPUNG BAY Emiyati Syarif Budhiman Ety Parwati Shoreline SPOT-4 image Ratio method NDVI Single band infrared Lampung Bay Shoreline is an imaginary line separating land and seawater. The intensification of land used/land cover at Lampung bay causes shoreline change either abrasions or accretions. The objectives of this study were to compare the shoreline extraction based on the digital image processing of SPOT-4 using ratio band of infrared and green band, Normalized Difference Vegetation Index (NDVI), and (band infrared) methods and to analyze shoreline change at Lampung Bay. Those methods applied on both cloudy free and cloudy SPOT-4 images and the result compared with RBI map as reference. The result showed that the best metod for shoreline axtraction was ratio band due to accuracy high and stable eventhough it applied on cloudy image. The shoreline changes at Lampung Bay along 2008 to 2012 caused by accretions. The total area of accretion at Lampung Bay for fours years were 662 Ha with the rates 165 Ha/year. The high of accretion rate caused by reclamation for urban built up, fishponds and mangrove. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13895 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 1-10 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13895/10812 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13896 2025-11-26T02:42:59Z ijreses:ART

SPATIAL PROJECTION OF LAND USE AND ITS CONNECTION WITH URBAN ECOLOGY SPATIAL PLANNING IN THE COASTAL CITY, CASE STUDY IN MAKASSAR CITY, INDONESIA Syahrial Nur Amri Luky Adrianto Dietriech Geoffrey Bengen Rahmat Kurnia spatial projection land use spatial planning remote sensing coastal city The arrangement of coastal ecological space in the coastal city area aims to ensure the sustainability of the system, the availability of local natural resources, environmental health and the presence of the coastal ecosystems. The lack of discipline in the supervision and implementation of spatial regulations resulted in inconsistencies between urban spatial planning and land use facts. This study aims to see the inconsistency between spatial planning of the city with the real conditions in the field so it can be used as an evaluation material to optimize the planning of the urban space in the future. This study used satellite image interpretation, spatial analysis, and projection analysis using markov cellular automata, as well as consistency evaluation for spatial planning policy. The results show that there has been a significant increase of open spaces during 2001-2015 and physical development was relatively spreading irregularly and indicated the urban sprawl phenomenon. There has been an open area deficits for the green open space in 2015-2031, such as integrated maritime, ports, and warehousing zones. Several islands in Makassar City are predicted to have their built-up areas decreased, especially in Lanjukang Island, Langkai Island, Kodingareng Lompo Island, Bone Tambung Island, Kodingareng Keke Island and Samalona Island. Meanwhile, the increase of the built up area is predicted to occur in Lumu Island, Barrang Caddi Island, Barrang Lompo Island, Lae-lae Island, and Kayangan Island. The land cover is caused by the human activities. Many land conversions do not comply with the provision of percentage of green open space allocation in the integrated strategic areas, established in the spatial plan. Thus, have the potential of conflict in the spatial plan of marine and small islands in Makassar City. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13896 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 95-110 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13896/10810 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13897 2025-11-26T01:24:40Z ijreses:FP

Front Pages IJReSES Vol. 12, No. 1(2015) Editorial Journal Front Pages IJReSES Vol. 12, No. 1(2015) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13897 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); I-III 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13897/10809 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13899 2025-11-26T01:24:40Z ijreses:ART

DEVELOPMENT OF DISSOLVED OXYGEN CONCENTRATION EXTRACTION MODEL USING LANDSAT DATA CASE STUDY: RINGGUNG COASTAL WATERS Muchlisin Arief detection dissolved oxygen correlation Landsat Ringgung Water is a key component to the process of earth’s life. However, with increasing industrial development and anthropogenic activities, water quality has been decreased dramatically. Therefore, monitoring is necessary to anticipate the threat of contamination and to take effective action at all levels in local or central government. Methods or algorithms were proposed for detecting or mapping or extraction the concentrations of dissolved oxygen (DO) derived from Landsat remote sensing imagery using empirical formulation. The aim of this study to monitor the quality of coastal waters over large areas. The method begins with the calculation of water surface temperature derived from Landsat data, using the correlation function obtained by correlating the temperature measurement by the infrared band reflectance values. Then the image is used to calculate the concentration of DO using the correlation function. the correlation function is obtained by correlating the results of field measurements of DO with temperature. The study conducted in the Ringgung coastal waters located in Padang Cermin District, Pesawaran municipal conducted on August 7 to 11, 2012. Based on the analysis, dissolved oxygen concentration of Ringgung coastal waters is inversely proportional to the amount of fresh water entering the coastal waters and directly proportional to the aeration process. As a result, in June the concentration of dissolved oxygen near the beach (on shore water) greater than in the offshore water. While in August, the concentration of dissolved oxygen near the coast (on shore water) is lower than in the offshore water. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13899 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 1-12 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13899/10813 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13900 2025-11-26T02:42:59Z ijreses:ART

THE EFFECT OF JPEG2000 COMPRESSION ON REMOTE SENSING DATA OF DIFFERENT SPATIAL RESOLUTIONS Anis Kamilah Hayati Haris Suka Dyatmika compression effect spatial resolution remote sensing JPEG2000 The huge size of remote sensing data implies the information technology infrastructure to store, manage, deliver and process the data itself. To compensate these disadvantages, compressing technique is a possible solution. JPEG2000 compression provide lossless and lossy compression with scalability for lossy compression. As the ratio of lossy compression getshigher, the size of the file reduced but the information loss increased. This paper tries to investigate the JPEG2000 compression effect on remote sensing data of different spatial resolution. Three set of data (Landsat 8, SPOT 6 and Pleiades) processed with five different level of JPEG2000 compression. Each set of data then cropped at a certain area and analyzed using unsupervised classification. To estimate the accuracy, this paper utilized the Mean Square Error (MSE) and the Kappa coefficient agreement. The study shows that compressed scenes using lossless compression have no difference with uncompressed scenes. Furthermore, compressed scenes using lossy compression with the compression ratioless than 1:10 have no significant difference with uncompressed data with Kappa coefficient higher than 0.8. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13900 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 111-118 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13900/10811 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13901 2025-11-26T02:42:59Z ijreses:ART

PRELIMINARY STUDY OF LSU-02 PHOTO DATA APPLICATION TO SUPPORT 3D MODELING OF TSUNAMI DISASTER EVACUATION MAP Linda Yunita Nurwita Mustika Sari Dony Kushardono Aerial remote sensing photo data of LSU-02 3D modelling tsunami The southern coast of Pacitan Regency is one of the vulnerable areas to the tsunami. Therefore, the map of the vulnerable and safe area from the tsunami disaster is required. Currently, there are many mapping technologies with UAVs used for spatial analysis. One of the UAV technologies which used in this research is LAPAN Surveillance UAV 02 (LSU-02). This study aims to map the evacuation plan area from LSU-02 aerial imagery. Tsunami evacuation area was identified by processing the aerial photo data into orthomosaic and Digital Elevation Model (DEM). The result shows that there are four points identified as the tsunami evacuation plan area. These points are located higher than the surrounding area and are easily accessible. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13901 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 119-126 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13901/10814 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13902 2025-11-26T01:11:12Z ijreses:ART

MODIS STANDARD (OC3) CHLOROPHYLL-A ALGORITHM EVALUATION IN INDONESIAN SEAS Gathot Winarso Yennie Marini MODIS Chlorophyll-a OC3 Algorithm Indonesian seas The MODIS-estimated chlorophyll-a information was widely used in some operational application in Indonesia. However, there is no information about the performance of MODIS chlorophyll-a in Indonesian seas and there is no data used in development of algorithm was taken in Indonesian seas. Even the algorithm was validated in other area, it is important to know the performance of the algorithm work in Indonesian seas. Performance of MODIS Standard (OC3) algorithm at Indonesian seas was analyzed in this paper. The in-situ chlorophyll-a concentration data was collected during MOMSEI (Monsoon Offset Monitoring and Its Social and Ecosystem Impact) 2012 Cruise 25th April – 12th   May 2012 and also from archived data of the Research and Development Center for Marine Coastal Resources, Agency of Marine and Fisheries Research and Development, Indonesian Ministry of  Marine Affairs and Fisheries. The in-situ data used in this research is located in Indian Ocean the west of Sumatera part and Pacific Ocean the north of Papua Province part. Satellite data which is used is Ocean Color MODIS Level-2 Product that downloaded from NASA and MODIS L-0 from LAPAN Ground Station. MODIS Level 0 from LAPAN then processed to Level-2  using latest SeaDAS Software. The match-up resulted the MNB(%) is -4.8% that means satellite-estimated was underestimate in 4.8 % and RMSE is 0.058. When the data was separated following to the data source, the correlation and trend line equation became better. From MOMSEI Cruise data, the MNB(%) was -18.8% and RMSE 0.05. From Pacific Ocean Data, MNB (%) was -27 % and RMSE 0.049. From SONNE Cruise 2005, MNB (%) was -27 % and RMSE 0.049. MODIS standard algorithm is work well in Indonesia case-1 seawaters, which contain chlorophyll-a only, and derived that influence to the electromagnetic wave. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13902 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 11-20 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13902/10816 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13903 2025-11-26T01:24:40Z ijreses:ART

THE EFFECT OF DIFFERENT ATMOSPHERIC CORRECTIONS ON BATHYMETRY EXTRACTION USING LANDSAT 8 SATELLITE IMAGERY Kuncoro Teguh Setiawan Yennie Marini Johannes Manalu Syarif Budhiman atmospheric correction bathymetry Landsat 8 imagery Remote sensing technology can be used to obtain information bathymetry. Bathymetric information plays an important role for fisheries, hydrographic and navigation safety. Bathymetric information derived from remote sensing data is highly dependent on the quality of satellite data use and processing. One of the processing to be done is the atmospheric correction process. The data used in this study is Landsat 8 image obtained on June 19, 2013. The purpose of this study was to determine the effect of different atmospheric correction on bathymetric information extraction from Landsat satellite image data 8. The atmospheric correction methods applied were the minimum radiant, Dark Pixels and ATCOR. Bathymetry extraction result of Landsat 8 uses a third method of atmospheric correction is difficult to distinguish which one is best. The calculation of the difference extraction results was determined from regression models and correlation coefficient value calculation error is generated BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13903 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 13-20 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13903/10815 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13904 2025-11-26T02:42:58Z ijreses:ART

DETERMINATION OF THE BEST METHODOLOGY FOR BATHYMETRY MAPPING USING SPOT 6 IMAGERY: A STUDY OF 12 EMPIRICAL ALGORITHMS Masita Dwi Mandini Manessa Muhammad Haidar Maryani Hastuti Diah Kirana Kresnawati bathymetry SPOT 6 empirical methodology multispectral image For the past four decades, many researchers have published a novel empirical methodology for bathymetry extraction using remote sensing data. However, a comparative analysis of each method has not yet been done. Which is important to determine the best method that gives a good accuracy prediction. This study focuses on empirical bathymetry extraction methodology for multispectral data with three visible band, specifically SPOT 6 Image. Twelve algorithms have been chosen intentionally, namely, 1) Ratio transform (RT); 2) Multiple linear regression (MLR); 3) Multiple nonlinear regression (RF); 4) Second-order polynomial of ratio transform (SPR); 5) Principle component (PC); 6) Multiple linear regression using relaxing uniformity assumption on water and atmosphere (KNW); 7) Semiparametric regression using depth-independent variables (SMP); 8) Semiparametric regression using spatial coordinates (STR); 9) Semiparametric regression using depth-independent variables and spatial coordinates (TNP), 10) bagging fitting ensemble (BAG); 11) least squares boosting fitting ensemble (LSB); and 12) support vector regression (SVR). This study assesses the performance of 12 empirical models for bathymetry calculations in two different areas: Gili Mantra Islands, West Nusa Tenggara and Menjangan Island, Bali. The estimated depth from each method was compared with echosounder data; RF, STR, and TNP results demonstrate higher accuracy ranges from 0.02 to 0.63 m more than other nine methods. The TNP algorithm, producing the most accurate results (Gili Mantra Island RMSE = 1.01 m and R2=0.82, Menjangan Island RMSE = 1.09 m and R2=0.45), proved to be the preferred algorithm for bathymetry mapping. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13904 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 127-136 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13904/10817 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13905 2025-11-26T01:11:12Z ijreses:ART

DETECTION OF ACID SLUDGE CONTAMINATED AREA BASED ON NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI) VALUE Nanik Suryo Haryani Sayidah Sulma Junita Monika Pasaribu Acid sludge Contamination Normalized Difference Vegetation Index (NDVI) The solid form of oil heavy metal waste is  known as acid sludge. The aim of this research is to exercise the correlation between acid sludge concentration in soil and NDVI value, and further studying the Normalized Difference Vegetation Index (NDVI) anomaly by multi-temporal Landsat satellite images. The implemented method is NDVI.  In this research, NDVI is analyzed using the  remote sensing data  on dry season and wet season.  Between 1997 to 2012, NDVI value in dry season  is around – 0.007 (July 2001) to 0.386 (May 1997), meanwhile in wet season  NDVI value is around – 0.005 (November 2006) to 0.381 (December 1995).  The high NDVI value shows the leaf health or  thickness, where the low NDVI indicates the vegetation stress and rareness which can be concluded as the evidence of contamination. The rehabilitation has been executed in the acid sludge contaminated location, where the high value of NDVI indicates the successfull land rehabilitation effort. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13905 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 21-32 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13905/10819 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13906 2025-11-26T01:24:40Z ijreses:ART

GROWTH PROFILE ANALYSIS OF OIL PALM BY USING SPOT 6 THE CASE OF NORTH SUMATRA Ita Carolita J. Sitorus Johannes Manalu Dhimas Wiratmoko growth profile SPOT 6 oil palm plantation age Oil Palm (Elaeis guineensis Jack.) is one of the world’s most important tropical tree crops. Its expansion has been reported to cause widespread environment impacts. SPOT 6 data is one of high resolution satellite data that can give information more detail about vegetation and the age of oil palm plantation. The objective of this study was to analyze the growth profile of oil palm and to estimate the productivity age of oil palm. The study area is PTP N 3 in Tebing Tinggi North Sumatera Indonesia.  The method that used is NDVI analysis and regression analysis for getting the model of oil palm growth profile. Data from the field were collected as the secondary data to build that model. The data that collected were age of oil palm and diameters of canopy for every age.   Results indicate that oil palm growth can be explained by variation of NDVI with formula y = -0.0004x2 + 0.0107x + 0.3912, where x is oil palm age and  Y is NDVI of SPOT, with R² = 0.657. This equation can be used to predict the age of oil palm for range 4 to 11 years with R2 around 0.89. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13906 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 21-26 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13906/10818 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13907 2025-11-26T01:11:11Z ijreses:ART

INTERPOLATION METHODS FOR SEA SURFACE HEIGHT MAPPING FROM ALTIMETRY SATELLITES IN INDONESIAN SEAS Rossi Hamzah Teguh Prayogo Spatial interpolation Kriging Inverse distance weighting Sea surface height Altimetry Altimetry satellite data, has a very low spatial resolution for using in determine fishing ground area. With very low spatial resolution is required interpolation method that can mapped Sea Surface Height (SSH) with a good result. SSH data from Global Near Real Time from AVISO, mapped in geographic projection and interpolated with Inverse Distance Weighting (IDW) and Ordinary Krigging method. This interpolation method are expected to know which the good method for mapped SSH data in resulting better information. The results of statistical calculation shows that RMSE value and standar deviations from kriging method is smaller than IDW method. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13907 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 33-40 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13907/10821 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13908 2025-11-26T01:24:39Z ijreses:ART

THE EFFECT OF ENVIRONMENTAL CONDITION CHANGES ON DISTRIBUTION OF URBAN HEAT ISLAND IN JAKARTA BASED ON REMOTE SENSING DATA Indah Prasasti Suwarsono Nurwita Mustika Sari urban heat island Landsat 7 land use/cover NDVI NDBI Jakarta Anthropogenic activities of urban growth and development in the area of Jakarta has caused increasingly uncomfortable climatic conditions and tended to be warmer and potentially cause the urban heat island (UHI). This phenomenon can be monitored by observing the air temperature measured by climatological station, but the scope is relatively limited. Therefore, the utilization of remote sensing data is very important in monitoring the UHI with wider coverage and effective. In addition, the remote sensing data can also be used to map the pattern of changes in environmental conditions (microclimate). This study aimed to analyze the effect of changes in environmental conditions (land use/cover, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Build-up Index (NDBI)) toward the spread of the urban heat island (UHI). In this case, the UHI was identified from pattern changes of Land Surface Temperature (LST) in Jakarta based on data from remote sensing. The data used was Landsat 7 in 2007 and Landsat 8 in 2013 for parameter extraction environmental conditions, namely: land use cover, NDVI, NDBI, and LST. The analysis showed that during the period 2007 to 2013, there has been a change in the condition of the land use/cover, impairment NDVI, and expansion NDBI that trigger an increase in LST and the formation of heat islands in Jakarta, especially in the area of business centers, main street and surrounding area, as well as in residential areas. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13908 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 27-40 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13908/10820 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13910 2025-11-26T02:42:58Z ijreses:ART

CARBON STOCK ESTIMATION OF MANGROVE VEGETATION USING REMOTE SENSING IN PERANCAK ESTUARY, JEMBRANA DISTRICT, BALI Amandangi Wahyuning Hastuti Komang Iwan Suniada Fikrul Islamy Perancak Estuary carbon stock estimation mangrove CO2 sequestration NDVI Mangrove vegetation is one of the forest ecosystems that offers a potential of substantial greenhouse gases (GHG) emission mitigation, due to its ability to sink the amount of CO2 in the atmosphere through the photosynthesis process. Mangroves have been providing multiple benefits either as the source of food, the habitat of wildlife, the coastline protectors as well as the CO2 absorber, higher than other forest types. To explore the role of mangrove vegetation in sequestering the carbon stock, the study on the use of remotely sensed data in estimating carbon stock was applied. This paper describes an examination of the use of remote sensing data particularly Landsat-data with the main objective to estimate carbon stock of mangrove vegetation in Perancak Estuary, Jembrana, Bali. The carbon stock was estimated by analyzing the relationship between NDVI, Above Ground Biomass (AGB) and Below Ground Biomass (BGB). The total carbon stock was obtained by multiplying the total biomass with the carbon organic value of 0.47. The study results show that the total accumulated biomass obtained from remote sensing data in Perancak Estuary in 2015 is about 47.20±25.03 ton ha-1 with total carbon stock of about 22.18±11.76 tonC ha-1and CO2 sequestration 81.41±43.18 tonC ha-1. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13910 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 137-150 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13910/10825 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13911 2025-11-26T01:24:39Z ijreses:ART

THE UTILIZATION OF LANDSAT 8 FOR MAPPING THE SURFACE WATERS TEMPERATURE OF GRUPUK BAY - WEST NUSA TENGGARA: WITH IMPLICATIONS FOR SEAWEEDS CULTIVATION Bidawi Hasyim Syarif Budiman Arlina Ratnasari Emiyati Anneke K. S. Manoppo surface water temperature Grupuk Bay Landsat 8 infrared thermal imaging Locating a suitable site is the key to success in cultivating seaweed, as it is becomes one of the coastal and marine prospects for improving the national economy. Numerous factors such as water movement, substratum, depth, salinity, light intensity, surface water temperature, influence the growth of this aquatic plant, and should be considered while choosing a farming area. One of key parameters on studying sea water conditions is surface temperature distribution, as changes on temperature effecting physical, chemical, and biological condition of the sea water. Surface waters temperature is affected by radiation, and sun position, geographic, seasons, overcast, interaction process between air and waters, evaporation level, and wind blowing. It's rarely easy job to measure surface waters temperature, because often, researcher has to deal with strong winds and high waves. The objectives of this research is to do surface waters temperature mapping of Grupuk Bay – West Nusa Tenggara, using thermal infrared channel of Landsat8 data, which is supported by field observation data. Surface temperature measurement is conducted through field survey in conjunction with Landsat 8 orbit. Surface temperature calculation is carried out by using certain method issued by United States Geological Survey (USGS, 2013). Calculation result on Grupuk Bay's water surface temperature shows that it ranges from 28.00 to 30.00oC, while field survey result shows that it ranges from 28.27 to 29.69oC. This research shows that sea surface temperature measurement result based on Landsat8 data has nearly identical range with field survey result. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13911 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 41-48 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13911/10824 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13912 2025-11-26T01:11:11Z ijreses:ART

APPLICATION OF CMORPH DATA FOR FOREST/LAND FIRE RISK PREDICTION MODEL IN CENTRAL KALIMANTAN Indah Prasasti Rizaldi Boer Lailan Syaufina Forest/Land Fire Risk CMORPH Monte Carlo Simulation Central Kalimantan Central Kalimantan Province is a region with high level of forest/land fire, especially during dry season. Forest/land fire is a dangerous ecosystem destroyer factor, so it needs to be anticipated and prevented as early as possible. CMORPH rainfall data have good potential to overcome the limitations of rainfall data observation. This research is aimed to obtain relationship model between burned acreage and several variables of rainfall condition, as well as to develop risk prediction model of fire occurrence and burned acreage by using rainfall data. This research utilizes information on burned acreage (Ha) and CMORPH rainfall data. The method applied in this research is statistical analysis (finding correlation and regression of two phases), while risk prediction model is generated from the resulting empirical model from relationship of rainfall variables using Monte Carlo simulation based on stochastic spreadsheet. The result of this study shows that precipitation accumulation for two months prior to fire occurrence (CH2Bl) has correlation with burned acreage, and can be estimated by using following formula (if rainfall ≤ 93 mm): Burnt Acreage (Ha) = 5.13 – 21.7 (CH2bl – 93) (R2 = 67.2%). Forest fire forecasts can be determined by using a precipitation accumulation for two months prior to fire occurrence and Monte Carlo simulation. Efforts to anticipate and address fire risk should be carried out as early as possible, i.e. two months in advance if the probability of fire risk had exceeded the value of 40%. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13912 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 41-54 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13912/10827 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13913 2025-11-26T02:42:58Z ijreses:ART

DETECTING THE AREA DAMAGE DUE TO COAL MINING ACTIVITIES USING LANDSAT MULTITEMPORAL (Case Study: Kutai Kartanegara, East Kalimantan) Suwarsono Nanik Suryo Haryani Indah Prasasti Hana Listi Fitriana M. Priyatna M. Rokhis Khomarudin Damage area coal mining Landsat multitemporal Coal is one of the most mining commodities to date, especially to supply both national and international energy needs. Coal mining activities that are not well managed will have an impact on the occurrence of environmental damage. This research tried to utilize the multitemporal Landsat data to analyze the land damage caused by coal mining activities. The research took place at several coal mine sites in East Kalimantan Province. The method developed in this research is the method of change detection. The study tried to know the land damage caused by mining activities using NDVI (Normalized Difference Vegetation Index), NDSI (Normalized Difference Soil Index), NDWI (Normalized Difference Water Index) and GEMI (Global Environment Monitoring Index) parameter based change detection method. The results showed that coal mine area along with the damage that occurred in it can be detected from multitemporal Landsat data using NDSI value-based change detection method. The area damage due to coal mining activities  can be classified into high, moderate, and low classes based on the mean and standard deviation of NDSI changes (ΔNDSI). The results of this study are expected to be used to support government efforts and mining managers in post-mining land reclamation activities. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13913 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 151-158 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13913/10826 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13914 2025-11-26T01:24:39Z ijreses:ART

