With the availability of very high resolution (VHR) satellite imagesfast and relatively cheap investigations of large urban areas incomparison to aerial photography are possible. In urban areas a predominantuse of satellite data is the generation of city models for applicationslike mobile phone signal propagation or flooding and catastrophesimulation. Since more and more large and quick growing cities emergein developing countries, monitoring and modeling of these areas fromsatellite will be the cheapest if not the only possibility. Mostof the actual methods used for the generation of city models dependon mainly manual work. A method for automatic derivation of -in afirst step very coarse -models of urban environments will be of greatuse. In this paper a production chain and the methods used for sucha automatic modeling is presented. The method is based on stereoimages from VHR satellite stereo imagery provided, e.g., by IKONOSor QuickBird. In a first step a digital surface model (DSM) is derivedfrom the stereo data. Subsequently a digital terrain model (DTM)and ortho images are created. Based on the local height differencesbetween DSM and DTM and the normalized difference vegetation index(NDVI) a coarse classification can be made. Upon this classificationobject models can be selected and object parameters can be adaptedto create an object-based representation of the satellite image scene.The method used is evaluated and the results are discussed.
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With the availability of very high resolution (VHR) satellite imagesfast and relatively cheap investigations of large urban areas incomparison to aerial photography are possible. In urban areas a predominantuse of satellite data is the generation of city models for applicationslike mobile phone signal propagation or flooding and catastrophesimulation. Since more and more large and quick growing cities emergein developing countries, monitoring and modeling of these areas fromsatellite will be the...
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