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Spectral and spatial resolution analysis of multi sensor satellite data for coral reef mapping : Tioman Island, Malaysia.


Citation

Pradhan, Biswajeet and Kabiri, Keivan (2012) Spectral and spatial resolution analysis of multi sensor satellite data for coral reef mapping : Tioman Island, Malaysia. In: 39th Committee on Space Research (COSPAR) Scientific Assembly, 14-22 Julai 2012, India. .

Abstract

This paper describes an assessment of coral reef mapping using multi sensor satellite images such as Landsat ETM, SPOT and IKONOS images for Tioman Island, Malaysia. The study area is known to be one of the best Islands in South East Asia for its unique collection of diversified coral reefs and serves host to thousands of tourists every year. For the coral reef identification, classification and analysis, Landsat ETM, SPOT and IKONOS images were collected processed and classified using hierarchical classification schemes. At first, Decision tree classification method was implemented to separate three main land cover classes i.e. water, rural and vegetation and then maximum likelihood supervised classification method was used to classify these main classes. The accuracy of the classification result is evaluated by a separated test sample set, which is selected based on the fieldwork survey and view interpretation from IKONOS image. Few types of ancillary data in used are: (a) DGPS ground control points; (b) Water quality parameters measured by Hydrolab DS4a; (c) Sea-bed substrates spectrum measured by Unispec and; (d) Landcover observation photos along Tioman island coastal area. The overall accuracy of the final classification result obtained was 92.25% with the kappa coefficient is 0.8940.


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Additional Metadata

Item Type: Conference or Workshop Item (Paper)
Subject: Coral reef ecology - Malaysia.
Subject: Spatial analysis.
Subject: Coral reefs and islands - Malaysia.
Divisions: Institute of Advanced Technology
Keywords: Coral reef; Multi-spectral segmentation; Pixel-based classification; Decision tree; Tioman Island.
Depositing User: Samsida Samsudin
Date Deposited: 24 Oct 2013 08:18
Last Modified: 01 Apr 2014 04:03
URI: http://psasir.upm.edu.my/id/eprint/25930
Statistic Details: View Download Statistic

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