DETECTING THE AFFECTED AREAS OF MOUNT SINABUNG ERUPTION USING LANDSAT 8 IMAGERIES BASED ON REFLECTANCE CHANGE Suwarsono Hidayat Jalu Tejo Nugroho Wiweka Parwati M. Rokhis Khomarudin affected area Landsat 8 NDVI Mount Sinabung reflectance The position of Indonesia as part of a "ring of fire" bringing the consequence that the life of the nation and the state will also be influenced by volcanism. Therefore, it is necessary to map rapidly the affected areas of a volcano eruption. Objective of the research is to detect the affected areas of Mount Sinabung eruption recently in North Sumatera by using optical images Landsat 8 Operational Land Imager (OLI). A pair of Landsat 8 images in 2013 and 2014, period before and after eruption, was used to analysis the reflectance change from that period. Affected areas of eruption was separated based on threshold value of reflectance change. The research showed that the affected areas of Mount Sinabung eruption can be detected and separated by using Landsat 8 OLI images based on the change of reflectance value band 4, 5 and NDVI. Band 5 showed  the highest values of decreasing and band 4 showed the highest values of increasing. Compared with another uses of single band, the combination of both bands (NDVI) give the best result for detecting the affected areas of  volcanic eruption. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13914 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 49-62 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13914/10828 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13915 2025-11-26T02:42:57Z ijreses:ART

MACHINE LEARNING-BASED MANGROVE LAND CLASSIFICATION ON WORLDVIEW-2 SATELLITE IMAGE IN NUSA LEMBONGAN ISLAND Aulia Ilham Marza Ihsan Marzuki clustering machine learning remote sensing data Machine learning is an empirical approach for regressions, clustering and/or classifying (supervised or unsupervised) on a non-linear system. This method is mainly used to analyze a complex system for  wide data observation. In remote sensing, machine learning method could be  used for image data classification with software tools independence. This research aims to classify the distribution, type, and area of mangroves using Akaike Information Criterion approach for case study in Nusa Lembongan Island. This study is important because mangrove forests have an important role ecologically, economically, and socially. For example is as a green belt for protection of coastline from storm and tsunami wave. Using satellite images Worldview-2 with data resolution of 0.46 meters, this method could identify automatically land class, sea class/water, and mangroves class. Three types of mangrove have been identified namely: Rhizophora apiculata, Sonnetaria alba, and other mangrove species. The result showed that the accuracy of classification was about 68.32%. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13915 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); 159-166 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13915/10829 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13916 2025-11-26T01:11:11Z ijreses:ART

SYNERGY APPROACH FOR IMPLEMENTING THE POLICY ON HIGH RESOLUTION IMAGERY TO ACCELERATE BASIC AND THEMATIC GEOSPATIAL INFORMATION Sukendra Martha Aris Poniman Hartono Remote sensing policy Basic and thematic geospatial information Synergy approaches Presidential Order no. 6/2012 mentioned explicitly to use ortho-rectifed image for the purposes of national program done by all Indonesian governmental agencies. Policy of uses, control quality, processing and distribution of high resolution of satellite data are regulated by this Order. There are some advantages of implementing this Order particularly in accelerating the national geospatial data and information, however, without synergy use of high resolution imagery (including integration, coordination and harmonization), in the present condition so far some obstacles have been discovered.  Without  synergic actions or approaches, the Order will not provide optimal impact as the main objectives to make more efficient in using the national budget. This article describes the needs of synergy approach to implement the Presidential Order no. 6/2012 concerning the uses, distribution of high remotely sensed imageries. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13916 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 55-62 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13916/10832 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13917 2025-11-26T02:42:57Z ijreses:BP

Back Pages IJReSES Vol. 14, No. 2(2017) Journal Editor Back Pages IJReSES Vol. 14, No. 2(2017) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13917 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 2 (2017); I-VI 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13917/10830 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13918 2025-11-26T01:24:39Z ijreses:ART

CHLOROPHYLL-A CONCENTRATIONS ESTIMATION FROM AQUA-MODIS AND VIIRS-NPP SATELLITE SENSORS IN SOUTH JAVA SEA WATERS Rayhan Nuris Jonson Lumban Gaol Teguh Prayogo Aqua-MODIS chlorophyll-a VIIRS-NPP remote sensing south Java Sea waters This study aimed to estimate the concentration of chlorophyll-a from satellite imagery of National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in the south Java Sea waters and compare it to the concentrations of chlorophyll-a estimation result from the MODIS-Aqua satellite. NPP satellite had Visible/Infrared Imager Radiometer Suite (VIIRS) sensors which performance was same as Moderate Resolution Imaging Spectroradiometer (MODIS) sensor with a better spatial resolution. This study used daily satellite imagery of VIIRS-NPP for the period of September 2012 to August 2013. The algorithm that was used to estimate the concentration of chlorophyll-a was Ocean Color 3-band ratio (OC-3). The results showed that the spatial distribution pattern of chlorophyll-a concentration between VIIRS - NPP sensor and MODIS had the same pattern, but the estimation of chlorophyll-a concentration from the MODIS sensor was higher than VIIRS -NPP sensor. The concentration of chlorophyll-a showed that there were spatial and temporal variation in the south Java Sea waters. Generally, concentrations of chlorophyll-a was higher in East monsoon than West monsoon. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13918 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 63-70 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13918/10831 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13920 2025-11-26T01:11:11Z ijreses:ART

DETECTING THE SPATIAL DISTRIBUTION OF SETTLEMENTS ON VOLCANIC REGION USING IMAGE LANDSAT-8 OLI IMAGERY Suwarsono M. Rokhis Khomarudin Settlement Volcanic Landforms Sinabung Volcano NDBI Geologically, Indonesia region is on track ring of fire, brings the consequence that the danger of volcanic eruption could occur at any time. Information sites where the settlement is located in the affected areas on emergency response process is needed in quick time. The availability of up to date data is important because it illustrates the actual condition of the region. Active volcanic landforms ranging from the crater to footslope in general is prone area to volcanic eruption, either by the threat of lava flows, pyroclastic falls, or lahars. This study aims to detect the spatial distribution of the settlement on volcanic region using Landsat-8 OLI. Parameters used for the detection of settlements is Normalized Difference Build-up Index (NDBI). Research methods include radiometric correction, delineation of the boundaries of volcanic landforms, NDBI value extraction, extraction of settlement areas, as well as the accuracy assesment.  Study area  is  Sinabung Volcano region located in the province of North Sumatera. Recently, the volcano experienced a devastating and catastrophic eruption. The results showed that the spatial distribution of settlements on volcanic landforms can be detected quickly from Landsat-8 OLI based on NDBI parameters with a sufficient degree of accuracy. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13920 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 63-72 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13920/10833 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13922 2025-11-26T02:49:56Z ijreses:FP

Front Pages IJReSES Vol. 14, No. 1(2017) Editorial Journal Front Pages IJReSES Vol. 14, No. 1(2017) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13922 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); I-VI 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13922/10837 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13923 2025-11-26T01:24:39Z ijreses:ART

MONITORING OF LAKE ECOSYSTEM PARAMETER USING LANDSAT DATA (A CASE STUDY: LAKE RAWA PENING) Bambang Trisakti Nana Suwargana Joko Santo Cahyono lake ecosystem Landsat lake water surface area TTS water clarity Most lakes in Indonesia have suffered (decrease in quality) caused by land conversion in the catchment area, soil erosion, and water pollution from agriculture and households. This study utilizes remote sensing data to monitor several parameters used as ecosystem status assessors in accordance with the guidelines of Lake Ecosystem Management provided by the Ministry of Environment. The monitoring was done at Lake Rawa Pening using Landsat TM/ETM+ satellite data over the period of 2000-2013. The data standardization was done for sun angle correction and also atmospheric correction by removing dark pixels using histogram adjustment method. RGB color composites (R: NIR + SWIR, G: NIR, B: NIR-RED) were used for water hyacinth identification; thus, the lake water surface area can be delineated. Further samples were collected for water hyacinth and water classification with Maximum Likelihood method. Total Suspended Matter (TSM) by Doxaran model and the water clarity from field measurement was correlated to build water clarity algorithm. The results show that Lake Rawa Pening was deterioting in term of quality during the period of 2000-2013; it can be seen from the dynamic rate of the shrinkage and the expansion of the lake water surface area, the uncontrolled distribution of water hyacinth which it covered 45% of the lake water surface area in 2013, the increased of TSM concentration, and the decreased of water clarity. Most parts of Rawa Pening’s water have clarity less than 2.5 m which indicated that the thropic status is hypertrophic class. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13923 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 71-81 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13923/10834 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13924 2025-11-26T01:11:11Z ijreses:ART

APPLICATION OF VAN HENGEL AND SPITZER ALGORITHM FOR INFORMATION ON BATHYMETRY EXTRACTION USING LANDSAT DATA Kuncoro Teguh Setiawan Syifa Wismayati Adawiah Takahiro OSAWA I. Wayan Nuarsa Bathymetry LANDSAT ETM+ Van Hengel and SpitzerAlgorithm Remote sensing technology provides an opportunity for effective and efficient bathymetry mapping, especially in areas which level of depth changes quickly. Bathymetry information is very useful for hydrographic and shipping safety. Landsat medium resolution satellite imagery can be used for the extraction of bathymetry information. This study aims to extract information from the Landsat bathymetry by using Van Hengel and Spitzer rotation algorithm transformation (1991) in the water of Menjangan Island, Bali. This study shows that Van Hengel and Spitzer rotation algorithm transformation (1991) can be used to extract information on the bathymetry of Menjangan Island. Extraction of bathymetric information generated from Landsat TM imagery data in March 19, 1997 had shown the depth interval of (-0.6) m to (-12.3) m and R2 value of 0.671. While Data LANDSAT ETM + dated June 23, 2000 resulted in depth interval of 0 m to (-19.1) m and R2 value of 0.796. Furthermore, data LANDSAT ETM + dated March 12, 2003 resulted in depth interval of 0 m to (-22.5) m and R2 value of 0.931. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13924 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); 73-80 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13924/10838 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13925 2025-11-26T02:49:56Z ijreses:ART

HARMFUL ALGAL BLOOM 2012 EVENT VERIFICATION IN LAMPUNG BAY USING RED TIDE DETECTION ON SPOT 4 IMAGE Emiyati Ety Parwati Syarif Budhiman harmful algal bloom Lampung Bay SPOT 4 image red tide algorithm In mid-December 2012, harmful algal bloom phenomenon occurred in Lampung Bay. Harmful Algal Bloom (HAB) is blooming of algae in aquatic ecosystems. It has negative impact on living organism, due to its toxic. This study was applied Red Tide (RT) detection algorithm on SPOT 4 images and verified the distribution of HAB 2012 event in Lampung Bay. The HAB event in 2012 in Lampung Bay can be detected by using RT algorithm on SPOT 4 images quantitatively and qualitatively. According to field measurement, the phytoplankton blooming which happen at Lampung Bay in 2012 were Cochlodinium sp. Image analysis showed that Cochlodinium sp has specific pattern of RT with values, digitally, were 13 to 41 and threshold value of red band SPOT 4 image was 57. The total area of RT distribution, which are found in Lampung Bay, was 11,545.3 Ha. Based on the RT classification of RT images and field data measurement, the RT which is caused many fishes died on the western coastal of Lampung Bay spread out from Bandar Lampung City to Batumenyan village. By using confusion matrix, the accuracy of this this method was 74.05 %. This method was expected to be used as early warning system for HAB monitoring in Lampung Bay and perhaps in another coastal region of Indonesia. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13925 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 1-8 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13925/10839 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13926 2025-11-26T01:24:39Z ijreses:BP

Back Pages IJReSES Vol. 12, No. 1(2015) Editorial Journal Back Pages IJReSES Vol. 12, No. 1(2015) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13926 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 1 (2015); 82-84 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13926/10841 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13927 2025-11-26T01:11:11Z ijreses:BP

Back Pages IJReSES Vol. 11, No. 1(2014) Editorial Secretariat Back Pages IJReSES Vol. 11, No. 1(2014) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13927 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 1 (2014); I-VI 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13927/10840 Copyright (c) 2014 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13929 2025-11-26T02:49:56Z ijreses:ART

A PARTIAL ACQUISITION TECHNIQUE OF SAR SYSTEM USING COMPRESSIVE SAMPLING METHOD compressive sampling partial acquisition technique synthetic aperture radar compressive sampling In line with the development of Synthetic Aperture Radar (SAR) technology, there is a serious problem when the SAR signal is acquired using high rate analog digital converter (ADC), that require large volumes data storage. The other problem on compressive sensing method,which frequently occurs, is a large measurement matrix that may cause intensive calculation. In this paper, a new approach was proposed, particularly on the partial acquisition technique of SAR system using compressive sampling method in both the azimuth and range direction. The main objectives of the study are to reduce the radar raw data by decreasing the sampling rate of ADC and to reduce the computational load by decreasing the dimension of the measurement matrix. The simulation results found that the reconstruction of SAR image using partial acquisition model has better resolution compared to the conventional method (Range Doppler Algorithm/RDA). On a target of a ship, that represents a low-level sparsity, a good reconstruction image could be achieved from a fewer number measurement. The study concludes that the method may speed up the computation time by a factor 4.49 times faster than with a full acquisition matrix. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13929 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 9-18 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13929/10842 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13931 2025-11-26T01:50:48Z ijreses:ART

THE USE OF MODIS DATA TO EXTRACT A DUST STORM PRODUCT Faten G. Abed Abed Alkareem Abed Ali Eshtar H. Nasser Dust storms identification composite image change detection MODIS Iraq in the summer is affected by low pressure centered in the area of Arabian Sea and the Indian Ocean, and the high pressure region in the plateau of Anatolia. This climate system causes that the Shamal wind blows from the plateau of Anatolia in the north and northwest with relatively cold temperature. From mid-June to mid-September, the wind is accompanied with intensive heating of the earth surface causing dust storms rising up to thousand meters in the atmosphere above Iraq region. In recent years, the frequency of dust storm events was increased in Iraq and its surrounding regions due to the long drought seasons. Unsupervised classification method was used to determine the intensity of the dust storm and to identify the area of dust cloud. In this study, we were able to map dust storm over Iraq region using MODIS Terra and Aqua satellite data within thermal bands (band 31 and 32), and visible band VIS (band 1). Other thermal band (band 21) was used to produce RGB composite image specifying the dust storm. A spectral subtraction between two bands was also used to produce another RGB composite image to obtain better detection for the dust storm over Iraq region. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13931 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 70-77 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13931/10843 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13935 2025-11-26T01:50:48Z ijreses:ART

COMPARISON ANALYSIS OF INTERPOLATION TECHNIQUES FOR DEM GENERATION USING CARTOSAT-1 STEREO DATA Andie Setiyoko Anil Kumar DEM Generation interpolation kriging point heigh Digital Elevation Model (DEM) can be generated using several techniques such as photogrammetric technique, interferometry, Lidar, etc. In photogrammetric technique, a DEM generation using stereo images, accuracy of generated DEM is also dependent on interpolation techniques. The process of interpolation is conducted to generate DEM as a continuous data from the point map that contained height information as a discrete data. In this research, point map was extracted from Cartosat-1 stereo image and from geodetic single frequency GPS in differential mode. Different interpolation techniques were applied on these data sets with different combination within these data sets. In this study, analysis of DEM interpolation was conducted with deterministic interpolators such as inverse distance weighted (IDW), global polynomial, local polynomial, and radial basis functions (RBF); and probabilistic interpolators such as simple kriging, ordinary kriging, universal kriging, indicator kriging, probabilistic kriging, disjunctive kriging, and cokriging. The accuracy of generated DEMs through different interpolation techniques were evaluated with ground point data collected from geodetic single frequency GPS in differential mode. Based on the analysis, the range error of DEMs generated was between 1.29 m to 2.96 m. Interpolation method with the least error was ordinary kriging using point map data and GPS points, while the highest error was obtained from global polynomial method. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13935 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 78-87 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13935/10844 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13938 2025-11-26T01:50:48Z ijreses:ART

THE EFFECT OF THE EXTENT OF CORAL REEF AREA ON UNIFORM BOTTOM REFLECTANCE DETERMINATION FOR WATER COLUMN CORRECTION USING LANDSAT ETM Syarif Budhiman Ety Parwati Emiyati coral reef Landsat ETM water column correction In one pixel of 30 meter spatial resolution of Landsat ETM multispectral sensor might consist of mixed bottom substrate types. The influence of a mixture of bottom substrate on the Landsat data can be a source of errors and together with the extent of coral reef area might contribute to affect the determination of uniform bottom reflectance. This study aimed to assess the effect of the extent of coral reef area on uniform bottom reflectance determination for water column correction. Lyzenga method was used for water column correction. This study carried out in two case studies using two sites with different size of coral reef ecosystems area i.e., Tidung island, in the Province of Jakarta and Maratua island, in the Province of East Kalimantan. Tidung island was selected to represent small area of coral reef ecosystem, while Maratua island was selected to represent relatively larger area of coral reef ecosystem. The results showed that the extent of coral reef influenced the determination of training sample areas for uniform bottom reflectance using Landsat ETM. The combination of moderate spatial resolution and the small area of coral reef ecosystem lead to the difficulties for uniform bottom substrate type determination at different depths. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13938 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 88-99 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13938/10845 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13940 2025-11-26T01:50:48Z ijreses:ART

NEW AUTOMATED CLOUD AND CLOUD-SHADOW DETECTION USING LANDSAT IMAGERY Kustiyo Dianovita Hedi Ismaya Mulia Inda Rahayu Erna Sri Adiningsih Landsat Cloud pixel Potential cloud pixel Cloud shadow Cloud cover has become a major problem in the use of optical satellite imageries, particularly in Indonesian region located along equator or tropical region with high cloud cover almost all year round. In this study, a new method for cloud and cloud shadow detection using Landsat imagery for specific Indonesian region was developed to provide a more efficient and effective way to detect clouds and cloud shadows. Landsat Top of Atmosphere (TOA) reflectance and Brightness Temperature (BT) were used as inputs into the model. The first step was to detect cloud based on cloud physical properties using albedo and thermal bands, the second step was to detect cloud shadows using the Near Infrared (NIR), and Short Wave Infrared (SWIR) bands, and finally, the geometric relationships were used to match the cloud and cloud shadow layer, before proceeding to the production of the final cloud and cloud shadow mask. The results were then compared with other method such as tree base cloud separation. It showed that method we proposed could provide better result than tree base method, the accuracy result of this method was 98.75%. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13940 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 100-111 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13940/10848 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13944 2025-11-26T02:49:55Z ijreses:ART

VALIDATION OF COCHLODINIUM POLYKRIKOIDES RED TIDE DETECTION USING SEAWIFS-DERIVED CHLOROPHYLL-A DATA WITH NFRDI RED TIDE MAP IN SOUTH EAST KOREAN WATERS Gathot Winarso Joji Ishizaka cochlodinium polykrikoides chlorophyll-a SeaWiFS red tide Annual summer red tides of Cochlodinium polykrikoides have happenned at southern coastal  of the South Korea, accounted economic losses of 76.4 billion won in 1995 on fisheries and other economic substantial losses. Therefore, it is important to eliminate the damage and losses by monitoring the bloom and to forecast their development and movement. On previous study, ocean color satellite, SeaWiFS, standard chlorophyll-a data was used to detect the red tide, using threshold value of chlorophyll-a concentration ≥ 5 mg/m3, resulted a good correlation using visual comparison. However, statistic based accuracy analysis has not be done yet. In this study, the accuracy of detection method was analyzed using spatial statistic. Spatial statistical match up analysis resulted 68% of red tide area was not presented in satellite data due to masking. Within red tide area where data existed, 36% was in high chlorophyll-a area and 64% was in low chlorophyll-a area. Within the high chlorophyll-a area 13% and 87% was in and out of the red tide area. It was found that the accuracy of this detection is low. However if the accuracy was yearly splitted, its found that 75% accuracy on 2002 where visually red tide detected spead out to the off-shore area. The fail and false detection are not due to the failure of the detection method but caused by limitation of the technology due to the natural condition i.e. type of red tide spreading, cloud cover and other flags such as turbid water, stray light etc. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13944 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 19-26 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13944/10852 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13945 2025-11-26T01:50:48Z ijreses:ART

SEMI-AUTOMATIC SHIP DETECTION USING PI-SAR-L2 DATA BASED ON RAPID FEATURE DETECTION APPROACH Katmoko Ari Sambodo Ship detection synthetic aperture radar Pi-SAR-L2 keypoint SURF detector Synthetic Aperture Radar (SAR) satellite an active sensor offering unique high spatial resolution regardless of weather conditions can operate both day and night time with wide area coverage. Therefore, SAR satellite can be used for monitoring ship on sea surface. This study showed on an alternative method for ship detection of SAR data using Pi-SAR-L2 (L-band, JAXA-Airborne SAR) data. The ship detection method is this study was consisted of eight main stages. After the Pi-SAR data was registered and speckle was filtered, then the land was masked using SRTM-DEM (Shuttle Radar Topography Mission-Digital Elevation Model) data since most ship detectors produced false detections when it applied to land areas. A ship sample image was then selected (cropped). The next step was to detect some unique keypoints of ship sample image using Speeded Up Robust Features (SURF) detector. The maximum distance (‘MaxDist’) of keypoints was also calculated. The same detector was then applied to whole Pi-SAR imagery to detect all possible keypoints. Then, for each detected keypoint, we calculated distance to other keypoint (‘Dist’). If ‘Dist’ was smaller than ‘MaxDist’, then we marked these two (or more) keypoints as neighboring keypoints. If the number of neighbor keypoints was equal or greater than two, finally we marked these keypoints as ‘Detected Ship’ (draw rectangle and show its geographic position). Results showed that our method can detect successfully 32 ‘possible ships’ from Pi-SAR-L2 data acquired on the area of North Sulawesi, Indonesia (August 8, 2012). BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13945 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 112-119 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13945/10851 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13947 2025-11-26T01:50:47Z ijreses:ART

SITE SELECTION OF SEAWEED CULTURE USING SPOT AND LANDSAT SATELLITE DATA IN PARI ISLAND Bidawi Hasyim Wawan K. Harsanugraha Yennie Marini Anneke K.S. Manoppo satellite data seaweed culture site selection coastal waters One of several factors for seaweed culture success is to determine the suitable location for seaweed culture based on oceanographic parameters. The best location for seaweed culture is coastal waters with suitable requirements for total suspended solid (TSS), sea surface temperature (SST), and area with calm water that is sheltered from waves, strong current and predator, such as lagoon in the middle of an atoll. The purpose of this study was to locate the suitable area for seaweed culture in Pari island, Seribu island using SPOT and LANDSAT-TM data. The results showed that TSS in Pari island waters were in the range of 150 mg/l - 200 mg/l, SST in the range of 22-29°C, while coral reefs and lagoon was only available in some coastal locations. The analysis showed that most of Pari island waters were suitable for seaweed culture. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13947 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 120-127 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13947/10853 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13948 2025-11-26T02:49:55Z ijreses:ART

