Sensitivity-Constrained Anisotropic Regularization for Two-Track InSAR 3D Landslide Deformation Inversion in the Baihetan Reservoir Area, China.
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| Title: | Sensitivity-Constrained Anisotropic Regularization for Two-Track InSAR 3D Landslide Deformation Inversion in the Baihetan Reservoir Area, China. |
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| Authors: | Dun, Jiawei1,2 (AUTHOR), Feng, Wenkai1,2 (AUTHOR) fengwenkai@cdut.cn, Yi, Xiaoyu1,2 (AUTHOR) |
| Source: | Remote Sensing. Aug2026, Vol. 18 Issue 15, p2525. 32p. |
| Subjects: | Mathematical regularization, Radar interferometry, Slopes (Soil mechanics), Tikhonov regularization |
| Geographic Terms: | China |
| Abstract: | Highlights: What are the main findings? A sensitivity-constrained anisotropic regularization framework was developed for 3D landslide deformation inversion from two-track InSAR observations, stabilizing weakly constrained deformation components in complex reservoir-bank terrain. The method mapped post-impoundment 3D deformation in the Baihetan Reservoir, revealed localized active landslides with coupled subsidence, horizontal displacement, and downslope creep, and identified rainfall and reservoir-level response lags for the Xiaomidi landslide. What are the implications of the main findings? The proposed framework provides a practical solution for reliable 3D landslide deformation recovery when only two SAR viewing geometries are available, overcoming weak direction instability and the limitations of conventional isotropic regularization in mountainous regions. By integrating stable 3D motion decomposition, slope-coordinate interpretation, GNSS validation, field evidence, and hydrological time lag analysis, this study strengthens post-impoundment landslide risk diagnosis and supports more physically interpretable monitoring of reservoir-bank slopes. 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. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? A sensitivity-constrained anisotropic regularization framework was developed for 3D landslide deformation inversion from two-track InSAR observations, stabilizing weakly constrained deformation components in complex reservoir-bank terrain. The method mapped post-impoundment 3D deformation in the Baihetan Reservoir, revealed localized active landslides with coupled subsidence, horizontal displacement, and downslope creep, and identified rainfall and reservoir-level response lags for the Xiaomidi landslide. What are the implications of the main findings? The proposed framework provides a practical solution for reliable 3D landslide deformation recovery when only two SAR viewing geometries are available, overcoming weak direction instability and the limitations of conventional isotropic regularization in mountainous regions. By integrating stable 3D motion decomposition, slope-coordinate interpretation, GNSS validation, field evidence, and hydrological time lag analysis, this study strengthens post-impoundment landslide risk diagnosis and supports more physically interpretable monitoring of reservoir-bank slopes. 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18152525 |
