Building Recognition Fusing Multi-Aspect High-Resolution Interferometric SAR Data

Abstract — The improved ground resolution of state-of-the-art synthetic aperture radar (SAR) sensors suggests utilizing this technique for the analysis of urban areas. However, building reconstruction from SAR or InSAR data suffers from the consequences of the inherent oblique scene illumination, such as layover, occlusion by radar shadow and multipath signal propagation. Especially in built-up areas, building reconstruction is therefore often impossible from a single SAR or InSAR measurement. But, the reconstruction quality can be significantly improved by a combined analysis of multi-aspect data. In this paper, an approach for the detection and reconstruction of buildings from multi-aspect high-resolution InSAR data sets is proposed. The InSAR data have a spatial resolution of about 30 cm and were taken from two flight directions spanning a difference of about 90°. The building recognition is supported by knowledge based analysis concerning the SAR-specific effects in urban areas. Frequently observable are lines of bright scattering resulting from dihedral corners between ground and building wall. These lines are part of the building footprint and can be distinguished from other lines of bright scattering using the InSAR heights. They are extracted from the magnitude images in slant geometry and projected into the world coordinate system. Here, due to the orthogonal flight directions, they can be fused to L-structures as base for building recognition. Simulation results are compared with real imagery. The approach is demonstrated for an InSAR data set of a building group in an urban environment