Annual Research Seminar
Vol 4, No 1 (2018): ARS 2018

IDENTIFIKASI LAHAN GAMBUT PADA CITRA SATELIT DENGAN NDVI MENGGUNAKAN METODE MAXIMUM LIKELIHOOD ESTIMATION

Reza Reza (Universitas Sriwijaya)
Erwin Erwin (Universitas Sriwijaya)



Article Info

Publish Date
29 May 2019

Abstract

This paper presents the model of remote sensing technique to classify peatland cover types in Sumatera Selatan Province. This study uses Landsat-8 satellite data to identify the type of peatland cover in Ogan komering Ilir. This area were picked up as pilot project ares for this research, because these areas had many peatland spot historically on last few years. The result show how this approach can be used lo peatland cover classification and for predicting peat in locations within the map unit quickly. The classification of peatland was done using Maximum likelihood estimation by using NDVI single band variables data. The result of data processing of landsat 8 satellite image shows that 764.950,4 hectares of Ogan Komering Ilir area is composed of peatland divided primary peatland and disturbed peatland. Besed on the results of landsat 8 imsge processing  data can be seen some areas of Ogan Komering Ilir indicate green color means the peat area.

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