Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia

H. S. Lim; M. Z. MatJafri; K. Abdullah; A. N. Alias; N. Mohd. Saleh; C. J. Wong; M. S. Surbakti

doi:10.1117/12.777256

17 March 2008 Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia

H. S. Lim, M. Z. MatJafri, K. Abdullah, A. N. Alias, N. Mohd. Saleh, C. J. Wong, M. S. Surbakti

Proceedings Volume 6977, Optical Pattern Recognition XIX; 69770H (2008) https://doi.org/10.1117/12.777256
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

Remote sensing offers an important means of detecting and analyzing temporal changes occurring in our landscape. This research used remote sensing to quantify land use/land cover changes at the Nanggroe Aceh Darussalam (Nad) province, Indonesia on a regional scale. The objective of this paper is to assess the changed produced from the analysis of Landsat TM data. A Landsat TM image was used to develop land cover classification map for the 27 March 2005. Four supervised classifications techniques (Maximum Likelihood, Minimum Distance-to- Mean, Parallelepiped and Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier) were performed to the satellite image. Training sites and accuracy assessment were needed for supervised classification techniques. The training sites were established using polygons based on the colour image. High detection accuracy (>80%) and overall Kappa (>0.80) were achieved by the Parallelepiped with Maximum Likelihood Classifier Tiebreaker classifier in this study. This preliminary study has produced a promising result. This indicates that land cover mapping can be carried out using remote sensing classification method of the satellite digital imagery.

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H. S. Lim, M. Z. MatJafri, K. Abdullah, A. N. Alias, N. Mohd. Saleh, C. J. Wong, and M. S. Surbakti "Land cover mapping after the tsunami event over Nanggroe Aceh Darussalam (NAD) province, Indonesia", Proc. SPIE 6977, Optical Pattern Recognition XIX, 69770H (17 March 2008); https://doi.org/10.1117/12.777256

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KEYWORDS

Earth observing sensors

Remote sensing

Image classification

Satellites

Landsat

Satellite imaging

Accuracy assessment

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