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Using Remote Sensing to Assess Tsunami-induced Impacts on Coastal Forest Ecosystems at the Andaman Sea Coast of Thailand : Volume 10, Issue 4 (13/04/2010)

By Roemer, H.

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Book Id: WPLBN0003991827
Format Type: PDF Article :
File Size: Pages 17
Reproduction Date: 2015

Title: Using Remote Sensing to Assess Tsunami-induced Impacts on Coastal Forest Ecosystems at the Andaman Sea Coast of Thailand : Volume 10, Issue 4 (13/04/2010)  
Author: Roemer, H.
Volume: Vol. 10, Issue 4
Language: English
Subject: Science, Natural, Hazards
Collections: Periodicals: Journal and Magazine Collection (Contemporary), Copernicus GmbH
Publication Date:
Publisher: Copernicus Gmbh, Göttingen, Germany
Member Page: Copernicus Publications


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Kaiser, G., Sterr, H., Ludwig, R., & Roemer, H. (2010). Using Remote Sensing to Assess Tsunami-induced Impacts on Coastal Forest Ecosystems at the Andaman Sea Coast of Thailand : Volume 10, Issue 4 (13/04/2010). Retrieved from

Description: Department of Geography, Christian-Albrechts-Universität zu Kiel, Kiel, Germany. The December 2004 tsunami strongly impacted coastal ecosystems along the Andaman Sea coast of Thailand. In this paper tsunami-induced damage of five different coastal forest ecosystems at the Phang-Nga province coast is analysed with a remote sensing driven approach based on multi-date IKONOS imagery. Two change detection algorithms, change vector analysis (CVA) and direct multi-date classification (DMC), are applied and compared regarding their applicability to assess tsunami impacts. The analysis shows that DMC outperforms CVA in terms of accuracy (Kappa values for DMC ranging between 0.947 and 0.950 and between 0.610–0.730 for CVA respectively) and the degree of detail of the created change classes. Results from DMC show that mangroves were the worst damaged among the five forests, with a 55% of directly damaged forest in the study area, followed by casuarina forest and coconut plantation. Additionally this study points out the uncertainties in both methods which are mainly due to a lack of ground truth information for the time between the two acquisition dates of satellite images. The created damage maps help to better understand the way the tsunami impacted coastal forests and give basic information for estimating tsunami sensitivity of coastal forests.

Using remote sensing to assess tsunami-induced impacts on coastal forest ecosystems at the Andaman Sea coast of Thailand

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