Facade Reconstruction Using Multiview Spaceborne TomoSAR Point Clouds

Recent advances in very high resolution tomographic synthetic aperture radar inversion (TomoSAR) using multiple data stacks from different viewing angles enables us to generate 4-D (space-time) point clouds of the illuminated area from space with a point density comparable to LiDAR. They can be potentially used for facade reconstruction and deformation monitoring in urban environment. In this paper, we present the first attempt to reconstruct facades from this class of data: First, the facade region is extracted using the density estimates of the points projected to the ground plane, the extracted facade points are then clustered into individual facades by means of orientation analysis, surface (flat or curved) model parameters of the segmented building facades are further estimated, and the geometric primitives such as intersection points of the adjacent facades are determined to complete the reconstruction process. The proposed approach is illustrated and validated by examples using TomoSAR point clouds generated from stacks of TerraSAR-X high-resolution spotlight images from two viewing angles, i.e., both ascending and descending orbits. The performance of the proposed approach is systematically analyzed. To explore the possible applications, we refine the elevation estimate of each raw TomoSAR point by using its more accurate azimuth and range coordinates and the corresponding reconstructed building facade model. Compared to the raw TomoSAR point clouds, significantly improved elevation positioning accuracy is achieved. Finally, a first example of the reconstructed 4-D city model is presented.