Abstract
The space borne synthetic aperture radar systems acquires imagery with very high spatial resolution, supporting various important application scenarios, such as damage assessment in urban areas after natural disasters. To ensure a reliable, consistent, and fast extraction of the image from the complex synthetic aperture radar scenes. Focusing on the analysis of urban areas, which is of the prime interest of VHR SAR. In this work we proposed a normal method for the automatic detection and 2-D reconstruction of radar foot prints. The method is based on the extraction of a set of low-level features from the images and on their composition to more structured primitives using a production system. The semantic meaning represents the probability that a primitive belongs to a certain scattering class and has been defined in order to compensate for the lack of detectable features in images. The efficiency of the proposed method is demonstrated by processing a 1-m resolution TerraSAR-X spot beam scene containing flat and gable-roof buildings at various settings. The results show that the method has a high overall detection rate and that radar foot prints are well reconstructed, in particular for medium and large buildings.