A COMPARISON OF OBJECT-BASED AND PIXEL-BASED APPROACHES FOR LAND USE/LAND COVER CLASSIFICATION USING LAPAN-A2 MICROSATELLITE DATA Jalu Tejo Nugroho Zylshal Nurwita Mustika Sari Dony Kushardono LAPAN-A2 microsatellite LU/LC object-based pixel-based In recent years, small satellite industry has been a rapid trend and become important especially when associated with operational cost, technology adaptation and the missions. One mission of LAPAN-A2, the 2nd generation of microsatellite that developed by Indonesian National Institute of Aeronautics and Space (LAPAN), is Earth observation using digital camera that provides imagery with 3.5 m spatial resolution. The aim of this research is to compare between object-based and pixel-based classification of land use/land cover (LU/LC) in order to determine the appropriate classification method in LAPAN-A2 dataprocessing (case study Semarang, Central Java).The LU/LC were classified into eleven classes, as follows: sea, river, fish pond, tree, grass, road, building 1, building 2, building 3, building 4 and rice field. The accuracy of classification outputs were assessed using confusion matrix. The object-based and pixel-based classification methods result for overall accuracy are 31.63% and 61.61%, respectively. According to accuracy result, it was thought that blurring effect on LAPAN-A2 data may be the main cause ofaccuracy decrease. Furthermore, the result is suggested to use pixel-based classification to be applied inLAPAN-A2 data processing. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13948 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 27-36 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13948/10854 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13949 2025-11-26T02:49:55Z ijreses:ART

VERIFICATION OF PISCES DISSOLVED OXYGEN MODEL USING IN SITU MEASUREMENT IN BIAK, ROTE, AND TANIMBAR SEAS, INDONESIA Armyanda Tussadiah Joko Subandriyo Sari Novita Widodo S. Pranowo verification PISCES model dissolved oxygen in situ measurement indonesia linear regression Dissolved oxygen (DO) is one of the most chemical primary data in supported life for marine organisms. Ministry of Marine Affairs and Fisheries Republic of Indonesia through Infrastructure Development for Space Oceanography (INDESO) Project provides dissolved oxygen data services in Indonesian Seas for 7 days backward and 10 days ahead (9,25 km x 9.25 km, 1 daily). The data based on Biogeochemical model (PISCES) coupled with hydrodynamic model (NEMO), with input data from satellite acquisition. This study investigated the performance and accuracy of dissolved oxygen from PISCES model, by comparing with the measurement in situ data in Indonesian Seas specifically in three outermost islands of Indonesia (Biak Island, Rote Island, and Tanimbar Island). Results of standard deviation values between in situ DO and model are around two (St.dev ± 2). Based on the calculation of linear regression between in situ DO with the standard deviation obtained a high determinant coefficient, greater than 0.9 (R2 â‰¥ 0.9). Furthermore, RMSE calculation showed a minor error, less than 0.05. These results showed that the equation of the linear regression might be used as a correction equation to gain the verified dissolved oxygen. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13949 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 37-46 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13949/10858 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13951 2025-11-26T01:50:47Z ijreses:ART

COASTAL UPWELLING UNDER THE INFLUENCE OF WESTERLY WIND BURST IN THE NORTH OF PAPUA CONTINENT, WESTERN PACIFIC Harold J.D.Waas Vincentius P. Siregar Indra Jaya Jonson Lumban Gaol Coastal upwelling wind burst El Nino Ekman transport Ekman layer Depth Coastal upwelling play an important role in biological productivity and the carbon cycle in the ocean. This research aimed to examine the phenomenon of coastal upwelling that occur in the coastal waters north of Papua continent under the influence of Westerly Wind Burst(WWB) prior to the development of El Nino in the Pacific. Data consisted of sea surface temperature, vertical oceanic temperature, ocean color satellite image, wind stress and vector wind speed image, sea surface high, and Nino 3.4 index. Coastal upwelling events in the northern coastal waters of Papua continent occurred in response to westerly winds and westerly wind burst (WWBs) during December to March characterizing by low sea surface temperature (SST) (25 - 28ï‚°C), negative sea surface high deviation and phytoplankton blooming, except during pre-development of the El Nino 2006/2007 where weak upwelling followed by positive sea surface high deviation. Strong coastal upwelling occurred during two WWBs in December and March1996/1997 with maximum wind speed in March produced a strong El Nino 1997/1998. Upwelling generally occurred along coastal waters of Jayapura to Papua New Guinea with more intensive in coastal waters north of Papua New Guinea indicated by Ekman transport and Ekman layer depth maximum. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13951 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 128-139 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13951/10856 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13953 2025-11-26T02:49:55Z ijreses:ART

IN-SITU MEASUREMENT OF DIFFUSE ATTENUATION COEFFICIENT AND ITS RELATIONSHIP WITH WATER CONSTITUENT AND DEPTH ESTIMATION OF SHALLOW WATERS BY REMOTE SENSING TECHNIQUE Budhi Agung Prasetyo Vincentius Paulus Siregar Syamsul Bahri Agus Wikanti Asriningrum in-situ measurement diffuse attenuation coefficient relationship with water constituent depth estimation shallow water remote sensing Diffuse attenuation coefficient, Kd(λ), has an empirical relationship with water depth, thus potentially to be used to estimate the depth of the water based on the light penetration in the water column. The aim of this research is to assess the relationship of diffuse attenuation coefficient with the water constituent and its relationship to estimate the depth of shallow waters of Air Island, Panggang Island and Karang Lebar lagoons and to compare the result of depth estimation from Kd model and derived from Landsat 8 imagery. The measurement of Kd(λ) was carried out using hyperspectral spectroradiometer TriOS-RAMSES with range 320 – 950 nm. The relationship between measurement Kd(λ) on study site with the water constituent was the occurrence of absorption by chlorophyll-a concentration at the blue and green spectral wavelength. Depth estimation using band ratio from Kd(λ) occurred at 442,96 nm and 654,59 nm, which had better relationship with the depth from in-situ measurement compared to the estimation based on Landsat 8 band ratio. Depth estimated based on Kd(λ) ratio and in-situ measurement are not significantly different statistically. Depth estimated based on Kd(λ) ratio and in-situ measurement are not significantly different statistically. However, depth estimation based on Kd(λ) ratio was inconsistent due to the bottom albedo reflection because the Kd(λ) measurement was carried out in shallow waters. Estimation of water depth based on Kd(λ) ratio had better results compared to the Landsat 8 band ratio. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13953 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 47-60 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13953/10861 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13954 2025-11-26T01:50:47Z ijreses:ART

DROUGHT AND FINE FUEL MOISTURE CODE EVALUATION: AN EARLY WARNING SYSTEM FOR FOREST/LAND FIRE USING REMOTE SENSING APPROACH Yenni Vetrita Indah Prasasti Nanik Suryo. Haryani M. Priyatna M. Rokhis Khomarudin Fire danger rating systes Drought code Fine fuel moisture code This study evaluated two parameters of fire danger rating system (FDRS) using remote sensing data i.e. drought code (DC) and fine fuel moisture code (FFMC) as an early warning program for forest/land fire in Indonesia. Using the reference DC and FFMC from observation data, we calculated the accuracy, bias, and error. The results showed that FFMC from satellite data had a fairly good correlation with FFMC observations (r=0.68, bias=7.6, and RMSE=15.7), while DC from satellite data had a better correlation with FFMC observations (r=0.88, bias=49.91, and RMSE=80.22). Both FFMC and DC from satellite and observation were comparable. Nevertheless, FFMC and DC satellite data showed an overestimation values than that observation data, particularly during dry season. This study also indicated that DC and FFMC could describe fire occurrence within a period of 3 months before fire occur, particularly for DC. These results demonstrated that remote sensing data can be used for monitoring and early warning fire in Indonesia. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13954 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 2 (2012); 140-147 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13954/10860 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13957 2025-11-26T02:49:55Z ijreses:ART

TIME SERIES ANALYSIS OF TOTAL SUSPENDED SOLID (TSS) USING LANDSAT DATA IN BERAU COASTAL AREA, INDONESIA Ety Parwati Anang Dwi Purwanto TSS Landsat 5 TM Landsat 7 ETM + Landsat 8 watershed mangrove Water quality information is usually used for the first examination of the pollution.  One of the parameters of water quality is Total Suspended Solid (TSS), which describes the amount of matter of particles suspended in the water. TSS information is also used as initial information about waters condition of a region. TSS could be derive from Landsat data with several combinations of spectral channels to evaluate the condition of the observation area for both the waters and the surrounding land. The study aimed to evaluate Berau waters condition in Kalimantan, Indonesia, by utilizing TSS dynamics extracted from Landsat data. Validated TSS extraction algorithm was obtained by choosing the best correlation between  field data and image data. Sixty pairs of points had been used to build validated TSS algorithms for the Berau Coastal area. The algorithm was TSS = 3.3238 * exp (34 099 * Red Band Reflectance). The data used for this study were Landsat 5 TM, Landsat 7 ETM and Landsat 8 data acquisition in 1994, 1996, 1998, 2002, 2004, 2006, 2008 and 2013. For detailed evaluation, 20 regions were created along the watershed up to the coast. The results showed the fluctuation of TSS values in each selected region. TSS value increased if there was a change of any kind of land cover/land used into bareland, ponds, settlements or shrubs. Conversely, TSS value decreased if there was a wide increase of mangrove area or its position was very closed to the ocean. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13957 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 61-70 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13957/10863 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13959 2025-11-26T02:49:54Z ijreses:ART

SIMULATION OF DIRECT GEOREFERENCING FOR GEOMETRIC SYSTEMATIC CORRECTION ON LSA PUSHBROOM IMAGER Muchammad Soleh Wismu Sunarmodo Ahmad Maryanto direct georeferencing pushbroom imager systematic geometric correction LSA LAPAN has developed remote sensing data collection by using a pushbroom linescan imager camera sensor mounted on LSA (Lapan Surveillance Aircraft). The position accuracy and orientation system for LSA applications are required for Direct Georeferencing and depend on the accuracy of off-the-shelf integrated GPS/inertial system, which used on the camera sensor. This research aims to give the accuracy requirement of Inertial Measurement Unit (IMU) sensor and GPS to improve the accuracy of the measurement results using direct georeferencing technique. Simulations were performed to produce geodetic coordinates of longitude, latitude and altitude for each image pixel in the imager pushbroom one array detector, which has been geometrically corrected. The simulation results achieved measurement accuracies for mapping applications with Ground Sample Distance (GSD) or spatial resolution of 0,6 m of the IMU parameter (pitch, roll and yaw) errors about 0.1; 0.1; and 0.1 degree respectively, and the error of GPS parameters (longitude and latitude) about 0.00002 and 0.2 degree. The results are expected to be a reference for a systematic geometric correction to image data pushbroom linescan imager that would be obtained by using LSA spacecraft. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13959 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); 71-82 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13959/10865 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13960 2025-11-26T02:28:45Z ijreses:ART

ANALYSIS OF CRITICAL LAND IN THE MUSI WATERSHED USING GEOGRAPHIC INFORMATION SYSTEMS Danang Surya Candra Critical Land Watershed Remote Sensing GIS Weighting Method SPO-4 Critical land is a land that is no longer functioning as a regulator of water, agricultural production elements and environmental protection elements. Owing to the fact that the analysis of critical land is usually carried out manually, the probability of errors in processing (human error) is very high. This research utilizes the Geographic Information System (GIS) technology to analyze critical area in protected forest area of Musi Watershed. The application of GIS technology, enables the analysis of critical land according to standard of critical land criteria. The results show that the very critical level area in protected forest area of Musi Watershed is 1.7%. The dominant level is in critical potential area (53.34%). BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13960 International Journal of Remote Sensing and Earth Sciences; Vol. 8 (2011); 13-18 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13960/10866 Copyright (c) 2011 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13962 2025-11-26T02:49:54Z ijreses:BP

Back Pages IJReSES Vol. 14, No. 1(2017) Editorial Journal Back Pages IJReSES Vol. 14, No. 1(2017) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13962 International Journal of Remote Sensing and Earth Sciences; Vol. 14 No. 1 (2017); I-VII 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13962/10867 Copyright (c) 2017 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13966 2025-11-26T02:28:45Z ijreses:ART

CO2 FLUX IN INDONESIAN WATER DETERMINED BY SATELLITE DATA Ni Wayan Ekayanti Abd. Rahman as-syakur CO2 flux salinity SST sink and sources of CO2 The oceans was considered to be a major sink for CO2. The improving of quantitative and qualitative description about the ability of sea in uptaking or emitting CO2 is a great scientific concern in meteorological and climatological science. Measurement of the ability of sea in uptake or emitting CO2 could determined by measuring the CO2 exchange coefficient on sea interface and the measuring the different partial pressure of CO2 between the air and sea. In this study, CO2 flux distribution of Indonesian waters in 2007 to 2009 was computed using monthly CO2 exchange and the different partial pressure of CO2 estimated from wind speed, salinity, SST, and sea characteristic, which were obtained from satellite data. The carbon dioxide flux thus was estimated and discussed by two different designs of transfer velocity (k), of Wanninkhof (1992), kW92 relationship and by Nightingale et al. (2000), kN, relationship. The result indicated that generally, Indonesian water was emitting the CO2 to the air. Average CO2 emitting from sea to the air for recent year in 2007 to 2009 are 3.80 (mol m-2year-1) and 2.85 (mol m-2year-1) with kW92 relationship and kN relationship calculation, respectively. The total average CO2 emission from sea to the air in 2007 to 2009 for the Indonesian waters areas are 0.15 (PgC year-1) and 0.12 (PgC year-1) based on kW92 relationship and kN relationship calculations, respectively. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13966 International Journal of Remote Sensing and Earth Sciences; Vol. 8 (2011); 1-12 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13966/10870 Copyright (c) 2011 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13967 2025-11-26T02:53:53Z ijreses:FP

Front Pages IJReSES Vol. 12, No. 2(2015) Editorial Journal Front Pages IJReSES Vol. 12, No. 2(2015) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13967 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); I-XV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13967/10871 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13969 2025-11-26T02:53:52Z ijreses:ART

MANGROVE ABOVE GROUND BIOMASS ESTIMATION USING COMBINATION OF LANDSAT 8 AND ALOS PALSAR DATA Gathot Winarso Yenni Vetrita Anang D Purwanto Nanin Anggraini Soni Darmawan Doddy M. Yuwono Mangrove biomass Landsat 8 ALOS PALSAR Mangrove ecosystem is important coastal ecosystem, both ecologically and economically. Mangrove provides rich-carbon stock, most carbon-rich forest among ecosystems of tropical forest. It is very important for the country to have a large mangrove area in the context of global community of climate change policy related to emission trading in the Kyoto Protocol. Estimation of mangrove carbon-stock using remote sensing data plays an important role in emission trading in the future. Estimation models of above ground mangrove biomass are still limited and based on common forest biomass estimation models that already have been developed. Vegetation indices are commonly used in the biomass estimation models, but they have low correlation results according to several studies. Synthetic Aperture Radar (SAR) data with capability in detecting volume scattering has potential applications for biomass estimation with better correlation. This paper describes a new model which was developed using a combination of optical and SAR data. Biomass is volume dimension related to canopy and height of the trees. Vegetation indices could provide two dimensional information on biomass by recording the vegetation canopy density and could be well estimated using optical remote sensing data. One more dimension to be 3 dimensional feature is height of three which could be provided from SAR data. Vegetation Indices used in this research was NDVI extracted from Landsat 8 data and height of tree estimated from ALOS PALSAR data. Calculation of field biomass data was done using non-decstructive allometric based on biomass estimation at 2 different locations that are Segara Anakan Cilacap and Alas Purwo Banyuwangi, Indonesia. Correlation between vegetation indices and field biomass with ALOS PALSAR-based biomass estimation was low. However, multiplication of NDVI and tree height with field biomass correlation resulted R2 0.815 at Alas Purwo and R2 0.081 at Segara Anakan.  Low correlation at Segara anakan was due to failed estimation of tree height. It seems that ALOS PALSAR height was not accurate for determination of areas dominated by relative short trees as we found at Segara Anakan Cilacap, but the result was quite good for areas dominated by high trees. To improve the accuracy of tree height estimation, this method still needs validation using more data. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13969 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 85-96 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13969/10874 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13970 2025-11-26T02:28:44Z ijreses:ART

TREND IN PRECIPITATION OVER SUMATERA UNDER THE WARMING EARTH Iskhaq Iskandar Muhammad Irfan Fadli Syamsuddin Akmal Johan Pradanto Poerwono Climate variations Dry season Precipitation Sumatera and Kalimantan Wet season A long-term climate variations in the western Indonesian region (e.g. Sumatera) were evaluated using precipitation data as a proxy. The result showed that there was a long-term climate variation over Sumatera region indicated by a decreasing trend in precipitation (drying trend). Moreover, the long-term precipitation trend has a strong seasonality. Remarkable decreasing trend at a rate of 3.9 cm/year (the largest trend) was observed during the northwest monsoon (DJF) season, while the smallest decreasing trend of 1.5 cm/year occurred during the southeast monsoon (JJA) season. This result suggested that the Sumatera Island experienced a drying trend during the northwest monsoon season, and a dryer condition will be more frequently observed during the southeast monsoon season. The long-term precipitation over the Sumatera Island was linked to coupled air-sea interactions in the Indian and Pacific oceans. The connection between the seasonal climate trends and sea surface temperature (SST) in the Indian and Pacific oceans was demonstrated by the simultaneous correlations between the climate indices (e.g. Dipole Mode Index (DMI) and the Niño3.4 index) and the precipitation over the Sumatera Island. The results suggested that both the Indian Ocean Dipole (IOD) and the El Niño-Southern Oscillation Index (ENSO) have significant correlation with precipitation. However, remarkable correlations were observed during the fall transition of the IOD event. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13970 International Journal of Remote Sensing and Earth Sciences; Vol. 8 (2011); 19-24 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13970/10873 Copyright (c) 2011 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13972 2025-11-26T02:53:52Z ijreses:ART

THE EFFECT OF HYDROLOGIC RESPONSE UNIT ON CI RASEA WATERSHED STREAMFLOW BASED ON LANDSAT TM Emiyat Eko Kusratmoko Sobirin SWAT HRU landcover watershed Landsat Ci Rasea . This paper discusses spatial pattern of Hydrologic Response Unit (HRU), which is a unit formed of hydrological analysis, including geology and soil type, elevation and slope, and also land cover in 2009. This paper also discusses the impact of HRU on streamflow of Ci Rasea watershed, West Java. Ci Rasea watershed is located at the upstream part of Ci Tarum watersheds in West Java Province, Indonesia. This research used SWAT (Soil and Water Assessment Tool) model to obtain spatial HRU and river flow. The method used Landsat TM data for land cover and daily rainfall for river flow modeling. The results have shown spatial pattern of HRU which was affected by land cover, soil type and slope. In 2009, accumulated surface runoff and streamflow changes were spatially affected by HRU changes. The large amount accumulation of river flow discharge happened in HRU with landcover paddy field, silty clay soil, and flat slope. While the low discharge of river flow happened in HRU with plantation, clay soil, and slightly steep slopes as HRU dominant. It was found that accumulation of surface runoff in Ci Rasea watershed can be reduced by changing the land cover type in some areas with clay and slightly steep slope to become plantation area and the areas with sandy loam soil and flat slope can be used for paddy fields. Beside affected by HRU, the river flow discharge was also affected by the distance of sub watershed to the outlet. By using NS model and statistical t-student for calibration and validation, it was obtained that the accuracy of river flow models with HRU was 70%. It meant that the model could better simulate water flows of the Ci Rasea watershed.   BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13972 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 97-106 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13972/10876 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13976 2025-11-26T02:53:52Z ijreses:ART

HEIGHT MODEL INTEGRATION USING ALOS PALSAR, X SAR, SRTM C, AND ICESAT/GLAS Atriyon Julzarika integration height model SAR data scale 1:10.000 The scarcity of height models is one of the important issues in Indonesia. ALOS PALSAR, X SAR, SRTM C, and ICESAT/GLAS are free available global height models. Four data can be integrated the height models. Integration takes advantage of each characteristic data. The spatial resolution uses ALOS PALSAR. ICESAT/GLAS has a minimal height error because it is DTM. SAR has advantages of minimal error in the highland and need a low pass filter on the lowland. DSM uses X SAR and DEM from ALOS PALSAR. Characteristics and penetration of vegetation objects can be seen from the wavelength type of SAR data. This research aims to make height model integration in order to get the vertical accuracy better than vertical accuracy of global height models and minimum height error. The study area is located in Karo Regency. The first process is to crop the height models into Karo Regency, geoid undulation correction using EGM 2008. The next step is to detect pits and spires by using radius value 1000 m and depth +1.96σ (+5 m) with uncertainty 95,45%. Then generate HEM and height model integration. To know the accuracy of this height model, 100 reference points measured using GNSS, altimeter, and similar point observed on the height model integration are selected. The accuracy test covers RMSE, accuracy (z), and height difference test. The result of this study shows that the height model integration has a vertical accuracy in 1.14 m. This height model integration can be used for mapping scale 1: 10.0000. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13976 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 107-116 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13976/10878 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13977 2025-11-26T02:28:44Z ijreses:ART

VARIABILITY AND VALIDATION OF SEA SURFACE TEMPERATURE ESTIMATED BY PATHFINDER ALGORITHM OF NOAA-AVHRR SATELLITE IN THE NORTH PAPUA WATERS Bisman Nababan Bidawi Hasyim Hilda I.N. Bada SST Pathfinder NOAA AVHRR Validation TAO buoy North Papua Waters Variability and validation of sea surface temperatures (SST) in north Papua waters were conducted using SST estimated by Pathfinder algorithm of NOAA AVHRR satellite and SST measurements from TAO buoy in 2001-2009. Satellite data (SST Pathfinder) were daily, weekly, and monthly composite with 4x4 km2 resolution and downloaded from http://poet.jpl.nasa.gov. In situ data (SST measurement from buoy TAO) were measured at a depth of 1.5 m and recorded every hour (http://www.pmel.noaa.gov/tao_deliv). The in situ data then converted into daily, weekly, and monthly average data. In general, the SST values of both satellite and in situ SST in the north Papua waters ranged between 27.10 - 31.90 °C. During the east season (June-September), SST values (27.90-31.90 °C) were generally higher than the SST values ( 27.10-30.13 °C) during the west season (December-February). In general, the SST values both day-time and night-time from in situ and the satellite measurements showed no significant differences except in waters close to the shore. The results also showed that the coefficient of determination values (R2) between the satellite and the in situ SST measurements were relatively low (65%) and up to 5% of RMSE. The relatively low correlation between in situ dan satellite SST measurements may be due to high cloud coverage (90-96%) in the north Papua waters so that SST satellite data become less representative of the in situ data. These results also indicated that the Pathfinder algorithm can not be used as a valid estimate of SST NOAA AVHRR satellite for the north Papua waters. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13977 International Journal of Remote Sensing and Earth Sciences; Vol. 8 (2011); 25-31 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13977/10881 Copyright (c) 2011 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13979 2025-11-26T02:53:52Z ijreses:ART

WATER CLARITY MAPPING IN KERINCI AND TONDANO LAKE WATERS USING LANDSAT 8 DATA Bambang Trisakti Nana Suwargana I Made Parsa lake water SDT TSS tropic state water clarity Land conversion occurred in the lake catchment area caused the decreasing of water quality in many lakes of Indonesia. According to Lake Ecosystem Management Guidelines from Ministry of Environment, tropic state of lake water is one of parameters for assessing the lake ecosystem status. Tropic state can be indicated by the quantity of nitrogen, phosphorus, chlorophyll, and water clarity. The objective of this research is to develop the water quality algorithm and map the water clarity of lake water using Landsat 8 data. The data were standardized for sun geometry correction and atmospheric correction using Dark Object Subtraction method. In the first step, Total Suspended Solid (TSS) distributions in the lake were calculated using a semi empirical algorithm (Doxaran et al., 2002), which can be applied to a wide range of TSS values. Secchi Disk Transparency (SDT) distributions were calculated using our water clarity algorithm that was obtained from the relationship between TSS and SDT measured directly in the lake waters. The result shows that the water clarity algorithm developed in this research has the determination coefficient that reaches to 0,834. Implementation of the algorithm for Landsat 8 data in 2013 and 2014 showed that the water clarity in Kerinci Lake waters was around 2 m or less, but the water clarity in Tondano Lake waters was around 2 – 3 m. It means that Kerinci Lake waters had lower water clarity than Tondano Lake waters which is consistent with the field measurement results.   BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13979 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 117-124 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13979/10880 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13981 2025-11-26T02:53:52Z ijreses:ART

