Generation of Coarse 3d Models of Urban Areas from High Resolution Stereo Satellite Images

With the emergence of more and more satellites delivering very high resolution (VHR) imagery with ground sampling distances in the range of one meter or below the generation of three dimensional urban models directly from space may become possible. Such models are required for many applications in areas where no up-to-date detailed urban mapping exists like in developing countries. Besides the creation and updating of maps from sprawling urban settlements, such three dimensional models are also very useful for simulation and planning. For example simulations of catastrophic events like flooding, tsunamis or earth quakes rely on digital terrain models (DTM) populated with three-dimensional man made and natural objects. Using VHR satellite imagery is often the faster and cheaper alternative to acquiring aerial photos or even laser DEMs or in some times even the sole source of information for remote areas. In this paper a method for an automatic processing chain for urban modeling based on stereo images from VHR satellites is proposed. After import and preprocessing of the images a digital surface model (DSM) is derived from the stereo data. Subsequently a digital terrain model (DTM) and true ortho images are generated based on the DSM. Using a high objects mask and a vegetation mask based on the normalized difference vegetation index (NDVI) a coarse classification will be derived and suitable models for the detected objects (e.g. houses, trees, ...) are selected and finally the 3D models get exported in a suitable format like VRML.