UTILIZATION OF MULTI TEMPORAL SAR DATA FOR FOREST MAPPING MODEL DEVELOPMENT
DOI:
https://doi.org/10.30536/j.ijreses.2013.v10.a1844Keywords:
Forest mapping, multi temporal, ALOS PALSAR, threshold, LANDSATAbstract
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.
Downloads
Published
Issue
Section
License
Copyright (c) 2013 Author (s)

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright Notice for the International Journal of Remote Sensing and Earth Sciences (IJReSES)
Copyright Holder: Author(s).
By submitting an article to IJReSES, author(s) agree to the following terms:
1. Grant of Publishing Rights: Authors grant IJReSES the license to publish the article and to identify itself as the original publisher. This includes the right to make the article available in all forms and media.
2. Commercial Rights: Authors grant IJReSES the rights to produce and sell hardcopy volumes of the journal. These volumes may be purchased by libraries, individuals, or other entities.
3. Third-Party Use: Authors agree to allow any third party to freely use the article, provided that the original authors are credited and the article is cited appropriately. This facilitates the dissemination and impact of the work.
4. Creative Commons License: The article is distributed under the Creative Commons Attribution non Commercial Share Alike 4.0 License (CC BY-NC-SA 4.0). This license allows others to distribute, remix, adapt, and build upon the work, even commercially, as long as the original author is credited for the original creation.
5. Associated Published Material: Unless otherwise stated, any associated published material (such as supplementary data, graphics, and multimedia) is distributed under the same CC BY-NC-SA 4.0 License.
By adhering to these terms, authors ensure the wide dissemination and accessibility of their work, contributing to the advancement of knowledge in the fields of remote sensing and earth sciences.


