SEGMENTATION OF BUILDINGS BASED ON HIGH RESOLUTION PERSISTENT SCATTERER POINT CLOUDS
Keywords: Persistent Scatterer Interferometry (PSI), Synthetic Aperture Radar, Airborn Laser Scanning, Data Fusion, Clustering, Reverse Geocoding, Time Series Analysis, Building Information Modeling, Data Mining
Abstract. Integrating differential synthetic aperture radar measurements into building information modeling systems requires a mapping of these measurement points onto structural parts of the building. We use a reverse geocoding approach to project building footprints into slant-range geometry, which helps to accurately assign PS points to single building identities. By treating the deformation time series as points in a high dimensional feature space, we can use dimensional reduction and clustering techniques to extract clusters of points that show a similar movement behavior. We visualize these clusters by mapping them onto ground truth, using laser scanning point clouds. Our approach segments buildings into plausible parts.