Share Email Print

Proceedings Paper

Application of remote sensing in coastal change detection after the tsunami event in Indonesia
Author(s): H. S. Lim; M. Z. MatJafri; K. Abdullah; N. Mohd. Saleh; M. S. Surbakti
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Shoreline mapping and shoreline change detection are critical in many coastal zone applications. This study focuses on applying remote sensing technology to identify and assess coastal changes in the Banda Aceh, Indonesia. Major changes to land cover were found along the coastal line. Using remote sensing data to detect coastal line change requires high spatial resolution data. In this study, two high spatial data with 30 meter resolution of Landsat TM images captured before and after the Tsunami event were acquired for this purpose. The two satellite images was overlain and compared with pre-Tsunami imagery and with after Tsunami. The two Landsat TM images also were used to generate land cover classification maps for the 24 December 2004 and 27 March 2005, before and after the Tsunami event respectively. The standard supervised classifier was performed to the satellite images such as the Maximum Likelihood, Minimum Distance-to-mean and Parallelepiped. High overall accuracy (>80%) and Kappa coefficient (>0.80) was achieved by the Maximum Likelihood classifier in this study. Estimation of the damage areas between the two dated was estimated from the different between the two classified land cover maps. Visible damage could be seen in either before and after image pair. The visible damage land areas were determined and draw out using the polygon tool included in the PCI Geomatica image processing software. The final set of polygons containing the major changes in the coastal line. An overview of the coastal line changes using Landsat TM images is also presented in this study. This study provided useful information that helps local decision makers make better plan and land management choices.

Paper Details

Date Published: 1 October 2008
PDF: 8 pages
Proc. SPIE 7110, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII, 71100C (1 October 2008); doi: 10.1117/12.800061
Show Author Affiliations
H. S. Lim, Univ. Sains Malaysia (Malaysia)
M. Z. MatJafri, Univ. Sains Malaysia (Malaysia)
K. Abdullah, Univ. Sains Malaysia (Malaysia)
N. Mohd. Saleh, Univ. Sains Malaysia (Malaysia)
M. S. Surbakti, Syiah Kuala Univ. (Indonesia)

Published in SPIE Proceedings Vol. 7110:
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VIII
Ulrich Michel; Daniel L. Civco; Manfred Ehlers; Hermann J. Kaufmann, Editor(s)

© SPIE. Terms of Use
Back to Top