OZONE VARIABILITY AND OZONE DEPLETING SUBSTANCES (ODS) IN INDONESIA BASED ON MLS-AURA DATA Ninong Komala Novita Ambarsari BrO ClO MLS-AURA ozone Research and characterizing the ozone profiles and Ozone Depleting Substances (ODS) in Indonesia is a satellite data-based research activities. The aim of the study was to obtain the characteristics of ozone in Indonesia as well as the contribution of ODS to the variability of ozone. By performing a data inventory based on satellite data, analyze the pattern of annual, seasonal and perform linkage analysis of the contribution of ODS changes to the conditions of ozone. Daily data of vertical profiles of ozone and  in the form of volume mixing ratio (vmr) with format HDF (Hierarchical Data Format) is extracted to the territory of Indonesia to take parameters as latitude, longitude, and concentration. Then converted to Excel format with the help of data processing software of MATLAB. Results obtained in the form of ozone characteristics in Indonesia, the percentage of contribution to the variability of ozone also contribution to the variability of ozone in Indonesia in several levels of height. By using Microwave Limb Sounders (MLS) AURA satellite data in the period of 2005 to 2013 characteristics of monthly vertical profiles of ozone in Indonesia has been obtained. The ODS studied were ClO and BrO. Peak of vertical profiles of ozone occurs at a pressure of 10 hPa or altitude of 25.9 km. ClO peak occurs at a pressure of 2.1 hPa or altitude of 30.6 km and BrO reached the peak at 14 hPa or altitude of 24.5 km. When ClO and BrO reach a maximum concentration at stratosphere then ozone molecules is potentially damaging or decrease in the stratosphere. Temporal variations of ozone showed decrease when  ODS concentrations increased (particularly ClO and BrO). Linear regression of ozone with ozone showed a negative correlation coefficient which indicates there is a strong relationship between ozone concentrations decline in pressure of 14 hPa when BrO reach the maximum. Likewise for ClO which also showed a negative correlation with the decrease in ozone concentration. ClO contribution to the decreasing of ozone in Indonesia was marked by every addition of 0.01 ppb ClO will reduce ozone of  0.00583 ppm (5.83 ppb). While any increase of  0.01 ppb of BrO will decrease 0.03 ppb of ozone. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13981 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 125-134 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13981/10883 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13982 2025-11-26T02:53:51Z ijreses:ART

ANALYSIS ON THE QUALITY OF AEROSOL OPTICAL THICKNESS DATA DERIVED FROM NPP VIIRS AND AQUA MODIS OVER WESTERN REGION OF INDONESIA Erna Sri Adiningsih Andy Indrajat Noriandini D. Salyasari aerosol optical thickness NPP VIIRS EDR Aqua MODIS sun glint cloud masking Preliminary analysis on quality data of Aerosol Optical Thickness/Depth or AOT/AOD derived from NPP VIIRS EDR (Environmental Data Record) has been done in previous work. Qualitative analysis of the previous work revealed that AOT data of VIIRS had insufficient quality due to some factors such as sun glint and cloud cover. However the accuracy of AOT VIIRS data over western area of Indonesia has not been investigated. Therefore this paper describes further analysis on AOT VIIRS data quality and accuracy. Comparison with AOT derived from Aqua MODIS data was implemented since AOT of MODIS has verified well with AOT data from field observation. Examination on cloud masking intermediate product of VIIRS was done for its importance in AOT data processing and persistent cloud cover obstacle over Indonesia. We used VIIRS and MODIS data archieved by LAPAN ground station. Further analysis on sun glint and cloud masking images indicates that these two intermediate products predominantly affect the quality of AOT from VIIRS and MODIS over the study areas. Compared with AOT of MODIS, AOT of VIIRS seems to result more pixels consisting AOT information over the same area and date. The statistical results showed that AOT values of VIIRS highly correlated with AOT values of MODIS with R2 of 78%. The accuracy of AOT derived from VIIRS was adequate as indicated by RMSE of  0.0977 or less than 0.5 for the samples over Sumatra, Borneo, and Java islands. Visual comparison of AOT images indicates that VIIRS data could result more detailed AOT values than MODIS data. Therefore the AOT of VIIRS data could be recommended for further applications in western area of Indonesia.   BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13982 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 135-142 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13982/10884 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13983 2025-11-26T02:28:44Z ijreses:ART

DEVELOPING TROPICAL LANDSLIDE SUSCEPTIBILITY MAP USING DINSAR TECHNIQUE OF JERS-1 SAR DATA Ilham Alimuddin Luhur Bayuaji Haeruddin C. Maddi Josaphat Tetuko Sri Sumantyo Hiroaki Kuze Optical Images JERS-1 SAR DInSAR Tropical Landslide GIS Susceptibility Map 1 Introduction Recently natural disasters increased in terms of frequency complexity scope and destructive capacity Comprehensive information in natural disaster area is essential to prevent and mitigate people from further damage that might occur before and after such event. Mapping this area is one way to comprehend the situation when disaster strikes. Remote sensing data have been widely used along with GIS to create a susceptibility map. The objective of this study was to develop existing landslides susceptibility map by integrating optical satellite images of Landsat ETM and ASTER with Japanese Earth Resource Satellites (JERS-1) Synthetic Aperture Radar (SAR) data complemented by ground GPS and feature measurement into a Geographical Information Systems (GIS) platform. The study area was focused on a landslide event occurred on 26 March 2004 in Jeneberang Watershed of South Sulawesi, Indonesia. Change detection analysis was used to extract thematic information and the technique of Differential SAR Interferometry (DInSAR) was employed to detect slight surface displacement before the landslide event. The DInSAR processed images would be used to add as one weighted analysis factor in creating landslide susceptibility map. The result indicated that there was a slight movement of the slope prior to the event of landslide during the JERS-1 SAR data acquisition period of 1993-1998.  Keywords: Optical Images, JERS-1 SAR, DInSAR, Tropical Landslide, GIS, Susceptibility Map 1. Introduction Recently, natural disasters increased in terms of frequency, complexity, scope, and destructive capacity. They have been particularly severe during the last few years when the world has experienced several large-scale natural disasters such as the Indian Ocean earthquake and tsunami; floods and forest fires in Europe, India and China, and drought in Africa (Sassa, 2005). Mapping such natural disaster areas is essential to prevent and mitigate people from further damage that might occur before and after such event. In Indonesia in p.articular, in these recent years natural disasters occurred more frequently compared to the last decade (BNPB, 2008). Once within a month in 2011, in three different islands, Indonesia was stricken by earthquake, tsunami, flash floods, and volcanic eruptions with severe fatalities to the people and environment. It was obvious that Indonesia was prone to natural disaster due to its position of being squeezed geologically by three major world plates and this fact makes Indonesia one of the most dangerous BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13983 International Journal of Remote Sensing and Earth Sciences; Vol. 8 (2011); 32-40 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13983/10886 Copyright (c) 2011 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13985 2025-11-26T02:53:51Z ijreses:ART

IDENTIFICATION OF LAND SURFACE TEMPERATURE DISTRIBUTION OF GEOTHERMAL AREA IN UNGARAN MOUNT BY USING LANDSAT 8 IMAGERY Udhi C. Nugroho Dede Dirgahayu Domiri land surface temperature Landsat MODIS geothermal Ungaran Indonesia located at the confluence of Eurasian tectonic plate, Australian tectonic plate and the Pacific tectonic plate. Therefore, Indonesia has big geothermal potential. One of the areas that has geothermal potential is Ungaran Mount. Remote sensing technology can have a role in geothermal exploration activity to map the distribution of land surface temperatures associated with geothermal manifestations. The advantages of remote sensing are able to get information without having to go directly to the field with a large area, and it takes quick, so that the information can be used as an initial reference exploration activities. This study aimed to obtain the distribution of land surface temperature as a regional analysis of geothermal potential. The method of this research was a correlation of brightness temperature (BT) Landsat 8 with land surface temperature (LST) MODIS. The results of correlation analysis showed the R2 value was equal to 0.87, it shows that between BT Landsat 8 and LST MODIS has a very high correlation. Based on Landsat 8 LST imagery correction, the average of fumarole temperature and hot spring is 240C. Fumarole and hot spring are located in dense vegetation land which has average temperature around 26.90C. Land surface temperature Landsat 8 can not be directly used to identify geothermal potential, especially in the dense vegetation area, due to the existence of dense vegetation which can absorb heat energy released by geothermal surface feature. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13985 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 143-150 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13985/10885 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13986 2025-11-26T02:53:51Z ijreses:ART

DETECTION OF FOREST FIRE, SMOKE SOURCE LOCATIONS IN KALIMANTAN DURING THE DRY SEASON FOR THE YEAR 2015 USING LANDSAT 8 FROM THE THRESHOLD OF BRIGHTNESS TEMPERATURE ALGORITHM Kustiyo Ratih Dewanti Inggit Lolitasari Landsat 8 TIRS brightness temperature hotspots source of smoke Almost every dry season, there are large forest/land fires in several regions in Indonesia, especially in Kalimantan and Sumatra in the dry season of August to September 2015 a forest fire in 6 provinces namely West Kalimantan, Central Kalimantan, South Kalimantan, Riau, Jambi, and South Sumatra. Even some parties proposed that the Government of Indonesia declares them as a national disaster. The low-resolution remote sensing data have been widely used for monitoring the occurrence of forest/land fires (hotspots), and mapping of  burnt scars. The hotspot detection was done by utilizing the data of NOAA-AVHRR and MODIS data which have a lower spatial resolution (1 km). In order to increase the level of detail and accuracy of product information, this research is done by using Landsat 8 TIRS (Thermal Infrared Sensor) band which has a greater spatial resolution of 100 m. The purpose of this research is to find and to determine the threshold value of the brightness temperature of the TIRS data to identify the source of fire smoke. The data used is the Landsat 8 of several parts of Borneo during the period of 24 August to 18 September 2015 recorded by the LAPAN's receiving station. Landsat - 8 TIRS band was converted into brightness temperature in degrees Celsius, then dots in a region that is considered the source of the smoke if the temperature of each pixel in the region > 43oC, and given the attributes with the highest temperatures of the pixels in the region. The source of the smoke was obtained through visual interpretation of the objects in the multispectral Natural Color Composite (NCC) and True Color Composite (TCC) images. Analysis of errors (commission error) is obtained by comparing the temperature detected by TIRS band with a visual appearance of the source of the smoke. The result of the experiment showed that there were detected 9 scenes with high temperatures over 43oC from the 27 scenes Kalimantan Landsat 8 data, which include 153 sites. The accuracy (commission error) of identification results using temperature ≥ 51°C is 0%, temperature ≥ 47°C is 10%, and temperature ≥ 43°C is 30.5%. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13986 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); 151-160 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13986/10887 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13987 2025-11-26T02:53:51Z ijreses:BP

Back Pages IJReSES Vol. 12, No. 2(2015) Editorial Journal Back Pages IJReSES Vol. 12, No. 2(2015) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/13987 International Journal of Remote Sensing and Earth Sciences; Vol. 12 No. 2 (2015); I-IX 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13987/10888 Copyright (c) 2015 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13989 2025-11-26T02:28:44Z ijreses:ART

DEM GENERATION FROM STEREO ALOS PRISM AND ITS QUALITY IMPROVEMENT Bambang Trisakti Atriyon Julzarika Digital Elevation model Optical stereo data ALOS PRISM DEM fusion Bullseye Digital elevation mode (DEM) is important data for supporting many activities. One of DEM generation methods is photogrametry of optical stereo data based on image matching and collinear correlation. The problem of DEM from optical stereo data is bullseye due to low contrast in relatively flat area and cloud cover. The research purpose is to generate DEM from ALOS PRISM stereo data level 1B2R and improve the quality of the DEM. DEM was generated using Leica Photogrametry Suite (LPS) software. The study area is located in Sragen district and its vicinity. The process needed three dimension of Ground Control Point (GCP) XYZ, as input data for collinear correlation. Ground measurement was conducted using differential GPS to collect 30 GCPs that used for input (21 GCPs) and for accuracy evaluation (9 GCPs). The generated DEM has good detail (10 m), but it has bullseye which mostly occurred in relatively flat area. The quality improvement was carried out by combining the DEM with SRTM DEM (30 m) using DEM fusion method. Both DEMs were processed for geoids correction (EGM 2008), co-registration and histogram normalization. The fusion method was conducted by considering height error map (HEM) of each DEM. The quality of fused DEM was evaluated by comparing HEM, the number of bullseye, and vertical accuracy before and after the fusion. The result shows that DEM fusion can preserve detail information of the DEM and significantly reduce the bullseye (decreasing more than 66% of bullseye). It also shows the improvement (from 7.6 m to 7.3 m) of vertical accuracy. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13989 International Journal of Remote Sensing and Earth Sciences; Vol. 8 (2011); 41-48 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13989/10892 Copyright (c) 2011 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13996 2025-11-26T02:40:19Z ijreses:ART

DERIVING INHERENT OPTICAL PROPERTIES FROM MERIS IMAGERY AND IN SITU MEASUREMENT USING QUASI-ANALYTICAL ALGORITHM Wiwin Ambarwulan Widiatmaka Syarif Budhiman QAA MODTRAN MERIS Remote sensing reflectance Berau estuary water The  paper  describes inherent optical properties  (IOP)  of  the  Berau  coastal  waters  derived from in  situ measurements  and Medium  Resolution  Imaging  Spectrometer  (MERIS) satellite  data. Field  measurements  of optical  water,  total  suspended  matter  (TSM), and  chlorophyll-a  (Chl-a) concentrations were carried out during the dry season of 2007. During this periode, only four MERISdata were  coincided with in  situ measurements on 31 August  2007. The MERIS  top-of-atmosphere radiances were atmospherically corrected using the MODTRAN radiative transfer model. The in situ optical  measurement  have  been  processed  into apparent optical properties  (AOP) and sub  surface irradiance. The remote sensing reflectance of in situ measurement as well as MERIS data were inverted into  the  IOP  using quasi-analytical algorithm  (QAA).  The  result  indicated  that coefficient  of determination (R 2) of backscattering coefficients of suspended particles (bbp) increased with increasing wavelength,  however  the  R2 of  absorption  spectra  of  phytoplankton  (aph)  decreased  with  increasing wavelength. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13996 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 1-8 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13996/10891 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13997 2025-11-26T02:40:19Z ijreses:ART

LAND COVER CLASSIFICATION OF ALOS PALSAR DATA USING SUPPORT VECTOR MACHINE Katmoko Ari Sambodo Novie Indriasari Land cover ALOS-PALSAR support vector machine (SVM) classification Jambi South Sumatra Land cover classification is  one  of  the  extensive  used  applications in  the  field  of remote sensing. Recently, Synthetic Aperture Radar (SAR) data has become an increasing popular data source because  its  capability  to  penetrate  through  clouds,  haze,  and  smoke.  This  study  showed  on  an alternative  method  for  land  cover  classification  of  ALOS-PALSAR  data  using  Support  Vector Machine (SVM) classifier. SVM discriminates two classes by fitting an optimal separating hyperplane to the training data in a multidimensional feature space, by using only the closest training samples. In order  to  minimize  the  presence  of  outliers  in  the  training  samples  and  to  increase  inter-class separabilities,  prior  to  classification,  a  training  sample  selection  and  evaluation  technique  by identifying its position in a horizontal vertical–vertical horizontal polarization (HV-HH) feature space was applied. The effectiveness of our method was demonstrated using ALOS PALSAR data (25 m mosaic, dual polarization) acquired in Jambi and South Sumatra, Indonesia. There were nine different classes  discriminated:  forest,  rubber  plantation,  mangrove  &  shrubs  with  trees,  oilpalm  &  coconut, shrubs,  cropland,  bare  soil,  settlement,  and  water.  Overall  accuracy  of  87.79%  was  obtained,  with producer’s accuracies for forest, rubber plantation, mangrove & shrubs with trees, cropland, and water class were greater than 92%. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13997 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 9-18 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13997/10893 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/13998 2025-11-26T02:40:18Z ijreses:ART

MULTITEMPORAL LANDSAT DATA TO QUICK MAPPING OF PADDY FIELD BASED ON STATISTICAL PARAMETERS OF VEGETATION INDEX (CASE STUDY: TANGGAMUS, LAMPUNG) I Made Parsa Dede Dirgahayu NDVI Landsat paddy field maximum and minimum vegetation index Lampung Paddy  field  has  unique  characteristics  that  distinguish  it  from  other  plants.  Before it planting, paddy field is always flooded so that the appearance is dominated by water (aqueous phase). Within the  growth  of rice, field  conditions  will  be  increasingly  dominated  by  greenish rice  plants.While at the end, the rice plants will turn yellow indicating for harvesting. During flooding stage, the normalized difference vegetation index (NDVI) of pady field is negative. The negative value of NDVI of paddy field will ultimately increase to the maximum value at the maximum vegetative growth. TheNDVI of paddy field will decrease from generative phase until harvest and after harvest. The objective of  this  study  was  to  perform  the vegetation  index  analyses for multitemporal  Landsat  imagery of paddy field. The results showed that the difference of vegetation index values (maximum - minimum)of  paddy  field  were greater than the  difference  of vegetation index  values of  other land  uses.  Such differences values can be used as indicator to map land for rice. The evaluation results with reference data showed that the mapping accuracy (overall accuracy) was of 87.4 percent. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/13998 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 19-24 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/13998/10894 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14001 2025-11-26T02:40:17Z ijreses:ART

FISHPOND AQUACULTURE INVENTORY IN MAROS REGENCY OF SOUTH SULAWESI PROVINCE Yennie Marini Emiyati Teguh Prayogo Rossi Hamzah Bidawi Hasyim Fishpond aquaculture Optic remote sensing Satellite imaging radar SPOT-4 PALSAR Currently, fishpond aquaculture becomes an interesting business for investors because of its profit,  and  a  source  of  livelihood  for  coastal  communities.  Inventory  and  monitoring  of  fishpond aquaculture provide important baseline data to determine the policy of expansion and revitalization of the fishpond. The aim of this research was to conduct an inventory and monitoring of fishpond area inMaros regency of South Sulawesi province using Satellite Pour l’Observation de la Terre (SPOT -4) and Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Apeture Radar (PALSAR). SPOT image classification process was performed using maximum likelihood supervised classification  method and  the  density  slice  method  for ALOS  PALSAR.  Fishpond  area  from  SPOT data was  9693.58  hectares  (ha),  this  results  have  been  through  the  process  of  validation  and verification by the ground truth data. The fishponds area from PALSAR was 7080.5 Ha, less than the result  from  SPOT  data.  This  was  due  to  the  classification  result  of  PALSAR  data  showing someobjects around fishponds (dike, mangrove, and scrub) separately and were not combined in fishponds area  calculation.  Meanwhile, the  result  of  SPOT -4  image  classification  combined object  around fishponds area. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14001 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 25-35 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14001/10895 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14003 2025-11-26T02:40:17Z ijreses:ART

GROWTH RATE AND PRODUCTIVITY DYNAMICS OF ENHALUS ACOROIDES LEAVES AT THE SEAGRASS ECOSYSTEM IN PARI ISLANDS BASED ON IN SITU AND ALOS SATELLITE DATA Agustin Rustam Dietriech Geoffrey Bengen Zainal Arifin Jonson Lumban Gaol Risti Endriani Arhatin Enhalus acoroides growth rate productivity rate productivity ALOS Pari island Enhalus acoroides is the largest population of seagrasses in Indonesia. However, growth rate  and  productivity  analyses  of Enhalus  acoroides and  the use  of  satellite data to estimate its the productivity are still rare. The goal of the research was to analyze the growth rate, productivity rate,seasonal productivity of Enhalus acoroides in Pari island and its surroundings. The study was divided into two phases i.e., in situ measurments and satellite image processing. The field study was conducted to obtain the coverage percentage, density, growth rate, and productivity rate, while the satellite image processing was used to estimate the extent of seagrass. The study was conducted in August 2011 toJuly  2012  to  accommodate  all  four  seasons. Results  showed  that  the highest  growth  rate  andproductivity occurred during the transitional season from west Monsoon to the east Monsoon of 5.6cm/day  and  15.75  mgC/day, respectively.   While, the  lowest growth rate  and productivity occurred during  the  transition  from east  Monsoon  to  the  west  Monsoon of 3.93  cm/day  and  11.4  mgC/day, respectively. Enhalus  acoroides productivity reached its maximum during  the  west  Monsoon  at 1081.71 mgC/day/m2 and minimum during east Monsoon with 774.85 mgC/day/m2 . Based on ALOS data in 2008 and 2009, total production of Enhalus acoroides in the proximity of Pari islands reached its maximum occur during the west Monsoon (48.73 – 49.59 Ton C) and minimum during transitional season (16.4-16.69 Ton C). Potential atmospheric CO2 absorption by Enhalus acoroides in Pari island was estimated at the number 60.14 – 181.82 Ton C.   BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14003 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 37-46 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14003/10899 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14004 2025-11-26T02:58:36Z ijreses:FP

Front Pages IJReSES Vol. 11, No. 2(2014) Editorial Secretariat Front Pages IJReSES Vol. 11, No. 2(2014) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/14004 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); I-XV 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14004/10897 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14005 2025-11-26T02:58:36Z ijreses:ART

ANALYSIS OF SAR MAIN PARAMETERS FOR SAR SENSOR DESIGN ON LSA Muchammad Soleh Rahmat Arief Synthetic Aperture Radar (SAR) LAPAN Surveillance Aircraft (LSA) SAR parameters LAPAN plans to conduct a flight test of LSA (LAPAN Surveillance Aircraft). LSA STEMME-S15 is capable of carrying sensor payloads up to 160 kg that are mounted on both sides of the wings with altitude between 400-2000 m. LSA can be designed to perform imaging by using optical sensors and SAR (Synthetic Aperture Radar). Compared to imaging using optical sensors, SAR sensor has advantages such as it can operate all day and night, able to penetrate clouds, and able to see objects from side looking, while optical sensors generally see the object perpendicular to the ground. Therefore the use of SAR imaging technology can complement optical imaging technology. To design SAR system imagers on LSA, it is necessary to simulate the primary parameters SAR i.e. altitude and look angle of sensor, speed of LSA, SAR frequency and signals power shot to object to calculate the resolution of azimuth and ground range values that can be obtained. This SAR parameters simulation used MATLAB which have been designed with two approaches; the first approach where the SAR sensor is ideal and in which all the fundamental parameters (such as polarization, frequency, etc.) are used to generate the desired sensitivity and resolution of azimuth and ground range, and the second approach is where SAR sensor is designed in a limited antenna size (constraint case), with the assumption that the dimensions of the antenna and the average available power are fixed. The data used in this simulation is a pseudo-data obtained from LSA technical spesification and SAR sensor. The simulation results with the first approach shows that if LSA is flying at an altitude of 1000 m, with speed of 36.11 m/s, and SAR frequency of 5.3 GHz, then to get resolution of azimuth, slant range and ground range of 1 m, 1.2 m and 3 m, it is necessary to design the length and width of SAR antenna at 2 m and 13.5 cm, with look angle of 23.5 degrees. While the result of second approach simulation is that if LSA is flying on the same altitude and speed, on the same look angle and SAR frequency, with a particular design of antenna length and width of 2 m and 13.5 cm, then azimuth, slant range and ground range resolution of 1 m, 1.87 and 4.79 m will be obtained. Form both simulations, it can be concluded that limited SAR system on LSA, especially on the technical aspects of mounting and space as in the simulation with the second approach, will produce slightly lower slant range and ground range resolution when compared with SAR system in the first simulation. This shows that space limitation on LSA will affect decrease the value of spatial ground range resolution. The simulation results are expected to be inputs on designing SAR imaging system on LSA. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14005 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 85-96 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14005/10898 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14006 2025-11-26T02:58:36Z ijreses:ART

