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

Reza Reza, Erwin Erwin

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.


Keywords


remote sensing; peatland; NDVI; maximum likelihood estimation

Full Text:

PDF

References


IDRIS. Guide to GIS and Image Processing Volume 1

USAID/INDONESIA, (2006). Satellite Imagery Basic Information Availability, Characteristics and How to Purchase it

Minakshi Kumar. Photogrammetry and Remote Sensing Division. Indian Institute of Remote Sensing

D.Nagesh Kumar, IISc,Banglore. Remote Sensing-Digital image processing – Image Enhancement

B.Sreenivas, B.N. Chary. Pre-processing of Satellite Using Digital Image Processing


Refbacks

  • There are currently no refbacks.