Fusion of high resolution SAR images with optical and GIS data and its application to change detection in urban areas

SAR images are perfectly suited for change detection, given that they are not affected by different sun illumination conditions and/or clouds. There is potential to improve the SAR change detection results by taking into account prior knowledge of the scene, which can be obtained from other sources of information such as high resolution optical images and data from Geographic Information Systems (GIS). In this paper we will describe how information about the scene geometry and a classification of the scene into different semantic classes can be obtained from the optical and GIS data, and how this information can be transformed to the slant-range coordinate system of SAR images so that it can be easily used in the change detection process. Finally, we will show some initial results that illustrate the benefits of using this information about the scene during the change detection.