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

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. (C) 2016 The Authors. Published by IASE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).