Sensitivity-Constrained Anisotropic Regularization for Two-Track InSAR 3D Landslide Deformation Inversion in the Baihetan Reservoir Area, China

Interferometric synthetic aperture radar (InSAR) is a key tool for monitoring landslide deformation in reservoir regions. However, when only ascending and descending line-of-sight (LOS) observations are available, 3D deformation inversion over complex hillslopes remains challenging because of slope-geometry priors and the anisotropic observation sensitivity. This study focuses on hillslopes in the Baihetan Reservoir area after impoundment. We use 340 ascending and descending Sentinel-1A images acquired from April 2021 to October 2024, generating LOS displacement time series using the extended small baseline subset (E-SBAS) technique. We propose a two-track InSAR 3D inversion framework centered on sensitivity-constrained anisotropic regularization (SC-Aniso). In this framework, a local-gradient surface-parallel flow model (LGSPFM) serves as a supporting pixel-scale topographic prior for representing local slope geometry. SC-Aniso constitutes the primary methodological innovation by mapping the inverse joint LOS sensitivities of the E, N, and U components to component-wise regularization weights. This design suppresses noise amplification in weakly constrained directions. Results show that the Baihetan Reservoir area is generally stable, with localized anomalies mainly in typical reservoir-bank landslide zones. The inverted 3D fields reveal coupled subsidence, horizontal displacement and downslope creep in the L01–L03 landslides. GNSS validation shows vertical RMSEs below 5.29 mm, mean 3D rate differences below 4 mm/yr, and an average component-wise rate difference of 2.56 mm/yr. At the optimal regularization parameter, SC-Aniso reduces north–south dispersion in stable areas by 41.9% compared with isotropic regularization. Wavelet analysis indicates a 288–384 day seasonal period for nonlinear displacement of the Xiaomidi landslide, with lags of 24 and 90 days relative to precipitation and reservoir water level, respectively. This study provides support for accurately recovering 3D deformation and interpreting movement mechanisms of landslides under limited two-track LOS observations.