LAUSR

When the distributed scatterer interferometric synthetic aperture radar (DS-InSAR) technology is used for surface deformation monitoring, the accuracy strongly depends on the quality of phase optimization. Especially, in the low-coherence region, how to conveniently and effectively improve the quality of phase optimization has been a hot and difficult research topic in recent years. This article proposes a hybrid phase optimization method for the DS-InSAR technology, which chooses either nonlocal (NL) or minimum mean square error (MMSE) method for each pixel according to the distribution of statistically homogeneous pixel in two windows of different sizes. This hybrid method (NL-MMSE) is not limited by the number of interferogram and is not influenced by multimaster images. The NL-MMSE method was applied to the deformation monitoring in the Jinsha River basin, Tibet, China, using 28 Sentinel-1A SAR images acquired between February and December 2020. Compared with the NL and MMSE methods, the NL-MMSE method provides better phase quality of the interferogram stack and is able to extract more temporal coherence points for subsequent deformation inversion. The deformation monitoring results showed there are three obvious large-scale landslide deformation and dozens of small-scale deformation in the study area. It is demonstrated that the NL-MMSE method based on DS-InSAR technology can accurately monitor the detailed deformation characteristics of the low-coherence surface, and can be applied and promoted as an effective means of identifying and monitoring geological hazards.