Fusion of InSAR and GIS data for 3D building reconstruction and change detection

The new generation of space-borne high resolution SAR sensors such as TerraSAR-X, SAR-Lupe or Cosmo-SkyMed provides SAR images of 1-3m spatial resolution or even below in special spotlight modes. Naturally, the development of methods to automatically derive detailed cartographic information of both rural and urban areas from this kind of data is a major issue driven by these missions. Since SAR is an active system and largely independent from weather conditions; it is furthermore an attractive imaging technology for rapidly acquiring area-wide information of regions hit by disasters such as floodings, landslides, or earthquakes. Thus, the development of automatic methods for damage analysis or - generally - change detection is another important issue. For such kind of tasks existing Geodata available from Geographic Information Systems (GIS) have to be adjusted with current SAR data. In this paper an approach for 3D building reconstruction based on multi-temporal information fusion by exploiting GIS and InSAR data is presented. Thereby, GIS data consisting of building footprints are used as initial information. The simulation exploits building hypotheses, which are based on the given 2D footprint and an assumed building height, and provides as result synthetic InSAR phases. An iterative adjustment between simulated and measured real InSAR phases enables the reconstruction of the current building shape. Our approach is tested on single-pass airborne InSAR data.