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With the launch of the German TerraSAR-X system, a new generation of high-resolution spaceborne SAR data is available. This opens new perspectives and challenges for the automatic interpretation of urban environments. In fact, a rich information content, previously hidden or not clearly distinguishable in low resolution images such as urban structures (small buildings, vehicles, etc), is now disclosed. However, only proper approaches are able to retrieve automatically this new detailed information. This paper provides solutions for the semi-automatic interpretation and mapping of urban areas using the high resolution provided by TerraSAR-X data. Our solutions take into the increase, with the high resolution, of the visibility of some man-made structures whose scattering response has improved with the high frequency X-band SAR sensor carried by the TerraSAR-X system. They are mainly based on two steps. Firstly, we extract and describe two kinds of information: backscattering and statistical. Secondly, we propose to use information fusion techniques where intelligence has been introduced and enhanced in the way the different information is processed or treated, so that accurate mapping of urban areas could be reached. This mapping is performed through semantic categorization and retrieval of the different scene contents. Promising improvements and real progress toward automatic urban area mapping have been achieved using TerraSAR-X data.