A TWO-STEPS RADIOMETRIC CORRECTION OF SPOT-4 MULTISPECTRAL AND MULTITEMPORAL FOR SEAMLESS MOSAIC IN CENTRAL KALIMANTAN Kustiyo Ratih Dewanti Inggit Lolita Sari Radiometric correction Reflectance Viewing angle This research analyzed the radiometric correction method using SPOT-4 imageries to produce the same reflectance for the same land cover. Top of Atmosphere (TOA) method was applied in previous radiometric correction approach, this TOA approach was upgraded with the reflectance effect from difference satellite viewing angle. The 250 scene of Central Kalimantan SPOT-4 imageries from 2006 until 2012 with varies viewing angle was used. This research applied two-step approaches, the first step is TOA correction, and the second step is normalization using a linear function of reflectance and satellite viewing angle. Gain and offset coefficient of this linear function was calculated using an iterative approach to producing the same reflectance in the forest area. The target of iterative processed is to minimize the standard deviation of a digital number from a forest area in the selected region. The result shows that the standard deviation of a digital number from a forest area in the two steps approach are 8.6, 16.5, and 16.8 for band 1, band 3 and band 4. These values are smaller compared with the standard deviation of digital number result from TOA approach are 15.0, 28,3 and 34.7 for band 1, band 3 and band 4.  Decreasing the standard deviation shows the homogeneity of forest reflectance that could be seen in the seamless result. This algorithm can be applied for making seamless SPOT-4 mosaic whole of Indonesia. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14006 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 97-104 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14006/10901 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14007 2025-11-26T02:40:16Z ijreses:ART

DEVELOPMENT OF LAND MOISTURE ESTIMATION MODEL USING MODIS INFRARED, THERMAL, AND EVI TO DETECT DROUGHT AT PADDY FIELD Dede Dirgahayu Domiri MODIS reflectances EVI LST land moisture paddy The drought phenomena often occurs in summer season at paddy field of Java island. The drought phenomena causes decrease in rice production. This research was aimed to develop a model of land  moisture (LM) estimation  at  agricultural field,  especially  for  paddy  field  based  on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data which has seven reflectance and two thermal bands. The method used in this study included data correction, advance processing of MODIS data  (land indices  transformation),  extraction  of  land  indices  value  at  location  of  field  survey,  and regression  analysis  to  make  the  best  model  of  land  moisture  estimation. The  result  showed that reflectance of 2nd channel (NIR) and rasio of Enhanced Vegetation Index (EVI) with Land Surface Temperature (LST) had high correlation with surface soil moisture (% weight) at 0 – 20 cm depth with formula: LM = 15.9*EVI/LST – 0.934*R2 – 16.8 (SE=9.6%; R2 =76.2%). Based on the model, land  moisture  was  derived  spatially at the  agricultural field,  especially at paddy  field to  detect  andmonitor drought events. Information of land moisture can be used as an indicator to detect drought condition and early growing season of paddy crop  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14007 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 47-54 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14007/10900 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14009 2025-11-26T02:40:16Z ijreses:ART

DETERMINATION OF STRATIFICATION BOUNDARY FOR FOREST AND NON FOREST MULTITEMPORAL CLASSIFICATION TO SUPPORT REDD+ IN SUMATERA ISLAN Tatik Kartika Inggit Lolita Sari Bambang Trisakti Muti temporal classificatioon stratification zone Fores CVA Landsat Quick Bird Multi-temporal classification is a method to determine forest and non-forest by considering a missing data, such as cloud cover using correlations value from the other data. This circumstances is frequently occured in a tropical area such as in Indonesia. To gain an optimum result of forest and non-forest classification, it is needed a stratification zone that describes the difference of vegetation condition due to different of vegetation type, soil type, climate, and land use/cover associations. This stratification zone will be useful to indicate the different biomass volume relating to carbon content for supporting the REDD+ project. The objective of this study was to determine stratification boundary by performing multi temporal  classification in Sumatera Island  using  Landsat  imagery  in  25 meter resolution and Quick Bird imagery in 0.6 meter. Rough stratification was made by considering land use/cover, DEM and landform, using visual interpretation of moderate spatial resolution of satellitedata. High spatial resolution data was also provided in some areas to increase the accuracy level of stratification zone. The stratification boundary was evaluated using forest classification indices, and it was  redetermined  to  obtain  the  final  stratification  zone. The  indices was generated  by CanonicalVariate Analysis (CVA) method, which was depend on training samples of forest and non-forest in each previous stratification zone. The amount of indices used in each zone were two or three indices depending on the separability of the forest and non-forest classification. The suitable indices used in each  zone  described forest  as  100, non-forest  as  0, and  uncertain  forest between  50-99. The  result showed 20 stratification zones in Sumatera spreading out in coastal, mountain, flat area, and group of small islands. The stratification zone will improve the accuracy of forest and non-forest classification result and their change based on multi temporal classification. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14009 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 55-64 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14009/10903 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14010 2025-11-26T02:58:35Z ijreses:ART

EVALUATION OF MANGROVE DAMAGE LEVEL BASED ON LANDSAT 8 IMAGE Gathot Winarso Anang D Purwanto Mangrove new index mangrove degradation remote sensing Monitoring of mangrove damage in Java requires special attention because the mangrove vegetation has been under pressure from various other land uses which are considered more productive. This paper applied quick-mangrove-damage-detection technique using Landsat 8. The purpose of this study is to develop mangrove damage identification algorithm using Landsat 8. The findings from field survey in Segara Anakan-Cilacap show that major mangrove logging generates the growth of minor mangrove, specifically Derris and Acanthus type; the minor mangrove cover area is categorized as high density based on NDVI value. The index use does not meet the actual condition in the field. This study proposes a new index as mangrove quality indicator. The new proposed mangrove index is derived from 2 bands that could differentiate mangrove vegetation where different digital number of two bands is higher from mangrove forest than non-mangrove forest. That phenomenon is caused the low of SWIR spectral on mangrove forest due to absorption by wet soil below the mangrove forest where flooded in high tide.  The new mangrove index is formulated as (NIR – SWIR / NIR x SWIR) x 10000. The new mangrove index has good correlation with density of major mangrove in the field, and also good correlation with mangrove degradation map. Mangrove index has been functioning properly and can be applied in Segara Anakan, Cilacap and potentially can be applied in other locations. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14010 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 105-116 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14010/10902 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14012 2025-11-26T02:40:15Z ijreses:ART

UTILIZATION OF MULTI TEMPORAL SAR DATA FOR FOREST MAPPING MODEL DEVELOPMENT Bambang Trisakti Rossi Hamzah Forest mapping multi temporal ALOS PALSAR threshold LANDSAT Utilization  of  optical  satellite  data  in  tropical  region  was  limited to  free  cloud  cover. Therefore, Synthetic  Aperture  Radar  (SAR)  becomes  an  alternative  solution  for  forest  mapping  in Indonesia due to its capability to penetrate cloud. The objective of this research was to develop a forestmapping model based on multi temporal SAR data. Multi temporal ALOS PALSAR data for 2007 and 2008  were  used  for  forest  mapping,  and  one  year  mosaic  LANDSAT  data  in  2008  was  used  as references  data  to  obtain  training  sample  and  to  verify  the  final  forest  classification.  PALSAR processing was done using gamma naught conversion and Lee filtering. Samples were made in forest and  water  area, and  the  statistical  values  of the  each  object  were  calculated.  Some  thresholds  were determined  based  on  the  average  and  standard  deviation,  and  the  best  threshold  was  selected  to classify forest and water in 2008. It was assumed that forest could not change in 1-2 years period. The classification of forest, water, and the change were combined to produce final forest in 2008, and then it was visually verified with mosaic LANDSAT in 2008. The result showed that forest, water, and the change  could  be  well  classified  using  threshold  method.  The  forest  derived  from  PALSAR  was visually  consistent  with  forest  appearance  in  LANDSAT  and  forest  produced  from  INCAS.  It  has better performance than forest derived from INCAS for separating oil palm plantation from the forest. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14012 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 1 (2013); 65-74 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14012/10905 Copyright (c) 2013 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14013 2025-11-26T02:28:43Z ijreses:ART

APPLICATION OF SATELLITE MICROWAVE REMOTE SENSING DATA TO SIMULATE MIGRATION PATTERN OF ALBACORE TUNA Mukti Zainuddin Katsuya Saitoh Sei-Ichi Saitoh Kinesis model Microwave remote sensing SST Albacore tuna Migration pattern To simulate migration pattern of albacore tuna in the western North Pacific Ocean during the winter period, a kinesis model driven by high accuracy of sea surface temperature (SST) maps was used. The SST data were derived from the Tropical Rainfall Measuring Mission/TRMM Microwave Imager (TRMM/TMI). Simulations showed that albacore tuna aggregated in areas of thermal preference indicated by contour line of 20°C SST. Results are compared with empirical observation maps of albacore tuna fishing locations determined from longline fishing operation during the same time periods. Albacore tuna distributions along thermal fronts generating from Simulations were fairly consistent with fishing data especially during November-January, although seasonal variations in surface temperature ranges occupied suggest that additional oceanographic factors are involved particularly during February-March. Simulations and empirical data had similar temperature distributions at approximately 18-21°C and one-sample Kolmogorov-Smirnov test reinforced the result performance. These results suggest that kinesis model driven by satellite microwave remote sensing is one of effective mechanisms for describing migration pattern of tuna in the open ocean environment. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14013 International Journal of Remote Sensing and Earth Sciences; Vol. 8 (2011); 49-56 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14013/10907 Copyright (c) 2011 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14014 2025-11-26T02:58:35Z ijreses:ART

EVALUATION OF SPOT-5 IMAGE FUSION USING MODIFIED PAN-SHARPENING METHODS Sukentyas Estuti Siwi Image Fusion Pan-sharpening method SPOT-5 UIQI Image fusion, commonly known as pan-sharpening, is a method that combines two data: a panchromatic image that has geometric detail information with the highest spatial resolution and multi-spectral image that has the highest color information but with the lowest resolution. Pan-sharpeningis very important for various remote sensing applications, such as to improve the image classification, to change the detection using temporal data, to increase the geometric, image segmentation, and to improve the visibility of certain object that does not appear on certain data. This study aims to compare the existing pan-sharpening methods such as Brovey, Brovey modification using green and red band, Gram-Schmidt, HPF, Multiplicative, and SFIM.The quality of the pan-sharpening result should be evaluated, this study used Universal Image Quality Index (UIQI/Q index); this evaluation methodgives the opportunity to choose which method is best to provide the most similar spectral information with the original multispectral image. A pan-sharpening qualitative analysis shows that there has been a sharpening process on all pan-sharpening images. Based on spectral visualization (color display), several pan-sharpening methods such as HPF multiplicative method provides brighter colorsand Brovey transformation method displays dark colors. Gram-Schmidt method also provides a different color from the original multispectral image. A pan-sharpening quantitative analysis shows that the best pan-sharpening method with UIQI value> 0.9 is Brovey modification using green and red band. This is due to the green band (500-590 nm) and the red band(610-680 nm) wavelength are in the panchromatic band (480-710 nm) of the SPOT-5 Data.  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14014 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 117-126 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14014/10906 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14015 2025-11-26T02:58:35Z ijreses:ART

THE USE OF HIGH RESOLUTION IMAGES TO EVALUATE THE EVENT OF FLOODS AND TO ANALYSIS THE RISK REDUCTION CASE STUDY: KAMPUNG PULO, JAKARTA M. Rokhis Khomarudin Suwarsono Dini Oktavia Ambarwati Gunawan Prabowo Flood risk Kampung Pulo High-resolution remote sensing UAV1 The flood hit Kampung Pulo region in almost every year. This disaster has caused the evacuation of some residents in weeks. Given the frequency of occurrence is quite high in the region it is necessary to do a study to support disaster risk reduction. This study aimed to evaluate the incidence of flooding that occurred in Kampung Pulo in terms of topography, river conditions, characteristics of the building, and socioeconomic conditions. Methods of study include geomorphology analysis, identification of areas of stagnant, the estimated number of people exposed, the estimation of socio-economic conditions of the population, as well as determining the location of an evacuation. The data used is high-resolution remote sensing imagery is QuickBird and SPOT-6. It also used the results of aerial photography using Unmanned Aerial Vehicle (UAV). Aerial photography was conducted on January 18, 2013, which is when the serious flooding that inundated almost the entire region of Kampung Pulo. Information risk level of buildings and population resulting from this study were obtained by using GIS. The results obtained from this study can be used to develop recommendations and strategies for flood mitigation in Kampung Pulo, Jakarta. One of them is the determination of the location for vertical evacuation plan in the affected areas.   BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14015 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 127-136 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14015/10908 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14016 2025-11-26T03:17:04Z ijreses:ART

COMBINATION OF SPECKLE DIVERGENCE AND NEIGHBORHOOD ANALYSIS TO CLASSIFY SETTLEMENT FROM TERASAR-X DATA M. Rokhis Khomarudin Agung Indrajit Settlements areas Speckle divergence Neighborhood SAR Abstract.  The  objectives  of  this  research  were  to  develop  and  improve  methods  for determination  of  settlements  area  with  focus  on  synthetic  aperture  radar  (SAR)  data. Remote  sensing  settlement  classification  has  made  great  progress,  both  for  optical  and radar  data  as  well  for  their  fusion.  Yet,  in  radar  imagery,  settlement  classification  still contains  some  problems.  Several  studies  on  application  of  radar  imagery  have  been conducted  using  techniques  such  as  textural  analysis,  multi-temporal  analysis,  statistical model,  spatial  indexes,  and  object-based  classification.  Most  of  the  development  methods have several problems in the specific area especially in the tropical country. Several studies also  showed  that  settlement  classification  accuracies  were  just  below  60%.    This  was  not sufficient    enough  to  classify  settlement  areas  using  SAR  imagery.  Therefore,  in  this research, we proposed a new method i.e., the combination of the speckle divergence and the neighborhood  analysis.  The  proposed  method  was  applied  to  classify  settlement  area  in Cilacap  and  Padang  Districts  of  Indonesia.  The  results  showed  that  the  proposed  method produced a good accuracy i.e., 85.5% for Cilacap Districts and 78.1% for Padang Districts.  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14016 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 1 (2012); 1-12 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14016/10909 Copyright (c) 2012 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14018 2025-11-26T02:58:35Z ijreses:ART

ANALYSIS OF SEA SURFACE HEIGHT ANOMALY CHARACTERISTICS BASED ON SATELLITE ALTIMETRY DATA (CASE STUDY: SEAS SURROUNDING JAVA ISLAND) Sartono Marpaung Wawan K. Harsanugraha Altimetry Zonal Anomaly Characteristics and Sea Surface Height Sea surface height anomaly is a oceanographic parameter that has spatial and temporal variability. This paper aims to determine the characters of sea surface height anomaly in the south and north seas of Java Island. To find these characters, a descriptive analysis of monthly anomaly data is performed spatially, zonally and temporally. Based on satellite altimetry data from 1993 to 2010, the analysis shows that the average of sea surface height anomaly varies, ranging from -15 cm to 15 cm. Spatially and zonally, there are three patterns that can be concidered as sea surface height anomaly characteristics: anomaly is higher in coastal areas than in open seas, anomaly is lower in coastal areas than in open seas and anomaly in coastal area is almost the same as in open seas. The first and second patterns occur in the south and north seas of Java Island. The third pattern occurs simultaneously in south and north seas of Java Island. Characteristics of temporal anomaly have a sinusoidal pattern in south and north seas of Java Island. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14018 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 137-142 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14018/10910 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14019 2025-11-26T03:17:04Z ijreses:ART

LAND COVER CLASSIFICATION ALOS AVNIR DATA USING IKONOS AS REFERENCE Bambang Trisakti Dini Oktavia Ambarwati ALOS-AVNIR Maximum likelihood enhanced neighbor classifier Confusion matrix Abstract.  Advanced Land Observation Satellite (ALOS) is a Japanese satellite equipped with 3  sensors  i.e.,  PRISM,  AVNIR,  and  PALSAR.  The  Advanced  Visible  and  Near  Infrared Radiometer (AVNIR) provides multi spectral sensors ranging from Visible to Near Infrared to observe  land  and  coastal  zones.  It  has  10  meter  spatial  resolution,  which  can  be  used  to map  land  cover  with  a  scale  of 1:25000.  The  purpose  of  this  research  was  to  determineclassification  for  land  cover  mapping  using  ALOS  AVNIR  data.  Training  samples  were collected  for  11  land  cover  classes  from  Bromo  volcano  by  visually  referring  to  very  high resolution  data  of  IKONOS  panchromatic  data.  The  training  samples  were  divided  into samples  for  classification  input  and  samples  for  accuracy  evaluation.  Principal  component analysis (PCA) was conducted for AVNIR data, and the generated PCA bands were classified using Maximum Likehood  Enhanced Neighbor method. The classification result was filtered and  re-classed  into  8  classes.  Misclassifications  were  evaluated  and  corrected  in  the  post processing  stage.  The  accuracy  of  classifications  results,  before  and  after  post  processing, were  evaluated  using  confusion  matrix  method.  The  result  showed  that  Maximum Likelihood  Enhanced  Neighbor  classifier  with  post  processing  can  produce  land  cover classification  result  of  AVNIR  data  with  good  accuracy  (total  accuracy  94%  and  kappa statistic 0.92).  ALOS AVNIR has been proven as a potential satellite data to map land cover in the study area with good accuracy. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14019 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 1 (2012); 13-20 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14019/10911 Copyright (c) 2012 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14020 2025-11-26T02:58:35Z ijreses:ART

UTILIZATION OF SAR AND EARTH GRAVITY DATA FOR SUB BITUMINOUS COAL DETECTION Atriyon Julzarika Kuncoro Teguh Setiawan SAR and Earth Gravity Data sub bituminous lignite coal and peat coal height model Remote sensing data can be used for geological and mining applications, such as coal detection. Coal consists of five classes of Anthracite, Bituminous, Sub-Bituminous, Lignite coal and Peat coal. In this study, the type of coal that is discussed is Sub bituminous, Lignite coal, and peat coal. This study aims to detect potential sub bituminous using Synthetic Aperture Radar (SAR) data, and earth gravity. One type of remote sensing data to detect potential sub bituminous, lignite coal and peat coal are SAR data and satellite data Geodesy. SAR data used in this study is ALOS PALSAR. SAR data is used to predict the boundary between Lignite coal with Peat coal. The method used is backscattering. In addition to the SAR data is also used to make height model. The method used is interferometry. Geodetic satellite data is used to extract the value of the earth gravity and geodynamics. The method used is physical geodesy. Potential sub-bituminous coal can be known after the correlation between the predicted limits lignite coal-peat coal by the earth gravity, geodynamics, and height model. Volume predictions of potential sub bituminous can be known by calculating the volume using height model and transverse profile test. The results of this study useful for preliminary survey of geological in mining exploration activities. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14020 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 143-152 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14020/10912 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14022 2025-11-26T02:39:46Z ijreses:ART

GEOSTATISTICAL TEST USING LEAST SQUARE ADJUSTMENT COMPUTATION TO OBTAIN THE REDUCTION PARAMETER FOR DSM TO DEM CONVERSION (Study of Case: Cilacap, Indonesia) Atriyon Julzarika 3D Model ALOS images DEM DSM Least Square Adjustment Abstract. ALOS satellite is one of the natural resources satellites that can be used for 3Dmodel applications. The problems of 3D model generation based on satellite imagery arethe model always in Digital Surface Model (DSM), not in Digital Elevation Model (DEM).The reference system of 3D model that are produced by ALOS satellite image is still assurface for z axis, whereas x axis and y axis has been closed to 2D reference system insome certain datum and system of map projection. Therefore, it needs a research to observethe accuracy and the precision of ALOS satellite data using a least square adjustment inparameter methods. The results of this research will be used as a reference for next researchto find a way for changing DSM from ALOS satellite image to be DEM automatically. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14022 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 1-11 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14022/10913 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14023 2025-11-26T03:17:03Z ijreses:ART

COMPARISON OF THE VEGETATION INDICES TO DETECT THE TROPICAL RAIN FOREST CHANGES USING BREAKS FOR ADDITIVE SEASONAL AND TREND (BFAST) MODEL Yahya Darmawan Parwati Sofan NDVI EVI BFAST method NDFI Forest Changes Indonesia Remotely  sensed  vegetation  indices  (VI)  such  as  the  Normalized  Difference Vegetation Index (NDVI) are increasingly used as a proxy indicator of the state and condition of  the  land  cover/vegetation,  including  forest.  However,  the  Enhanced  Vegetation  Index (EVI)  on  the  outcome  of  forest  change  detection  has  not  been  widely  investigated.  We compared the influence of using EVI and NDVI on the number and time of detected changes by applying Breaks for Additive Seasonal and Trend (BFAST), a change detection algorithm. We  used  MODIS  16-day  NDVI  and  EVI  composite  images  (April  2000-April  2012)  of  three pixels  (pixels  352,  378,  and  380)  in  the  tropical  peat  swamp  forest  area  around  the  flux tower of  Palangka Raya, Central Kalimantan.  The results  of  BFAST method were compared to  the  Normalized  Difference  Fraction  Index  (NDFI)  maps  and  the  maps  were  validated  by the  hotspot  of  the  Infrastructure  and  Operational  MODIS-Based  Near  Real-Time  Fire(INDOFIRE).  Overall,  the  number  and  time  of  changes  detected  in  the  three  pixels  differed with both time series data  because of the  data quality due to the cloud cover.  Nonetheless, we  found  that  EVI  is  more  sensitive  than  NDVI  for  detecting  abrupt  changes  such  as  the forest fires of August 2009-October 2009 that occurred in our study area and it was verified by  the  NDFI  and  the  hotspot  data.  Our  results  demonstrated  that  the  EVI  for  forest monitoring in the tropical peat swamp forest area which is covered by intense cloud cover is better  than  that  NDVI.  Nonetheless,  further  research  with  improving  spatial  resolution  of satellite images for application of NDFI is highly recommended.  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14023 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 1 (2012); 21-34 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14023/10915 Copyright (c) 2012 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14024 2025-11-26T02:58:34Z ijreses:ART

