Change detection in urban context with multitemporal ERS-SAR images by using data fusion approach

We propose in this paper, a new method for change detection in urban context with multitemporal SAR images. The method operates in two steps: change measures computation between the two SAR images, and the fusion of previous change measures with an interpretation measure, used as prior information, with the help of fuzzy subsets theory. This interpretation attribute comes from an optical image, across NDVI (Normalized Difference Vegetation Index). The proposed method is applied on two ERS-SAR images and one multispectral optical SPOT (2001) image of the urban area of Douala city, in order to appreciate changes between (1994) and (1999). The method allows the global change analysis in urban context at a pixel scale and at an area larger than a pixel.