It is very important to extract water and settlement areas from SAR images in practical applications. In this paper the single band and single-polarization Radarsat-1 SAR image is used to water and settlement area extraction. Firstly

the statistic structure information of sample image is analyzed using semi-variogram to determine the optimum parameters for textural information extraction. In order to establish the multi-dimension feature space for image classification

the textural measures such as mean

angle second moment and entropy have been calculated based on grey level co-occurrence matrix method. Then the water and settlement area information can be enhanced effectively using false color composite method. Three types of sample such as water

settlement and other are collected as training samples

and the image data are processed using support vector machine classification method. Finally

the image fusion on the target level between classification result image and NDVI image is conducted in order to eliminate the mountain influence

and the water and settlement areas are extracted accurately with a total classification accuracy of 8257%

and Kappa coefficient of 0.58.