AN EFFECTIVE INFORMATION SYSTEM OF DROUGHT IMPACT ON RICE PRODUCTION BASED ON REMOTE SENSING Rizatus Shofiyati Wataru Takeuchi Soni Darmawan Parwati Sofan Drought Rice production Satellite remote sensing Information system Long droughts experienced in the past are identified as one of the main factors in the failure of rice production. In this regard, special attention to monitor the condition is encouraged to reduce the damage. Currently, various satellite data and approaches can withdraw valuable information for monitoring and anticipating drought hazards. MODIS, MTSAT, AMSR-E, TRMM and GSMaP have been used in this activity. Meteorological drought index (SPI) of the daily and monthly rainfall data from TRMM and GSMaP have analyzed for last 10-year period. While, agronomic drought index has been studied by observing the character of some indices (EVI, VCI, VHI, LST, and NDVI) of sixteen-day and monthly MODIS, MTSAT, and AMSR-E data at a period of 4 years. Network for satellite data transfer has been built between LAPAN (data provider), ICALRD (implementer), IAARD Cloud Computing, University of Tokyo (technical supporter), and NASA. Two information system have been developed: 1) agricultural drought using the model developed by LAPAN, and 2) meteorological drought developed by Takeuchi (University of Tokyo).The accuracy study using quantitative method for LAPAN model uses VHI is 60% (Kappa 0,44), while that of for University of Tokyo model uses qualitative model with KBDI value 500-600 shows an early indication of  drought for paddy field. This will help the government or field officers in rapid management actions for the indicated drought area.This paper describes the implementation and dissemination of drought impact monitoring model on the area of rice production center using an integrated information system satellite based model. The two developed information systems are effective for spatially dissemination of drought information. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14024 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); 153-162 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14024/10914 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14029 2025-11-26T02:58:34Z ijreses:BP

Back Pages IJReSES Vol. 11, No. 2(2014) Editorial Secretariat Back Pages IJReSES Vol. 11, No. 2(2014) BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://ejournal.brin.go.id/ijreses/article/view/14029 International Journal of Remote Sensing and Earth Sciences; Vol. 11 No. 2 (2014); I-IX 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14029/10917 Copyright (c) 2014 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14036 2025-11-26T03:17:03Z ijreses:ART

INDENTIFYING PATTERNS OF SATTELITE IMAGERY USING AN ARTIFICIAL NEURAL NETWORK Iskhaq Iskandar Azhar K. Affandi Dedi Setiabudidaya Muhammad Irfan Wijaya Mardiansyah Fadli Syamsuddin Downwelling Monsoon Self-organizing map Satellite imagery Upwelling An artificial neural network analysis based on the self-organizing map (SOM) was used to examine patterns of satellite imagery. This study used 3 × 4 SOM array to extract patterns of satellite-observed chlorophyll-a (chl-a) along the southern coast of the Lesser Sunda Islands from 1998 to 2006. The analyses indicated two characteristic spatial patterns, namely the northwest and the southeast monsoon patterns. The northwest monsoon pattern was characterized by a low chl-a concentration. In contrast, the southeast monsoon pattern was indicated by a high chl-a distributed along the southern coast of the Lesser Sunda Islands. Furthermore, this study demonstrated that the seasonal variations of those two patterns were related to the variations of winds and sea surface temperature (SST). The winds were predominantly southeasterly (northwesterly) during southeast (northwest) monsoon, drived offshore (onshore) Ekman transport and produced upwelling (downwelling) along the southern coasts of the Lesser Sunda Islands. Consequently, upwelling reduce dSST and helped replenish the surface water nutrients, thus supporting high chl-a concentration. Finally, this study demonstrated that the SOM method was very useful for the identifications of patterns in various satellite imageries. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14036 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 1 (2012); 35-40 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14036/10920 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14038 2025-11-26T03:17:03Z ijreses:ART

ESTIMATION OF RADIOMETRIC PERFORMANCE OF ELEKCTRO-OPTICAL IMAGING SENSOR OF LOW EARTH EQUATORIAL ORBIT LAPAN SATTELITE Ahmad Maryanto Andy Indradjad Dinari Nikken Sulastrie Sirin Ayom Widipaminto image irradiance solar zenith angle imager LAPAN satellite Study of spectro-radiometric performance of electro-optical imager which is planned to be launched on low earth equatorial orbit LAPAN satellite was conducted through simulative calculation of image irradiance and its associated generated voltage at the image detector output. Simulative calculation was applied to three scenarios of selected spectral bands. Those spectral bands were selected spectra (1), which consisted of spectral bands B = (390-540 and 790-900) nm, G = (470-610 and 700-900 ) nm, and R = (590-650 and 650-900) nm; selected spectra (2) consisted of B1 = (390-540) nm, G1 = (470-610) nm, and R1 = (590-650) nm; and selected spectra (3) consisted of B1(Green) = (525-605) nm, B2(Red) = (630-690) nm, and B3(NIR) = (750-900) nm, on three scenarios of optical aperture or f-number (N) 2.8, 4.0, and 5.6. Green grasses, dry grasses, and conifers were examples of the imaged target, chosen as representation of vegetations. Kodak KLI-8023 was used as the optical detector. The integration time was assumed 3 miliseconds which correspond to about 20 m ground sampling distance (GSD). Solar zenith angle were varying from 90ï‚° (early morning) to 0ï‚° (solar noon). The results showed that option (3) of selected spectra, as proposed for pushbroom imager of LAPAN satellite, was relatively accepted to be implemented and complemented with f-number 4.0 of optical system used. Whereas simulation RGB color displayed composed by R = B2(Red), G = B3(NIR), B = B1(Green) also showed a greenish color sense as expected for vegetation imaged target. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14038 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 1 (2012); 41-52 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14038/10921 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14039 2025-11-26T03:17:03Z ijreses:ART

RED TIDE DETECTION USING Seawifs STANDARD CHOLOROPHYLL-a ALGORITHM IN SOUTHEAST KOREAN WATERS Gathot Winarso Cochlodinium polykrikoides Chlorophyll-a SeaWiFS Red tide Cochlodinium polykrikoides red tides have occurred in summer every year at coastal waters of the South Korea. Chlorophyll-a concentration data estimated from ocean color satellite SeaWiFS (Sea-viewing Wide Field-of-view Sensor) were used to detect the red tide in this study. The high value of chlorophyll-a concentration used to detect red tide was analyzed and compared with red tide map produced by National Fisheries Research and Development Institute of Korea (NFRDI). Based on SeaWiFS data and NFRDI red tide map, it was found that high chlorophyll-a concentration of ≥ 5 mg/m3in SeaWiFS images corresponded to the red-tide occurrence with some limitations. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14039 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 1 (2012); 53-62 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14039/10922 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14040 2025-11-26T03:17:03Z ijreses:ART

ORTORECTIFICATION OF SPOT-4 DATA USING RATIONAL POLYNOMIAL COEFFICIENTS Danang Surya Candra Orthorectification Rational polynomial coefficient SPOT-4 Orthorectification of satellite imagery can be done in two ways i.e., rigorous sensor model and the approximation model of the satellite’s orbit. Dependence on physicalparameters, to make rigorous sensor model is more complicated and difficult to apply. The approximation model can be either Rational Polynomial Coefficients (RPC) model or parallel projection system. RPC is a mathematical model which is not depends on the sensor. It is used to improve the positioning accuracy when the parameter of the physical sensor model is unknown. This study assessed orthorectification of SPOT-4 using the RPC model with 7 coefficients. Root Mean Square Error (RMSE) of GCPs obtained from the study was less than 1 pixel. RPC did not depend on physical and satellite orbit parameters. Thus the RPC was simpler and easier to apply. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14040 International Journal of Remote Sensing and Earth Sciences; Vol. 9 No. 1 (2012); 63-74 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14040/10923 Copyright (c) 2012 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14051 2025-11-26T02:39:46Z ijreses:ART

UTILIZATION OF IKONOS IMAGE AND SRTM AS ALTERNATIVE CONTROL POINT REFERENCE FOR ALOS DEM GENERATION Bambang Trisakti Gathot Winarso Atriyon Julzarika ALOS PRISM CP DEM generation GCP IKONOS SRTM Abstract. Digital Elevation Model (DEM) was generated from Advanced LandObservation Satellite - The Panchromatic Remote-Sensing Instrument for Stereo Mapping(ALOS PRISM) stereo data using image matching and collinear correlation based on LeicaPhotogrametry Suite (LPS) software. The process needs three dimension of Ground ControlPoint (GCP) or Control Point (CP) XYZ as input data for collinear correlation to determineexterior orientation coefficient. The main problem of the DEM generation is the difficultyto obtain the accurate field measurement GCP in many areas. Therefore, another alternativeCP sources are needed. The aim of this research was to study the possibility of (IKONOS)image and Shuttle Radar Topography Mission (SRTM) X-C band to be used as CPreference for ALOS PRISM DEM generation. The study area was Sragen and Bandungregion. The DEM of each study area was generated using 2 methods: generated using fieldmeasurement GCPs taken by differential GPS and generated using CPs from IKONOSimage (XY coordinat) and SRTM for (Z elevation). The generated DEMs were compared.The accuracy of both DEMs were evaluated using another field measurement GCPs. Theresult showed that the generated DEM using CPs from IKONOS and SRTM X-C hadrelatively same height pattern and height distribution along transect line with the DEMusing GCPs. The absolute accuracy of the DEM using CPs was about 60% - 80% lessaccuracy comparing to the DEM using GCPs. This research showed that IKONOS imageand SRTM X-C band can be considered as good alternative CP source to generate highaccuracy DEM from ALOS PRISM stereo data. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14051 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 12-23 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14051/10924 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14054 2025-11-26T02:39:46Z ijreses:ART

ESTIMATION OF DATA MEMORY CAPACITY FOR CIRCULARLY POLARIZED SYNTHETIC APERTURE RADAR ONBOARD UNMANNED AERIAL VEHICLE PLATFORM (CP-SAR UAV) P. Rizki Akbar J.T. Sri Sumantyo V.C.Koo H.Kuzel synthetic aperture radar circular polarization 3-dB axial ratio CP-SAR unmanned aerial vehicle Previously only linear polarization is widely used in the Synthetic Aperture Radar(SAR) system onboard spaceborne and airborne platforms. In such linearly polarized SAR(LP-SAR) systems, Faraday rotation in the ionosphere and platform posture will contribute tothe system noise. Therefore to improve this situation, currently a novel Circularly PolarizedSynthetic Aperture Radar (CP-SAR) sensor is developed in Microwave Remote SensingLaboratory, Chiba University. Moreover, from this research, a new backscattering data basedon circularly polarized wave in the remote sensing field can be obtained. As an early stage ofthe development of this CP-SAR sensor, we built an Unmanned Aerial Vehicle (UAV)platform for testing CP-SAR sensor capabilities. In this paper, we describe the novel CP-SARsensor and the method to design CP-SAR UAV especially in estimating the requirement ofdata memory capacity. Also a smaller antenna is possible to be implemented since the 3-dBaxial ratio on antenna characteristic becomes the main parameter in this new CP-SARtechnique. Hence, a compact CP-SAR sensor onboard a small and low cost spaceborneplatform yielding a high accuracy SAR image data can be realized in the near future. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14054 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 24-35 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14054/10926 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14059 2025-11-26T02:39:46Z ijreses:ART

MODIFICATION OF INPUT IMAGES FOR IMPROVING THE ACCURACY OF RICE FIELD CLASSIFICATION USING MODIS DATA I Wayan Nuarsa Fumihiko Nishio Chiharu Hongo rice field mapping modified classification temporal analysis Modis The standard image classification method typically uses multispectral imageryon one acquisition date as an input for classification. Rice fields exhibit high variability inland cover states, which influences their reflectance. Using the existing standard method forrice field classification may increase errors of commission and omission, thereby reducingclassification accuracy. This study utilised temporal variance in a vegetation index as amodified input image for rice field classification. The results showed that classification ofrice fields using modified input images provided a better result. Using the modifiedclassification input improved the correspondence between rice field area obtained from theclassification result and reference data (R2 increased from 0.2557 to 0.9656 for regencylevelcomparisons and from 0.5045 to 0.8698 for district-level comparisons). Theclassification accuracy and the estimated Kappa value also increased when using themodified classification input compared to the standard method, from 66.33 to 83.73 andfrom 0.49 to 0.77, respectively. The commission error, omission error, and Kappa variancedecreased from 68.11 to 42.36, 28.48 to 27.97, and 0.00159 to 0.00039, respectively, whenusing modified input images compared to the standard method. The Kappa analysisconcluded that there are significant differences between the procedure developed in thisstudy and the standard method for rice field classification. Consequently, the modifiedclassification method developed here is significant improvement over the standardprocedure. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14059 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 36-52 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14059/10928 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14060 2025-11-26T02:39:46Z ijreses:ART

ESTIMATION OF TIDAL ENERGY DISSIPATION AND DIAPYCNAL DIFFUSIVITY IN THE INDONESIAN SEAS I Wayan Gede Astawa Karang Fumihiko Nishio Takahiro Osawa Baroclinic energy conversion barotropic tides diapycnal diffusivity Indonesian Seas internal waves tidal elevations The Indonesian Seas separating the Indian Ocean from the West Pacific Oceanare representative regions of strong tidal mixing in the world oceans. In the present study,we first carry out numerical simulation of the barotropic tidal elevation field in theIndonesian Seas using horizontally two-dimensional primitive equation model. It is foundthat, to reproduce realistic tidal elevations in the Indonesian Seas, the energy lost by theincoming barotropic tides to internal waves within the Indonesian seas should be taken intoaccount. The numerical experiments show that the model predicted tidal elevations in theIndonesian Seas best fit the observed data when we take into account the baroclinic energyconversion in the Indonesian Seas ~86.1 GW for the M2 tidal constituent and ~134.6 GWfor the major four tidal constituents (M2, S2, K1, O1). For this baroclinic energy conversion,the value of Kñ averaged within the eastern area (Halmahera, Seram, Banda and MalukuSeas), the western area (Makassar and Flores Seas), and the southern area (Lombok Straitand Timor Passage) are estimated to be ~23 × 10-4 m2s-1, ~5 × 10-4 m2s-1, and ~10× 10-4m2s-1, respectively. This value is about 1 order of magnitude more than assumed for theIndonesian Seas in previous ocean general circulation models. We offer this study as awarning against using diapycnal diffusivity just as a tuning parameter to reproduce largescalephenomena. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14060 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 53-72 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14060/10929 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14062 2025-11-26T02:39:46Z ijreses:ART

REMOTE SENSING AND GIS TECHNIQUES FOR URBAN GROWTH MONITORING OF BASARAH CITY Salah A. H. Saleh Barasah landsat remote sensing temperature urban Basarah city has experienced a rapid urban expansion over the last decades dueto accelerated economic growth. This paper reports an investigation into the application ofthe integration of remote sensing and geographic information systems (GIS) for detectingurban built up growth for the period 1973 - 2002, and evaluate its impact on theenvironmental situation of Basarah city by analyzing the spatial distribution of urbanexpansion according to land cover types and normalized difference vegetation index(NDVI). The integration of remote sensing and GIS was found to be effective inmonitoring and analyzing urban growth patterns and in evaluating urbanization impact onsurface conditions of Baghdad area. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14062 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 73-83 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14062/10930 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14064 2025-11-26T02:39:46Z ijreses:ART

ESTIMATION OF GROSS PRIMARY PRODUCTION USING SATELLITE DATA AND GIS IN URBAN AREA, DENPASAR A.R. As-syakur T. Osawa I W.S. Adnyana ALOS/AVNIR-2 Aster gross primary production Denpasar Bali Remote sensing data with high spatial resolution is very useful to provideinformation about Gross Primary Production (GPP) especially over spatial coverage in theurban area. Most models of ecosystem carbon exchange based on remote sensing data usedlight use efficiency (LUE) model. The aim of this research was to analyze the distributionof annual GPP urban area of Denpasar. Two main satellite data used in this study wereALOS/AVNIR-2 and Aster satellite data. Result showed that annual value of GPP usingALOS/AVNIR-2 varied from 0.130 gC m-2 yr-1 to 2586.181 gC m-2 yr-1. Meanwhile, usingAster the value varied from 0.144 gC m-2 yr-1 to 2595.264 gC m-2 yr-1. The annual value ofGPP ALOS was lower than the value of Aster, because ALOS have high spatial resolutionand smaller interval of spectral resolution compared to Aster. Different land use couldeffect the value of GPP, because the different land use has different vegetation type,distribution, and different photosynthetic pathway type. The high spatial resolution of theremote sensing data is crucial to discriminate different land cover types in urban region.With heterogeneous land cover surface, maximum value of GPP using ALOS/AVNIR-2was smaller than that of Aster, however, the annual mean of GPP value usingALOS/AVNIR-2 was higher than that of Aster. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14064 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 84-95 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14064/10931 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14065 2025-11-26T02:39:45Z ijreses:ART

APPLICATION OF SEISMIC DATA PROCESSING FOR SEABED IMAGING Henry M. Manik Susilo Hadi Marine Geology Seismic The research was conducted in April-May 2010 in North Maluku watersbelonging to the District Luwuk Banggai, Central Sulawesi Province. This area is located atcoordinates 2 ° S - 4 ° S and 123 ° E - 126 ° east. Data processing was done at OceanAcoustics Laboratory, Department of Marine Science and Technology, Bogor AgriculturalUniversity and Marine Geological Institute (MGI) in Bandung. Seismic data processingusing the data in SEG-Y format. The data was computed with Seisee software and bandpass filtering using Matlab. Based on the results of research, it is evident that increasing thefrequency band was followed by the higher the resolution. Sampling point 30 in the form ofsandy clay sediments has an impedance value of 2.49 and the value of reflection coefficientof 0.23. While the sampling point 31 in the form of silty clay in the study showed the valueof the impedance of 1,93 with the reflection coefficient of 0.11. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14065 International Journal of Remote Sensing and Earth Sciences; Vol. 7 No. 1 (2010); 96-100 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14065/10932 Copyright (c) 2010 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14067 2025-11-26T04:17:55Z ijreses:ART

TWO VIEWING THEORY ON ATMOSPHERE CORRECTION IN OCEAN COLOR ALGORITHM Sisir Kumar Dash Tasuku Tanaka Ryutaro Tateishi GLI 6S Radiative Transfer Reflectance Rayleigh Mie A new algorithm for retrieving optical thickness and surface reflectance, data in the visible bands from satellites is developed. The proposed algorithm is to solve the simultaneous equation of two unknown variables, i.e. aerosol optical thickness and surface reflectance (r). In term of difference from the conventional and, one directional retrieval algorithm, we do not need the spectral characteristics of aerosol. We solve the equation by forward calculation using the 6S transfer code. The two observational equations change linearly within the domain where we solve the solution. We estimate the chlorophyll-a concentration from the evaluated r. This method is validated against Global Imager (GLI) data, which has two independent data for one pixel in both tilting and nadir viewing.  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14067 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 1-12 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14067/10934 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14068 2025-11-26T03:14:35Z ijreses:ART

VERTICAL DISTRIBUTION OF CHLOROPHYLL-A BASED ON NEURAL NETWORK TAKAHIRO OSAWA CHAO FANG ZHAO NUARSA I WAYAN I KETUT SWARDIKA YASUHIRO SUGIMORI Ocean color Chlorophyll-a (Chl-a) Vertical structure Artificial Neural Networks (ANN) An algorithm of estimating Vertical distribution of Chlorophyll-a (Chl-a) was evaluated based on Artificial Neural Networks (ANN) method in Hokkaido field in the northwest of Pacific Ocean. The algorithm applied to the data of SeaWiFS on OrbView-2 and AVHRR on NOAA off Hokkaido, has been applied on September 24, 1998 and September 28, 2001. Ocean color sensor provides the information of the photosynthetic pigment concentration for the upper 22% of the euphotic zone. In order to model a primary production in the water column derived from satellite, it is important to obtain the vertical profile of Chl-a distribution, because the maximum value of Chl-a concentration used to lie in the subsurface region. A shifted Gaussian model has been proposed to describe the variation of the chlorophyll-a (Chl-a) profile which consists of four parameters, i.e. background biomass (B0), maximum depth of Chl-a (zm), total biomass in the peak (h), and a measurement of the thickness or vertical scale of the peak (cr). However, these parameters are not easy to be determined directly from satellite data. Therefore, in the present study, an ANN methodology is used. Using in-situ data from 1974 to 1994 around Japan Islands, the above four parameters are calculated to derive the Chl-a concentration, sea surface temperature, mixed layer depth, latitude, longitude, and Julian days. The total of 6983 profiles of Chl-a and temperature are used for ANN. The correlation coefficients of these parameters are 0.79 (B0), 0.73 (h), 0.76 (cr) and 0.79 (zm) respectively. A site called A-linc off Hokkaido is used to evaluate Chl-a concentration in each depth. After comparing with in-situ data and ANN model, the results show good agreement relatively. Therefore, the ANN method is applicable and available tool to estimate primary production and fish resources from the space. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14068 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 1-11 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14068/10933 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14069 2025-11-26T04:17:54Z ijreses:ART

ESTIMATION OF CHLOROPHYLL-A CONCENTRATION FROM THE ATMOSPHERIC CORRECTION OF MISR DATA Sisir Kumar Dash Tasuku Tanaka Hiroyuki Hachiya Yashuhiro Sugimori MISR 6S AOT Surface reflectance Chlorophyll-a Multi Angle Imaging Spectro Radiometer (MISR) has a capability to observe the ocean surface from different viewing directions. Attempts were made to estimate the ocean surface reflectance and chlorophyll-a concentration using MISR data. The aerosol optical thickness (OAT), available from the MISR archive is compared with the results simulated using the 6S radiation transfer code. It turns out that the AOT values agree with each other up to 85 percent in certain areas in case-1 waters. Substituting the archive values of AOT into the radiative transfer process, we obtain the surface reflectance. This surface reflectance, in turn, is employed together with the in-water algorithm, to obtain the clhorophyll concentration maps for three viewing directions (aft, nadir and forward). The pattern of obtained chlorophyll map is reasonable. It is estimated that an error of about 35 percent is involved in the radiance calibration and AOT , Hence, with best possibility, the surface reflectance is quantified and the chlorophyll maps were generated. When it is compared with the nadir observation, the forward viewing camera overestimates and the aft viewing camera underestimates the chlorophyll-a concentrartion especially in case-1 waters. In case 2 waters, the chlorophyll-a concentration shows similiar patterns for the three different viewing directions. Due to lack of in-situ data, absolute chlorophyll values were ignored but errors were quatified for the surface reflectance and the aerosol optical thickness with the 6S simulated results. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14069 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 13-23 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14069/10935 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14070 2025-11-26T03:14:35Z ijreses:ART

STUDY OF MODIS-AQUA DATA FOR MAPPING TOTAL SUSPENDED MATTER (TSM) IN COASTAL WATERS Bambang Trisakti Parwati Syarif Budhiman MODIS-Aqua Landsat TSM algorithm model spatial resolution curve of spectral value The MODIS-Aqua data have been studied to map TSM distribution in coastal waters. TSM algorithm model for MODIS data with spatial resolution of 250 m, 500 m and 1000 m was developed by correlating the TSM derived from spectral values of MODIS and the TSM derived from Landsat-7 ETM data using the calibrated algorithm. Statistical test was conducted to see normality of data and level of influence from both parameters. Analysis was conducted to see the change of spectral value from bands of MODIS data with resolution of 1000 m towards the change of level of TSM concentration. The results showsthat the TSM algorithm model is in the form of power (Xa) with the highest correlation coefficient is obtained from the correlation between the Landsat TSM value with the quantification of band 1 and band 2 of MODIS data for spatial resolution 250 m, ratio of band 4 and band 3 for spatial resolution 500 m, and ratio of band 13 and 11 for spatial resolution 1000 m. The pattern of TSM distribution in coastal waters can be identified in more accurate using MODIS data with resolution of 250 m and 500 m. The analysis result of the curve of MODIS spectral value data with resolution 1000 m shows that the change of TSM concentration influences significantly to the form of curve of spectral value, especially for band 11 - 16 ( visible green, red and NIR). BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14070 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 19-31 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14070/10937 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14071 2025-11-26T03:14:35Z ijreses:ART

