Deformation monitoring of urban infrastructure by tomographic SAR using multi-view TerraSAR-X data stacks

Abstract

Synthetic Aperture Radar Tomography (TomoSAR) coupled with data from modern SAR sensors, such as the German TerraSAR-X (TS-X) produces the most detailed three-dimensional (3D) maps by distinguishing among multiple scatterers within a resolution cell. Furthermore, multi-temporal TomoSAR allows for recording the underlying deformation phenomenon of each individual scatterer. One of the limitations of using InSAR techniques, including TomoSAR, is that they only measure deformation along the radar Line-of-Sight (LOS). In order to enhance the understanding of deformation, a decomposition of the observed LOS displacement into the 3D deformation vector in the local coordinate system is desired. In this paper we propose a method, based on L1 norm minimization within local spatial cubes, to reconstruct 3D deformation vectors from TomoSAR point clouds available from, at least, three different viewing geometries. The methodology is applied on two pair of cross-heading TS-X spotlight image stacks over the city of Berlin. The linear deformation rate and amplitude of seasonal deformation are decomposed and the results from two individual test sites with remarkable deformation patterns are discussed in details.