High resolution stereo satellite imagery is now well suited for the creation of digital surface models (DSM) in urban areas due to recent developments in data resolution, quality and collection capabilities. A system for highly automated and operational DSM and orthoimage generation based on WorldView-2 imagery is presented using dense matching methodology, with emphasis on the usage of tri-stereo data for the generation of optimized DSMs. Due to constraints given by the three images, which allow six different pair-wise matchings (including left and right matching of each pair), robust results containing only very few outliers can be generated. The proposed system processes level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and exhibit a lower absolute accuracy than the ground resolution of approximately 0.5 m. In order to use the images for orthorectification or DSM generation, a bias or affine RPC correction is required, which can be achieved through a bundle adjusment using further scenes of the covered area from different dates. Furthermore these DSMs can be used to generate higher level products like digital terrain models (DTM), extracted single 3D objects like buildings and for automatic 3D change detection analysis. DLR-IMF and GAF AG developed and implemented within a close co-operation an operational workflow which now provides operational services based on multi source tri-stereo satellite data. The DSM processing is shortly described, some results of generated DSMs are shown and also examples for higher level products are given in the paper.
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