Abstract
Among all the issues involved in Geographic Information Science, automating the update of 2D building databases is a crucial and challenging issue. Such an update usually starts out with a manual change detection process. The main goal of this paper is to present a new method to automate the detection of changes in a 2D building database, starting from satellite images. The workflow of our approach is divided into 2 phases. Primitives, extracted from multiple images or from a correlation Digital Surface Model (DSM), are firstly collected for each building and matched with primitives derived from the existing database to achieve a final decision about acceptance or rejection. A specific algorithm, based on the DSM and a computed Digital Terrain Model (DTM), is subsequently used to extract new buildings. The method is here introduced and tested in two test areas, very different regarding the land use and topography. The outcomes of the method are assessed and show the good performance of our system, especially in terms of completeness, robustness and transferability.
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Champion, N., Stamon, G., Pierrot-Deseilligny, M. (2009). Automatic Revision of 2D Building Databases from High Resolution Satellite Imagery: A 3D Photogrammetric Approach. In: Sester, M., Bernard, L., Paelke, V. (eds) Advances in GIScience. Lecture Notes in Geoinformation and Cartography. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00318-9_3
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DOI: https://doi.org/10.1007/978-3-642-00318-9_3
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