STUDY OF OCEAN PRIMARY PRODUCTIVITY USING OCEAN COLOR DATA AROUND JAPAN TAKAHIRO OSAWA CHAOFANG ZHAO I WAYAN NUARSA SWARDIDAI I KETUT YASUHIROSUGIMORI ocean color primary productivity chlorophyll profile artificial neural network Ocean primary production is an important factor for determining the ocean's role in global carbon cycle. In recent years, much more chlorophyll-a concentration data in the euphotic layer were derived from the satellite ocean color sensors. The primary productivity algorithms have been proposed based on satellite chlorophyll measurements (Piatt, 1988; Morel, 1991) and other environmental parameters such as sea surfacetemperature or mixed layer depth (Behrenfeld and Falkowski, 1997; Esaias, 1996; Asanuma, 2002). In order to estimate integrated primary productivity in the whole water column, the vertical distribution of chlorophyll concentration below the sea surface should be reconstructed based on satellite data. In this paper, the vertical profile data of chlorophyll-a (Chl-a) measured around Japan Islands from 1974 to 1994 were reanalyzed based on the shifted-Gaussian shape proposed by Piatt et al (1988). Using this statistical model (neural network) and the photosynthesis irradiance parameters from Asanuma (2002), the distribution of primary productivity and its seasonal variation around Japan islands were estimated from SeaWiFS data, and the results were compared with in situ data and the other two models estimated from VGPM and mixed layer depth model. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14071 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 12-18 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14071/10936 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14072 2025-11-26T04:17:54Z ijreses:ART

ESTIMATION OF AIR TEMPERATURE USING REMOTE SENSING BASED ON THERMAL DIFFUSIVITY APPROACH M. Rokhis Khomarudin Ahmad Bey Idung Risdiyanto physical model temperature remote sensing The measurement of air temperature usually used thermometer in the meteorology or climate station under Bureau of Meteorology and Geophysics. In Indonesia, there are some limitations in air temperature measurement and then they could not provide the spatial high resolution information. The measurement of air temperature is very important for analyzing the human comfort, photosynthesis, and vegetation growth which we need saome details spatial information. However, when data were sparse, the underlying assumptions about the variation among sampled points often differed and the choice of interpolation method and parameters then became critical. Often though data may be too sparse to use any of the interpolation methods, alternate ways to derive spatially representative values of air temperature need to researched. The data that could provide spatial information are remote sensing. The objective of this research is to estimate air temperature using remote sensing data (NOAA/AVHRR and LANDSAT/TM), based on thermal diffusivity approach. The steps of this research include the calibration of surface temperature, the determination of amplitude, and the estimation of air temperature. Based on this research, the best equation to calculate surface temperature from NOAA AVHRR is Ulivieri et al equation. This equation shows the higher correlation between surface temperatures from NOAA/AVHRR and the observation in the field than the other equation. Physically, this research could estimate air temperature from satellites data, but statistically, this research has not enough significancy to describe the field observation. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14072 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 24-30 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14072/10938 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14073 2025-11-26T04:17:54Z ijreses:ART

A NEW APPROACH FOR THE TSUNAMI PREDICTION USING SATELLITE ALTIMETRY: TRIALS FOR ACEH TSUNAMI EVENTS IN 2004 AND 2005 Susumu Kanno Yasuo Furushima I Wayan Nuarsa I Gede Hendrawan tsunami earthquake bottom topography sea surface height, satellite altimetry altimeter disaster prevention Change in the sea surface height anomaly derived from satellite altimeter was examined and applied to evaluate the possibility of tsunami prediction before the occurance. Sea surface height anomaly was composed period during earthquake and tsunami occurance. Daily variability in the sea surface height anomaly was traced about the location of hypocenter, aftershock, and the end of erthquakes from satellite altimetry. Results shows that there are the locations where the sea surface height anomaly suddenly increased or decreased before tsunami event at least. This result can be utilized and applied for the development in not only the stunami monitoting system as the disaster monitoring, but also for the effective tsunami prediction system in the near future. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14073 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 31-40 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14073/10941 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14074 2025-11-26T03:02:44Z ijreses:ART

STUDY ON FLOOD INUNDATION IN PEKALONGAN, CENTRAL JAVA Syams Nashrrullah Aprijanto Junita Monika Pasaribu Manzul K. Hazarika Lal Samarakoon Tidal flood MIKE-21 InSAR Pekalongan ALOS/PALSAR Tidal flood or ‘rob’ is a serious problem in many coastal areas in Indonesia, including Pekalongan in the northern coast of Java island. This study aimed to simulate the flood inundation area for different scenarios of sea level rise, also to investigate the possibility of land subsidence that may further aggravate the problem of flooding in Pekalongan. In this study, the MIKE-21 model was used to simulate and predict the flood inundation area. Tidal data were generated from the Tide Model Drive (TMD). The tidal flood simulations were carried out for three different scenarios of sea level rise: 1) current situation, 2) next 50 years, assuming no sea level rise, and 3) next 50 years, assuming 50 cm of sea level rise. Based on the results, the ranges of water level rise in Pekalongan for each scenario were 0.23-1.27 m, 0.36-1.38 m, and 0.65-1.53 m, respectively. Meanwhile, ground displacement maps were derived from the ALOS/PALSAR data using Differential Interferometric Synthetic Aperture Radar (D-InSAR) technique. Twelve level 1.0 images of ALOS/PALSAR data acquired in ascending mode during 2008 to 2009 were collected and processed in time-series analyses. In total, 11 pairs of interferogram were produced by taking the first image in 2008 as the master image. The results showed that the average of land subsidence rate in Pekalongan city was 3 cm/year, and the subsidence mainly occurred in the western part of the city. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14074 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 76-83 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14074/10940 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14075 2025-11-26T03:14:35Z ijreses:ART

CORAL REEF HABITAT CHANGING ASSESSMENT OF DERAWAN ISLANDS, EAST KALIMANTAN, USING REMOTE SENSING DATA Marlina Nurlidiasari Syarif Budhiman Coral Reef Change Detection Landsat-TM Derawan Coral reefs in Dcrawan Islands are astonishingly rich in the marine diversity. However, these reefs are threatened by humans. Destructive fishing methods, such as trawl, blasting and cyanide fishing practise, are found to be the main cause of this degradation. The coral reefs habitat reduction is also caused by tourism activities due to trampling over the reef and charging organic and anorganic wastes. The capabilities of satellite remote sensing techniques combined with field data collection have been assessed for the coral reef mapping and the change detection of Derawan Island. Multi-temporal Landsat TM and ETM images (1991 and 2002) have been used. Comparison of the classified images of 1991 and 2002 shows spatial changes of the habitat. The changes were inaccordance with the known changes in the reef conditions. The analysis shows the decrease of the coral reef and patchy seagrass percentage, while the increase of the algae composite and patchy reef percentage. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14075 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 32-44 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14075/10939 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14076 2025-11-26T03:14:34Z ijreses:ART

MAPPING CORAL REEF HABITAT WITH AND WITHOUT WATER COLUMN CORRECTION USING QUICKBIRD IMAGE Marlina Nurlidiasari Syarif Budhiman Coral Reef Quickbird Water Column Correction Remote sensing from space offers an effective approach to solve the limitation of field sampling, in particular to monitor the reefs in remote sites. Moreover, using the achieved remotely sensed data, it is even possible to monitor the historic status of the coral reef environment. The capabilities of satellite remote sensing techniques combined with the field data collection have been assessed for generating coral reef habitat mapping of the Derawan Island. A very high spatial resolution multi-spectral QuickBird image (October 2003) has been used. The capability of QuickBird image to generate a coral reef habitat map with the water column correction by applying the Lyzenga method, and also without the water column correction by the applying maximum likelihood method, have beenassessed. The classification accuracy of the coral reef habitat map increased after the improvement of the water column effects. The classification of QuickBird image for coral reef habitat mapping increased up to 22% by applying a water column correction. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14076 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 45-56 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14076/10942 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14077 2025-11-26T04:17:54Z ijreses:ART

THREE-DIMENSIONAL SIMULATION OF TIDAL CURRENT IN LAMPUNG BAY: DIAGNOSTIC NUMERICAL EXPERIMENTS Alan Frendy Koropitan Safwan Hadi Ivonne M.Radjawane POM diagnostic mode tidal current residual current Lampung Ba Princeton Ocean Model (POM) was used to calculate the tidal current in Lampung Bay using diagnostic mode. The model was forced by tidal elevation, which was given along the open boundary using a global ocean tide model-ORITIDE. The computed tidal elevation at St. 1 and St 2 are in a good agreement with the observed data, but the computed tidal current at St 1 at depth 2 m is not good and moderate approximation is showed at depth 10 m. Probably, it was influenced by non-linier effect of coastal geometry and bottom friction because of the position of current meter, mooring closed to the coastline. Generally, the calculated tidal currents in all layers show that the water flows into the bay during flood tide and goes out from the bay during ebb tide. The tidal current becomes strong when passing through the narrow passage of Pahawang Strait. The simulation of residual tidal current with particular emphasis on predominant contituent of M2 shows a strong inflow from the western part of the bay mouth, up to the central part of the bay, then the strong residual current deflects to the southeast and flows out from the eastern part of the bay mouth. This flow pattern is apparent in the upper and lower layer. The other part flows to the bay head and froms an antic lockwise circulation in the small basin region of the bay head. The anticlockwise circulations are showed in the upper layer and disappear in the layer near the bottom. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14077 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 41-50 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14077/10945 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14078 2025-11-26T03:02:44Z ijreses:ART

ANALYSIS OF SPOT-6 DATA FUSION USING GRAM-SCHMIDT SPECTRAL SHARPENING ON RURAL AREAS Danang Surya Candra Data fusion SPOT-6 Gram-Schmidt PSNR rural area Image fusion is a process to generate higher spatial resolution multispectral images by fusion of lower resolution multispectral images and higher resolution panchromatic images. It is used to generate not only visually appealing images but also provide detailed images to support applications in remote sensing field, including rural area. The aim of this study was to evaluate the performance of SPOT-6 data fusion using Gram-Schmidt Spectral Sharpening (GS) method on rural areas. GS method was compared with Principle Component Spectral Sharpening (PC) method to evaluate the reliability of GS method. In this study, the performance of GS was presented based on multispectral and panchromatic of SPOT-6 images. The spatial resolution of the multispectral (MS) image was enhanced by merging the high resolution Panchromatic (Pan) image in GS method. The fused image of GS and PC were assessed visually and statistically. Relative Mean Difference (RMD), Relative Variation Difference (RVD), and Peak Signal to Noise Ratio (PSNR) Index were used to assess the fused image statistically. The test sites of rural areas were devided into four main areas i.e., whole area, rice field area, forest area, and settlement. Based on the results, the visual quality of the fused image using GS method was better than using PC method. The color of the fused image using GS was better and more natural than using PC. In the statistical assessment, the RMD results of both methods were similar. In the RVD results, GS method was better then PC method especially in band 1 and band 3. GS method was better than PC method in PSNR result for each test site. It was observed that the Gram-Schmidt method provides the best performance for each band and test site. Thus, GS was a robust method for SPOT-6 data fusion especially on rural areas. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14078 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 84-89 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14078/10943 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14079 2025-11-26T03:14:34Z ijreses:ART

DEVELOPMENT OF THE NEW ALGORITHM FOR MANGROVE CLASSIFICATION Nuarsa I Wayan Sandi Adnyana I Wayan Yasuhiro Sugimori Susumu Kanno Fumihiko Nishio Mangrove Landsat ETM+ Empirical Model Image Classification The objective of the study is to develop the algorithm for mangrove classification and density. Regression and correlation analysis was used to perform the equation. CE1 = (0.663*Band 3) + (0.l55 *Band 4) - (l.4*Band 5) + 0.995 And CE2 = 36 * Band 4 + 6*Band 5 + Band 3 were two formula that have been used to classify the mangrove. The object will be classified as mangrove when the value of CE1 is between -31.439 and 0.888, and value of CE2 is greater than or equal to 2000. On the other hand, density of the mangrove was expressed as DE = (2 * Band 4)/(Band 1+Band 3). Mangrove classification result in this study was similar to those of the existing methods. Statistical approach in this study generally gives the higher result tendency than other methods. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14079 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 57-64 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14079/10948 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14080 2025-11-26T03:02:43Z ijreses:ART

VULNERABILITY LEVEL MAP OF TSUNAMI DISASTER IN PANGANDARAN BEACH, WEST JAVA Iqoh Faiqoh Jonson Lumban Gaol Marisa Mei Ling Coastal vulnerability Tsunami GIS Pangandaran Indonesia is located in a seismic active region where tsunami often occur. One of tsunami prone areas in Indonesia is southern coast of Java, such as the coastal areas of Pangandaran, West Java. One of the instruments in the tsunami disaster mitigation is the vulnerability map of coastal region on tsunami. Analyses of tsunami vulnerability assessment was performed by using merger or overlay methods in Geographic Information Systems (GIS). The parameters used to analyze tsunami vulnerability level were elevation, topography, landuse, coastal border, and river banks. The vulnerability were divided into five classes i.e., very high, high, medium, low, and very low. Results showed that Pananjung, Babakan, Pangandaran (Pangandaran District); and Sukaresik and Cikembulan (Sidamulih District) sub-districts were identified as areas of very high level of tsunami vulnerability with total area of 737.703 hectares. Areas with low level of vulnerability were Pagergunung, Putrapinggan, and Kersaratu sub-districts with total area of 4,816.204 hectares. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14080 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 90-103 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14080/10946 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14081 2025-11-26T03:14:34Z ijreses:ART

SPECTRAL CHARACTERISTIZATION OF RICE FIELD USING MULTITEMPORAL LANDSAT ETM+ DATA NUARSA I WAYAN SUSUMU KANNO YASUHIRO SUGIMORI FUMIHIKO NISHIO Rice field Landsat ETM+ Spectral Characteristic Multi-temporal The preliminary study using Landsat ETM+ to estimate the rice production in Regency of Tabanan, Bali Province was conducted. The objectives of this study were to know spectral characteristic of rice plant in three importance growth periods of rice, and to develop a model to identify the distribution of rice. Landsat ETM+ in two acquisition dates (March 21st, 2003 and May 24*, 2003) were used in this study. Characteristics of rice were analyzed using radiance value of Landsat ETM+ obtained from converting digital number of Landsat data. Multi-variable linear regression analysis was developed to classify the rice in its growth period. The result showed that the rice plant has different reflectance in seedling-development period, ear differentiation period and maturation period. It isexpressed by the radiance value of Landsat ETM+. However, spectral characteristic of rice in each band of Landsat ETM+ is similar to the green vegetations in general, except in blueband (Bl). Based on statistical analysis, the classification of rice in each its growth period can be classified. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14081 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 65-71 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14081/10944 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14083 2025-11-26T04:17:54Z ijreses:ART

MONITORING OF LAND USE CHANGES USING AERIAL PHOTOGRAPH AND IKONOS IMAGE IN BEDUGUL, BALI I Wayan Sandi Adnyana Fumihiko Nishio Josaphat Tetuko Sri Sumantyo Gede Hendrawan land use monitoring aerial photograph Ikonos image There was change of expending land use in Bedugul. It is necessary to monito the change of highland of Bali, catchments area of Beratan, Buyan and Tamblingan lakes. In order to control land use change and to anticipate degradation of hydrology function of this area. This study is to monitor the land use change by remote sensing and GIS technique. To evaluate land use and land cover, aerial photograph imagery and Ikonos imagery were used. Over 22 years of observation (1981-2003), there was land use changes in the catchments area of Beratan, Buyan and Tamblingan lakes at Bedugul area. The area of settlement increased by 62.6 ha, dry land vegetable crops and forest decreased by 116.5 ha and 32.5 ha, respectively. The surface area of Buyan Lake was also decreased, due to sedimentation caused by erosion in the vegetables dry land crops. Planning the land use study on erosion and soil-water conservation in this area necessary, in order to control land use change, erosion, and sedimentation in the lakes. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14083 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 51-58 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14083/10951 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14084 2025-11-26T03:02:43Z ijreses:ART

THE RELATIONSHIP BETWEEN TOTAL SUSPENDED SOLID (TSS) AND CORAL REEF GROWTH (CASE STUDY OF DERAWAN ISLAND, DELTA BERAU WATERS) Ety Parwati Mahdi Kartasasmita Kadarwan Soewardi Tridoyo Kusumastanto I Wayan Nurjaya Landsat total suspended solid (TSS) coral reef Berau waters Total suspended solid (TSS) is one of the water quality parameters and limiting factor affecting coral reef growth. In this study, we used the algorithm of TSS= 3.3238*e(34.099* Green band) (where green band is reflectance band 2) to extract TSS from Landsat satellite data. The algorithm was validated with field data. Water column correction method developed by Lyzenga was used to map coral reef. The result showed that the coral reef area in Berau waters decreased significantly (about 12,805 ha or around 36 % ) from the year of 1979 to 2002. The most coral reef reduced area was detected around Derawan Island (about 5,685 ha). Further, some areas changed into sand dune. TSS concentration around Delta Berau and Derawan Island increased aproximately twice from 15- 35 mg/l in 1979 to 20-65 mg/l in 2002. The increase of TSS concentration was followed by the decrease of coral reef area. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14084 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 104-113 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14084/10947 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14085 2025-11-26T03:02:43Z ijreses:ART

IDENTIFICATION OF INUNDATED AREA USING NORMALIZED DIFFERENCE WATER INDEX (NDWI) ON LOWLAND REGION OF JAVA ISLAND Suwarsono Jalu Tejo Nugroho Wiweka inundated area NDWI Landsat lowland region Java Island Flood disaster is a major issues due to its frequently events on several areas in Indonesia. Delineation of inundated area caused by flood is needed to support disaster emergency response. The objective of this research was to identify inundated areas using NDWI methos from Landsat TM/ETM+ data on lowland regions of Java island. A pair of the data (before and during the flood) were in each observation areas. Observation areas were selected in several location of lowland regions of Java island where great event of flood occurred during the last decades. The thresholds values of NDWI change were used to separate the flood and non flood areas. The results showed that the extent of inundated area caused by flood on lowland regions can be identifyed and separated based on NDWI variables extracted from Landsat TM/ETM+. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14085 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 114-121 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14085/10949 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14086 2025-11-26T03:02:43Z ijreses:ART

DOWNWELLING DIFFUSE ATTENUATION COEFFICIENTS FROM IN SITU MEASUREMENTS OF DIFFERENT WATER TYPES Bisman Nababan Veronica S.A. Louhenapessy Risti E. Arhatin Ed Kd euphotic zone one optical depth NEGOM Process of light reduction or loss (attenuation) by scattering and absorption is affected by solar zenith, time, depth, and seawater constituents. Downwelling diffuse attenuation coefficient (Kd) is important to understand for light penetration and biological processes in ocean ecosystem. It is, therefore, important to know the Kd value and its variability in ocean ecosystem. The objective of this study was to determine downwelling diffuse attenuation coefficients and its variability form in situ measurements of different water types. In situ downwelling irradiances (Ed) were measured using a submersible marine environmental radiometer instrument (MER) during a clear sky, calm water condition, and at the time range of 10:30 a.m. up to 14:00 p.m. local time in the northeastern Gulf of Mexico in April 2000. In general, Ed values decreases exponentially with depth. Ed at 380 nm exhibited the lowest attenuation (the most penetrative light), while Ed at 683 nm exhibited the highest attenuation (the most light loss at the top of water column). Overall, the Kd patterns tended to decrease from 380 nm to 490 nm (blue-green wavelength), and increase from 490 nm to 683 nm (green-red wavelength). Kd values in offshore region were relatively lower than in coastal region. Kd can be used to determine the depth of euphotic zone in offshore or teh case-1 water type and the depth of one optical depth (the water column depth where the ocean color satellite can possibly sense). BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14086 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 122-133 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14086/10950 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14087 2025-11-26T03:02:43Z ijreses:ART

RANDOM FOREST CLASSIFICATION OF JAMBI AND SOUTH SUMATERA USING ALOS PALSAR DATA Mulia Inda Rahayu Katmoko Ari Sambodo Land cover ALOS-PALSAR random forest (RF) classification remote sensing Recently, Synthetic Aperture Radar (SAR) satellite imaging has become an increasing popular data source especially for land cover mapping because its sensor can penetrate clouds, haze, and smoke which a serious problem for optical satellite sensor observations in the tropical areas. The objective of this study was to determine an alternative method for land cover classification of ALOSPALSAR data using Random Forest (RF) classifier. RF is a combination (ensemble) of tree predictors that each tree predictor depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. In this paper, the performance of the RF classifier for land cover classification of a complex area was explored using ALOS PALSAR data (25m mosaic, dual polarization) in the area of Jambi and South Sumatra, Indonesia. Overall accuracy of this method was 88.93%, with producer’s accuracies for forest, rubber, mangrove & shrubs with trees, cropland, and water classes were greater than 92%. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14087 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 134-141 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14087/10952 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14088 2025-11-26T04:17:54Z ijreses:ART

ESTIMATION OF FISHERY RESOURCES BY M-F GIS USING SATELLITE DATA AND ITS APPLICATION TO TAC FOR SUSTAINABLE FISHERY PRODUCTION Yasuhiro Sugimori Takashi Moriyama Bambang Tejasukmana Indroyono Susilo Ketut Swardika remote sensing fisheries GIS TAC - BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14088 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 59-79 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14088/10955 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14089 2025-11-26T03:02:43Z ijreses:ART

ENVIRONMENTAL QUALITY CHANGES OF SINGKARAK WATER CATCHMENT AREA USING REMOTE SENSING DATA Ita Carolita Bambang Trisakti Heru Noviar Singkarak lake total suspended solid run off water discharge Landsat SPOT Lake Singkarak in west Sumatera is currently in very poor condition and become one of the priorities in the government lake rescue program. High sedimentation rate from soil erosion has caused siltation, decreasing of quality and quantity of lake water. Monitoring of the environment quality changes of the lake and its surrounding are required. This study used Landsat and SPOT satellite data in periods of 2000-2011 to evaluate environmental quality parameters of the lake such as land cover, lake water quality (total suspended solid), water run-off, and water discharge in Singkarak lake catchment area. Maximum likelihood classifier was used to obtain land cover. Total suspended solid was extracted using Doxaran algorithm. The look up table and rational method were used to estimate run-off and water discharge. The results showed that the decreasing of forest area and the increasing of settlement were consistent with the increasing of average run-off and water discharge in Paninggahan and Sumpur sub-catchment area. The results were also consistent with the increasing of TSS in Singkarak lake, where TSS increased from around 2-3 mg/l up to 5-6 mg/l in the periods of 2000-2011. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14089 International Journal of Remote Sensing and Earth Sciences; Vol. 10 No. 2 (2013); 142-148 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14089/10953 Copyright (c) 2013 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14090 2025-11-26T03:14:34Z ijreses:ART

