The worldwide urban growth leads to an increase in impervious surface, which in turn has many negative consequences for the environment. For an assessment of these phenomena in this study first TerraSAR-X radar data are classified using a knowledge-based approach to detect the extent of urban areas. Subsequently within this area the percentage of imperviousness is estimated by using a Support Vector Regression model with optical Landsat images and high resolution aerial pictures. These methods were developed for urban areas in Germany and transferred to Cape Town, South Africa. The overall accuracy of the settlement detection is 82.3 % and the mean error of the percentage of imperviousness is 14.1 % with a local regression model. It was also possible to apply a model generated for the German city of Munich for Cape Town but the absolute mean error increased to 32.8 %, indicating the necessity to further improve the radiometric adjustment.