Pemetaan Mangrove Kepulauan Lease, Provinsi Maluku Menggunakan Data Multi-Temporal dan Multi-Sensor Citra Satelit Landsat

Authors

  • Sam Wouthuyzen Loka Peningkatan Kompetensi Sumber Daya Manusia Oseanografi, Pulau Pari, LIPI
  • Fasmi Ahmad Pusat Penelitian Oseanografi LIPI

DOI:

https://doi.org/10.14203/oldi.2018.v3i1.134

Keywords:

Mangrove, Landsat, Multi-temporal, Multi-sensors, maps, Lease Islands

Abstract

Mangrove Mapping of The Lease Islands, Maluku Province Using Multi-Temporal And Multi-Sensor Of Landsat Satellite Images. Mangrove mapping in the Lease Islands, Maluku Province has been done, but using only a single date satellite image. Therefore, it is difficult to know the dynamics of their changes.  The aim of this study is to map mangroves every 5 year (1985-2015) using multi-sensors (MSS, TM, ETM+ and OLI) of Landsat and field data. Supervised classification using maximum likelihood was used for classifying mangrove and other habitats, and counting their areas. Results showed that mangrove in the Saparua and Nusalaut Islands, consisted of 22 and 13 species, respectively, with the longest distribution along the cost line of Tuhaha Bay due to freshwater supplay from the surrounding river, while the rest are grown in the hardy reef flat substrates. The mean overall acurracies of the maps was good enough (74.7%), except for one Landsat-5 TM and Landat-8 OLI because of the influences of cloud cover or haze.  During 30 years, the areas of mangrove are relatively stable since they are protected by local wisdom called "Kewang". The highest bias of 11.4% that made the areas of mangrove increase or decrease was not due to the utilization or conversion of mangrove, but mainly due to the influences of cloud cover/haze and the geometric differences among Landsat sensors. In the near future, the OBIA method should be try, because it seems to be able to produce mangrove maps with better accuracy.

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Published

2026-02-23

How to Cite

Sam Wouthuyzen, & Fasmi Ahmad. (2026). Pemetaan Mangrove Kepulauan Lease, Provinsi Maluku Menggunakan Data Multi-Temporal dan Multi-Sensor Citra Satelit Landsat. OLDI (Oseanologi Dan Limnologi Di Indonesia), 3(1), 19–37. https://doi.org/10.14203/oldi.2018.v3i1.134

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