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The application of interferometric synthetic aperture radar (InSAR) has been challenged over hilly and vegetated regions due to significant phase decorrelation. The spatiotemporal filtering techniques can partially overcome this, whereas the so-called ‘homogeneous pixels’ are selected based on the synthetic aperture radar (SAR) datasets and the computation is not satisfactorily efficient. In this letter, we propose the idea of interferogram homogeneous filtering relying on Light Detection and Ranging (LiDAR) derived topography features, instead of using amplitude or phase from the SAR images. The method exploits terrain slope and aspect to cluster topographically homogeneous pixels (THPs) and uses a coherence weighted phase-link (WPL) algorithm to reconstruct pixel phase histories. We compare the proposed method with two representative strategies, i.e., the amplitude statistically homogeneous pixels (SHPs) and the similar time-series interferometric phase pixels (STIPs). Results are given using L-band ALOS-1 data covering the forested Island of Lantau, Hong Kong. It is demonstrated that the LiDAR-derived THP has substantially decreased the computation load whereas the coherence of phase and the InSAR parameter estimation have been improved.

Distributed scatterer interferometry for forested and hilly areas using a topographical homogeneous filtering