Thresholding technique for flood extent mapping using dual polarization ENVISAT ASAR data

The research paper explores an optimum water extraction technique using synthetic aperture radar (SAR) data to give the flood inundation map for irregular flood scenario, in which the planned algorithm depends on thresholding technique using MRS amplitude SAR data. For classification, supervised maximum likelihood method is used, and gamma filtering technique was used for speckle removal. Since water layer in SAR data has low amplitude value, thresholding technique for amplitude SAR data could efficiently take out water layer. The mean backscatter basics of water layers in SAR data is not to be compared with inundated regions caused by sharp release and is not considered as a terrain value. The speckle filtering method was used for the power generated noise subtraction using a window size 5x5. The threshold values were calculated from backscatter values and their average was taken as threshold, which gives clear difference of backscatter values between the land and the water in the river and the flood plain areas. The maximum likelihood classifier provides 99% overall accuracy. The Landsat 5 TM data was used in this research for delineating water feature and flood accurately. The results obtained from SAR data were validated with Landsat TM data. Finally, the flood inundation map using optical data and SAR data was generated.