Simulation Based Change Detection between DSM and High Resolution SAR Image

Change analysis for remote sensing data taken at different times over urban areas provides meaningful information like the expansion of cities. This paper presents a method for the generation of a coregistered geocoded simulated SAR image using a LiDAR digital surface model (DSM) and the comparison to a real SAR image for the purpose of change detection. The DSM and metadata of the SAR image are used for the geocoding of the simulated image, while a line extraction and matching algorithm is used to compensate small shifts between the two images. Afterwards the shadow area in the simulated image is extracted and the corresponding mask is used to analyze the real SAR image in order to detect the changes. An application of the proposed concept is presented for the city centre of Munich where the comparison with the TerraSAR-X GEC product shows a good result. The detected positive changes (new buildings) are compared to a 3D change reference map and show a good correspondence.