THE APPLICATION OF WAVELET ANALYSIS FOR INTERNAL WAVE DETECTION IN SAR AND OPTICAL IMAGES DATA OVER TSUSHIMA STRAIT YESSY ARVELYNA wavelet analysis SAR image optical image internal wave On this paper, wavelet analysis has been used for internal wave detection in ERS SAR and ASTER images data over Tsushima strait, southwest of Japan, during 1993-2004 period. Various wavelet transforms, such as Haar wavelet, Symlet wavelet, Coif wavelet, Daubechies wavelet, and Discreet Meyer wavelet, are tested comparably with different level of synthesize image on horizontal, diagonal, and vertical detail, and approximation to study the internal wave characteristic in image. Internal wave features were detected as elongated pattern in image with higher wavelet coefficient (>36) than sea surface (litlle than 10) on horizontal and vertical detail coefficient of image transforms at level 2-5. The decomposition image shows the tendency that the decomposition of internal wave feature using wavelet transform tends to follow the wavelet function. This may reduced the height of leading wave. Smoother result of internal wave shape can be formed using higher scale resolution of image and higher number of vanishing moments such as Daubechies waveletdb5, Symlet wavelet-sym5, and Discrete Meyer wavelet. The compactly supported wavelet function with orthogonal basis with scale function and FIR filter, such as discrete Meyer function is proposed for smoothness of feature, space save coding, and to avoid depashing in image. So far, the detection processes were performed well on the internal waves data that occurred at north coast off Kitakyushu and NW/W/SW/E coast off Tsushima Island on June to September period whose lengths were detected between 6-28 km and wavelength between 120m-1.28km. The directions of internal wave propagation were varied between NW-SW at eastern channel and N-SW at western channel of Tsushima Strait. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14090 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 72-80 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14090/10954 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14091 2025-11-26T04:17:54Z ijreses:ART

CROP WATER STRESS INDEX (CWSI) ESTIMATION USING MODIS DATA M.Rokhis Khomarudin Parwati Sofan CWSI NDVI ST MODIS Land Surface Temperature Water Stress Crop Water Stress Index (CWSI) is an index which is used to explain the amount of crop water defisiency based on canopy surface temperature. Many researches of CWSI have been done for arranging irigation water system in several crops at different areas. Beside its application in irigation system, CWSI is also known as one of parameters that can influence crop productivity. Regarding the above explanation, it is implied that CWSI is important for monitoring crop drought, arranging irigation water, and estimating crop productivity. This research is proposed to estimate CWSI using MODIS (Moderate Resolution Imaging Spectroradiometer) data which is related to Normalized Difference Vegetation Index (NDVI) and Soil Moisture Storage (ST) in paddy field. The interest area is in East Java wich is the driest area in Java Island. MODIS land surface temperature is used to estimate CWSI, while MODIS reflectance 500 m is used to estimate NDVI. They were downloaded from NASA website. Data period was from June 15th to June 30 th, 2004. Based on the correlation between NDVI and CWSI, we can estimate NDVI value when paddy water stress occured. The result showed that the largest paddy area in East Java which has high water stress is located in Bojonegoro District. The water stress areain Bojonegoro Distric increase from June 15th to June 30th, 2004. The high to medium water stress level in East Java were predicted as bare land. The CWSI has negative correlation with NDVI and ST. The CWSI 0.6 are obtained in NDVI 0.5 with ST less than 50 percent. This showed that the paddy water stress began at NDVI 0.5 and ST 50 percent. Coefficient of correlation between CWSI and NDVI is 0.58, while CWSI and ST is 0.71. The correlation model between CWSI, NDVI and ST is statistically significant. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14091 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 80-84 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14091/10956 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14092 2025-11-26T03:14:34Z ijreses:ART

THE ASSESSMENT OF PELAGIC FISH STOCK AND ITS DISTRIBUTIONS IN INDIAN OCEAN BY SPLIT BEAM ACOUSTIC SYSTEM I Nyoman Arnaya Split-beam Acoustic System Fish Stock Assessment Target Strength Density Distribution Indian Ocean (southern part of Java-Bali-Lombok) The assessment of pelagic fish stock and its distribution in Indian Ocean, especially southern part of Java-Bali-Lombok, was conducted by SIMRAD EK-500 Split-beam Acoustic System, in October-November 2001. The research was carried out by R/V Baruna Jaya VII of Indonesia Institute of Science (LIPI), under the Fish Stock Assessment Project in Indonesian Waters of fiscal year 2001. As a result, it can be reported that (I) the dominant species of pelagic fish distributed in this area is small pelagic fish with target strength (TS) values between -54.00 dB to - 37.60 dB, absolute density of between 0.07 to 218 fish/1000 m\ and total fish stock of 526.570 ton/year; (2) the large pelagic fish (some species of tuna) also distributed in the area with average TS of -27 dB, absolute density between 0.00 to 0.07 fish/100 m\ and total fish stock of 386,260 ton/year. This result still needs more accurate verification, especially on the species composition and individual size of fish by a more appropriate biological sampling method (mid-water trawl). Consequently, more acoustical surveys combined with oceanographic sampling and exploratory fishing are needed to evaluate the existing condition of marine fish resources in the area, in order to optimize and set up the relevant and accurate fisheries management plan for suitable and responsible utilization offish resources. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14092 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 81-85 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14092/10957 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14093 2025-11-26T03:07:34Z ijreses:ART

IDENTIFICATION OF FISHERY RESOURCES IN MADURA STRAIT BASED ON THE IMPLEMENTATION OF POTENTIAL FISHING ZONE INFORMATION FROM REMOTE SENSING Bidawi Hasyim Maryani Hartuti Sayidah Sulma Fish Landing Port NOAA-AVHRR Potential fishing zone Spatial information of Potential Fishing Zone (PFZ) was used to identify the prospective location in the Madura Strait, where the fishermen from Fish Landing Port (FLP) around the Madura Strait conducted fishing activities. PFZ was aimed to determine fishing location, to identify the type of pelagic fish resources which were dominantly caught in the MAdura Strait. Fish resources data were obtained by observing the FLP in the east of Madura Strait especially in Pondok Mimbo, Jangkar, Besuki, Probolinggo, Pamekasan, and Sumenep. Based on the application of PFZ spatial information and observation, the types of pelagic fish caught on west monsoon were dominated by Euthynnus spp, Decapterus spp, Ratsrellinger spp, and Trichiurus spp. In the first transition season, types of fish resources were a mix between Euthynnus spp, Decapterus spp, Rastrellinger spp, Sardinella longiceps, and Trichiurus spp, however Sardinella longiceps were still dominated the catches. During the east monsoon fish resources at the Madura Strait was also dominated by Sardinella longiceps. This condition occurred until the second month of the second transition season followed by the mixing among Sardinella longiceps, Euthynnus spp, Decapterus spp, Rastrellinger spp and Trichiurus spp. Keywords: Fish Landing Port, NOAA-AVHRR, Potential fishing zone BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14093 International Journal of Remote Sensing and Earth Sciences; Vol. 6 (2009); 1-13 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14093/10963 Copyright (c) 2009 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14095 2025-11-26T03:14:34Z ijreses:ART

NUMERICAL CALCULATION FOR THE RESIDUAL TIDAL CURRENT IN BENOA BAY-BALI ISLAND GEDE HENDRAWAN WAYAN NUARSA WAYAN SANDI A.F. KOROPITAN YASUHIRO SUGIMORI model simulation tidal current residual current Princeton Ocean Model (POM) was used to calculate the tidal current and M2-residual current in Benoa Bay using barotropic model (mode 2). The model was forced by tidal elevation, which was given along the open boundary condition using tide data prediction from Hydro-Oceanography Division-Indonesian Navy (DISHIDROS TNI-AL). The computed tidal current and residual current have been compared with both data in Benoa Bay, that are data of the open boundary of Benoa Bay and condition of Benoa Bay after developed a port and reclamation of Serangan Island. The maximum velocity of tidal current for open boundary conditions at flood tide is 0.71 m/sec, whereas at ebb tide is 0.65 m/sec and the maximum velocity after developed a port and reclamation of Serangan Island, at flood tide, is 0.69 m/sec. The simulation of residual current with particular emphasis on predominant constituent of M2 after developed a port and reclamation of Serangan Island shows a strong flow at the western part of Tanjung Benoa and Benoa Harbor and also at bay mouth between Serangan Island and Tanjung Benoa. Maximum velocity of M2-residual current is 0.0585 m/sec by the simulation and showed that thecurrent which was produced forming two eddies in the bay of which one eddy is in the mouth of bay in southern part. The residual current for open boundary condition of bay shows four eddies circulation, one big eddies and the others small. The anticlockwise circulation occurs in the inner part of the bay. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14095 International Journal of Remote Sensing and Earth Sciences; Vol. 2 (2005); 86-93 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14095/10958 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14096 2025-11-26T04:17:53Z ijreses:ART

ESTIMATION OF TUNA FISHING GROUND IN LOW LATITUDE REGION USING SEA SURFACE HEIGHT GRADIENT DERIVED FROM SATELLITE ALTIMETRY: APPLICATION TO NORTHEASTERN INDIAN OCEAN Susumu Kanno Yasuo Furushima I Wayan Nuarsa I Ketut Swardika Atsushi Ono sea surface altimeter sea surface gradient remote sensing fishing ground search hook rate, fishery resource management In order to improve the method for prediction of tuna fishing ground, the modification of the analysis about satellite altimeter data was made as trial. In this study, we focused on the satellite altimeter, TOPEX/POSEIDON series, to improve the method of fishing ground prediction. Fishery data were supplied as hook rate by local fishing information around Indonesia and hearing infromation. The gradient of sea surface height is calculated between the neighbor grid which has the maximum gradient. Result showed that the fishery data with hook rate over 0.8 are grouped in a zone from 1.0E-06 of sea prediction of fishing ground quantitatively, but also reasonable accuracy as shown in the change in the standard deviation. This method can be utilized for the effective fishing plan with the resource protection and the economy in the fishing operation in near future. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article https://ejournal.brin.go.id/ijreses/article/view/14096 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006) 2549-516X 0216-6739 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14099 2025-11-26T03:34:09Z ijreses:ART

POLARIMETRIC-SAR CLASSIFICATION USING FUZZY MAXIMUM LIKEHOOD ESTIMATION CLUSTERING WITH CONSIDERATION OF COMPLEMENTARY INFORMATION BASED ON PHYSICAL POLARIMETRIC PARAMETERS, TARGET SCATTERING CHARACTERISTIK, AND SPATIAL CONTEXT KATMOKO ARI SAMBODO ANIATI MURNl RATIH DEWANTI MAHDI KARTASASMITA Cloudes polarimetric decomposition FMLE clustering polarimetric coherence Polarimetric-SAR unsupervised classification This paper shows a study on an alternative method for unsupervised classification of polarimetric-Syenthetic Aperture Radar (SAR) data. The first step was to extract several main physical polarimetric parameters (polarization power, coherence, and phase difference) from polarimetric covariance matrix (or coherency matrix) and physical scattering characteristics of land use/cover based on polarimetric decomposition (Cloude decomposition model). In this paper, we found that these features have complementary information which can be integrated in order to improve the discrimination of different land use or cover types. Classification stage was performed using Fuzzy Maximum Likelihood Estimation (FMLE) clustering algorithm. FMLE algorithm allows for ellipsoidal clusters of arbitrary extent and is consequently more flexible than standard Fuzzy K-Means clustering algorithm. Hoever, basic FMLE algorithm makes use exclusively the spectral (or intensity) properties of the individual pixel vectors and spatial-contextual information of the image was not taken into account. Hence, poor(noisy) classification result is ussualy obtained from SAR data due to speckle noise. In this paper, we propose a modified FMLE which integrate basic FMLE clustering with spatial-contextual information by statistical analysis of local neightbourhoods. The effectiveness of the proposed method was demonstrated using E-SAR polarimetric data acquired on the area of Penajam, East Kalimantan, Indonesia. Result showed classified images improving land-cover discrimination performance. Exhibiting homogeneous region, and preserving edge and other fine structures. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14099 International Journal of Remote Sensing and Earth Sciences; Vol. 5 (2008); 1-16 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14099/10959 Copyright (c) 2008 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14100 2025-11-26T04:17:53Z ijreses:ART

STUDY ON VARIABILITY MECHANISM OF 1997/1998 ENSO IN PACIFIC OCEAN AND EASTERN PART OF INDONESIAN ARCHIPELAGO Luh Made Chandra Astiti Ratnasari I Gede Hendrawan I Wayan Gede Astawa Karang Yasuhiro Sugimori ENSO SST ITF El Nino-Southern Oscillation (ENSO) is one of the most important climate anomalies humans are concerned about. It brought many changes in physical of the ocean. This phenomenon causes changes in sea surface temperature (SST). During El-Nino condition, the SST is much warmer in eastern side of Pacific Ocean than normal condition, and during La-Nina event the SST in eastern Pacific Ocean is cooler than normal condition. From July 1997, the warm water has spread from the western Pacific Ocean towards the east and the winds in the western Pacific were blowing strongly towards the east, pushing the warm water eastward on December 1997 and January 1998. Strong La-Nina condition water extended farther westward than usual. In October 1997, during El-Nino event 1997, the SST in eastern part of Indonesia Archipelago was cooler. The varies of SST in PacificOcean during El-Nino 1997 was influenced the Indonesian Through Flow (ITF). During El-Nino event 1997, surface current flown strongly from Pacific Ocean to the Indian Ocean On the other hand, since March 1998 the surface current inversed from Indonesian Sea to the Pacific Ocean.  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14100 International Journal of Remote Sensing and Earth Sciences; Vol. 3 (2006); 94-103 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14100/10960 Copyright (c) 2006 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14101 2025-11-26T03:58:39Z ijreses:ART

RESEARCH ON TECHNOLOGY DEVELOPMENT FOR FISHING VESSELS IDENTIFICATION BY SATELLITE REMOTE SENSING - STATUS IN DEVELOPED COUNTRIES AND JAPANESE PATROL SYSTEM T. Moriyama H. Tameishi J. Suwa S. Kanno Y. Sugimori vessel identification by satellite image IKONOS visible image JERS-1 Synthetic Apature Reader Current status and trends ov vessel detection, identification technology development and application in major countries were surveyed. According to increasing the number of foreign poaching and suspicious vessels intrusion into EEZ, patroliling by vessel and airplane does not satisfy the needs because of narrow coverege and observation frequncey. The satellite monitoring by SAR and optical sensor has been studied and partially used, but there are several disavantages such as observation frequncy, geometric occuracy and weather dependence to adopt for operational use. This paper describes an optimize system for vessel detection and identification by combining patrolling vessel, airplane and satellite. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14101 International Journal of Remote Sensing and Earth Sciences; Vol. 1 No. 1 (2004); 1-9 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14101/10961 Copyright (c) 2004 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14102 2025-11-26T03:34:08Z ijreses:ART

SEASONAL PATTERN OF WIND INDUCED UPWELLING OVER JAVA-BALI SEA WATERS AND SURROUNDING AREA Siswanto Suratno coastal upwelling Ekman transport Java-Bali Sea Monsoon circulation upwelling The influence of monsoonal wind to coastal upwelling mechanism which is generated by Ekman transport was studied here by analyzing wind stress curl (WSC) distribution over Java-Bali Sea waters and its surrounding area. Surface wind data were used as input data to calculate curl of wind stress in barotropic model. Confirmation with Corioli effect in the Southern Hemisphere, it could be known that negative curl value has relation with vertical motion of sea water as resulted by Ekman transport. Result of analysis showed that negative curl near coast over Java Sea which is stretching to Lombok Sea occurred in December to April when westerly wind of the North West Monsoon actives. It can be guidance and related with season of coastal upwelling in the region. Reversal condition, the occurrance of coastal upwelling in the south coast of JAva island related with the negative value of WSC that occurs since easterlies wind take place in May to August as a part of South East Monsoon episode. Generally, upwelling occurrance in the field of study is a response to the Monsoon circulation. This study with related data such as sea surface temperature, chlorophyll concetration and mixed layer depth that derived from satellite imaging data National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR), Aqua/Modis and sea viewing Wide Field-of-view Sensor(Sea WiFS) shows as magnificent confirmation pattern. So applying WSC to recoqnize upwelling zone is alternatively way as climatic approach to maps potential fertilizing of sea water in maritime-continent Indonesia.  BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14102 International Journal of Remote Sensing and Earth Sciences; Vol. 5 (2008); 46-56 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14102/10966 Copyright (c) 2008 Author (s) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14103 2025-11-26T03:34:09Z ijreses:ART

INTERNAL WAVES DYNAMICS IN THE LOMBOK STRAIT STUDIED BY A NUMERICAL MODEL NINING SARI NINGSIH RIMA RAHMAYANI SAFWAN HADI IRSAN S. BROJONEGORO internal wave non-hydrostatic approximation solitary waves thermal plumes A baroclinic 3D hydrodynamic model with the non-hydrostatic approximation called Massachusetts Institute of Technology Global Circulation Model (MIT gcm) has been applied to simulate the generation of internal tidal bores and their disintegration into internal solitary waves in the Strait of Lombok. Numerical simulation have been carried out by incorporating seasonal variations of the stratification of the water body, which exist during the first transitional monsoon, the east monsoon, the second transitional monsoon, and the west monsoon. Our simulation yields the results that the existence of the sill at the southern part of the Lombok Strait, strong tidal flow, and a stratified fluid, play an important role in forming some short of divergence and convergence area as an indication of the birth of internal waves, which are simulated on the both sides of the sill. The simulated results reproduce reasonably well the basic features of internal waves in the Strait of Lombok as captured by the Synthetic Aperture Radar (SAR) from the European Remote Sensing (ERS) satellites ERS 1 and ERS 2, such as a north-south asymmetry, propagation speeds, average amplitudes and wavelengths, and solution packets. Similiar to observations made by National Oceanic and Atmospheric Administration (NOAA) satellites, the simulation results also showed the intrusion of warmwater from thePacific Ocean into the Indian Ocean and the exitence of well-developmed thermal plume at south of the sill. Seasonal variations of interface depth of thermocline and the density difference between the stratified layers influence magnitudes of the amplitudes and wavelengths of the internal waves and solitons, and the distance of thermal plume in the Lombok Strait. It is found that during the monsoon transition periods and the west monson, the amplitudes of internal waves and solitons at the southern part of the strait is apparently larger than those at the northern one, whereas during the east monsoon, the wave amplitudes is large north of the sill than south of it. Meanwhile, the propagation speeds of northward propagating internal solitary waves (0.71-2.67m per s) are stronger than southward propagating ones (0.21-1.53 m per s) throughout the monsoon periods. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14103 International Journal of Remote Sensing and Earth Sciences; Vol. 5 (2008); 17-33 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14103/10962 Copyright (c) 2008 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14104 2025-11-26T03:34:09Z ijreses:ART

DROUGHT MONITORING OVER PADDY FIELD AREA IN INDRAMAYU DISTRICT, WEST JAVA USING REMOTELY SENSED INDICES PARWATI MIAO JUNGANG ORBITA ROSWINTIARTI Agricultural drought Meteorological drought Standardized Precipitation Index Temperature Condition Index Vegetation Condition Index In this research, several meteorological and agricultural drought indices based on remote sensing data are built for drought monitoring over paddy area in Indramayu District, West Java, Indonesia. The meteorological drought index of Standardized Precipitation Index (SPI) is developed from monthly Outgoing Long Wave Radiation (OLR) data from 1980 to 2005. The SPI represents the deficient of precipitation. Meanwhile, the agricultural drought of Vegetation Health Index (VHI) was developed from daily Moderate-resolution ImagingSpectroradiometer (MODIS) data during dry season (May-August) 2003-2006. The VHI was designed to monitoring vegetation health, soil moisture, and thermal conditions. The result shows that the agricultural drought occurate in Indramayu District, especially in the northern and southern part during the dry season in 2003 and 2004. It is found that there is a strong correlation between VHI and soil moisture measured in the field (r=0.84). BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14104 International Journal of Remote Sensing and Earth Sciences; Vol. 5 (2008); 34-45 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14104/10964 Copyright (c) 2008 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14105 2025-11-26T03:58:39Z ijreses:ART

THE DEVELOPMENT RESEARCH OF THE FISHING BOAT DISTINCTION TECHNIQUE BY SATELLITE-ONBOARD HIGH RESOLUTION OPTICAL SENSOR — DISTINCTION TECHNIQUE USING IKONOS DATA T. Moriyama H. Tameishi J. Suwa S. Kanno Y. Sugimori T. Osawa M. Koiwa IKONOS image SPOT ALOS image high resolution image alogarithm nearest neighbor interpolation cubic convolution interpolation This paper describes the vessel distinction algorithm by using radiance silhoutte algorithm for IKONOS data. Although original TKONOS image has high spatial resolution about 1 m, it is difficult to identify whole feature of the vessel. The newly developed algorithm named "Radiance Silhoutte Analysis Algorithm" can estimate entire length, full width and bridge location of the vessel in high accuracy. By using targeted vessels, it is evaluated the algorithm has sufficient accuracy for vessel distinction. The research also covers synthetic collation decision by using vessel type axtraction algorithm. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14105 International Journal of Remote Sensing and Earth Sciences; Vol. 1 No. 1 (2004); 10-23 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14105/10965 Copyright (c) 2005 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0

oai:ejournal.brin.go.id:article/14106 2025-11-26T03:07:34Z ijreses:ART

STUDY ON LAND SURFACE TEMPERATURE CHARACTERISTICS OF HOT MUD ERUPTION IN EAST JAVA, INDONESIA Luhur Bayuaji Hiroshi Watanabe Hideyuki Tonooka Josaphat Tetuko Sri Sumantyo Hiroaki Kuze ASTER TIR ASTER VNIR Hot mud volcano Temperature emissivity separation Water vapor scaling method hot mud has erupted in sidoarjo, east Java, Indonesia since 29 May 2006. It started as natural gas exploration project and punctured a geological structure at a depth of 2,8 km, releasing unprecedented volume of hot mud volcano (5x104 mcubix per day). By November 2006, it was estimated that hot mud had spread over (2,89 plus minus 0,10) x 106 m, swamping several villages with more than 10.000 people evacuated. In this research, by employing the advantage of spatial perspective of remote sensing imagery, the extent of hot mud spreading area and temperature distributions are derived from satellite images of the advanced Spaceborn Thermal Emission and Reflection Radiometer (ASTER) sensor onboard the Terra satellite. The mud spreading are was calculated using three visible or near infrared channels having a resolution of 15 m. Temperature distributions were calculated using the temperature or emissivity separation (TES) method on five thermal infraredchannels with a resolution of 90 m. The standard and water vapor scaling (WVS) methods were applied in the atmospheric correction process prior to the TES process. The result showed that the mud continued spreading during five months after the eruption. After 3-5 months from the eruption, the estimated temperature was about 30-69 degree of celcius in the mud spreading area. Also, estimations of the volume and weight of the hot mud were made on the basis of the visible of level 3 A product of ASTER and ground survey data. Keyword ASTER TIR, ASTER VNIR, Hot mud volcano, Temperature emissivity separation, Water vapor scaling method. BRIN 2025-11-26 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Peer-reviewed Article application/pdf https://ejournal.brin.go.id/ijreses/article/view/14106 International Journal of Remote Sensing and Earth Sciences; Vol. 6 (2009); 14-28 2549-516X 0216-6739 eng https://ejournal.brin.go.id/ijreses/article/view/14106/10968 Copyright (c) 2009 Author (S) https://creativecommons.org/licenses/by-nc-sa/4.0 46c85abcf4d871b960e87682011f3785