Abstract
Abstract. Due to the all-weather data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR) plays an important role in remote sensing applications like change detection. However, because of the complex geometric mapping of buildings in urban areas, SAR images are often hard to interpret. SAR simulation techniques ease the visual interpretation of SAR images, while fully automatic interpretation is still a challenge. This paper presents a method for supporting the interpretation of high resolution SAR images with simulated radar images using a LiDAR digital surface model (DSM). Line features are extracted from the simulated and real SAR images and used for matching. A single building model is generated from the DSM and used for building recognition in the SAR image. An application for the concept is presented for the city centre of Munich where the comparison of the simulation to the TerraSAR-X data shows a good similarity. Based on the result of simulation and matching, special features (e.g. like double bounce lines, shadow areas etc.) can be automatically indicated in SAR image.
Highlights
Because of the all-weather and all-time data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR) plays an important role in remote sensing applications like change detection, earth mapping etc
Line features are extracted from the simulated SAR image and the real SAR image and used for matching of the images
Two subpixel precise translation parameters are calculated from the matching result and enable a direct overlay of all simulated images on the real SAR image
Summary
Because of the all-weather and all-time data acquisition capabilities, high resolution space borne Synthetic Aperture Radar (SAR) plays an important role in remote sensing applications like change detection, earth mapping etc. Some other special features like roads (Tupin et al, 1998) and double bounce lines (Wegner et al, 2010) can be directly extracted from SAR images. To analyse the influence of neighbouring buildings in SAR images, we generate a digital elevation model (DEM) using a single building model for simulation. We extract line features from the simulated and real SAR image and use them for the matching of both images. An analysis of the features in SAR images using exactly overlaid simulated images is presented thereafter.
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