Fusion of SAR images for flood extent mapping in northern peninsula Malaysia

Dutsenwai, Hafsat Saleh; Mijinyawa, Abubakar; Ahmad, Baharin Bin; Tanko, Adamu. I.

International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 3, Issue 12 (December 2016), Pages: 37-48

Title: Fusion of SAR images for flood extent mapping in northern peninsula Malaysia

Author(s): Hafsat Saleh Dutsenwai ^{1, 2}, Baharin Bin Ahmad ^3,*, Abubakar Mijinyawa ⁴, Adamu. I. Tanko ²

Affiliation(s):

¹Department of Remote Sensing, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia (UTM), Johor, Malaysia
²Department of Geography, Faculty of Earth and Environmental Sciences, Bayero University Kano, BUK, Nigeria
³Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia (UTM), Johor, Malaysia
⁴Department of Geoscience and Petroleum Engineering, Universiti Teknologi PETRONAS (UTP), Perak, Malaysia

https://doi.org/10.21833/ijaas.2016.12.006

Full Text - PDF XML

Abstract:

This study aimed at mapping the flood extents in the northern peninsula Malaysia in order to contribute to the flood disaster eradication by extracting more and better information through the fusion of RadarSat 1 and TerraSAR-X images. Principal Component Analysis and Brovey Transform (BT) techniques were used. The best principal component of the PCA, which is the PC2 was classified and compared with the classified BT image using Maximum likelihood (ML) and support Vector Machine (SVM). The results indicated that the classification of the BT image using SVM has higher accuracy with an overall of 70.9615% as well as kappa coefficient of 0.3418. This method showed relative improvement on the classification of the flooded and non-flooded areas which were used to produce the flood extent Map that was further verified with the DEM of the area. The final results in this study showed more information on the areas that are affected by the floods especially the extents which became more visible after the classification of the fused images.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Flood extent, RadarSat-1, TerraSAR-X, Mapping, PCA, Brovey transform

Article History: Received 1 September 2016, Received in revised form 25 November 2016, Accepted 27 November 2016

Digital Object Identifier: https://doi.org/10.21833/ijaas.2016.12.006

Citation:

Dutsenwai HS, Ahmad BB, Mijinyawa A, and Tanko AI (2016). Fusion of SAR images for flood extent mapping in northern peninsula Malaysia. International Journal of Advanced and Applied Sciences, 3(12): 37-48

http://www.science-gate.com/IJAAS/V3I12/Dutsenwai.html

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