RESEARCH ARTICLE
Characterization of post-event kinematics of Baige landslide using multi-source remotely-sensed imagery
Zhenyan Lai,
Xuguo Shi,
Daqing Ge,
Menghua Li,
Chencheng Li,
Li Zhang,
Zhenyan Lai
School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
Search for more papers by this authorCorresponding Author
Xuguo Shi
School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
Correspondence
Xuguo Shi, School of Geography and Information Engineering, China University of Geosciences, Wuhan, China.
Email: [email protected]
Search for more papers by this authorDaqing Ge
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, China
Search for more papers by this authorMenghua Li
Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorChencheng Li
School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
Search for more papers by this authorLi Zhang
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, China
Search for more papers by this authorZhenyan Lai,
Xuguo Shi,
Daqing Ge,
Menghua Li,
Chencheng Li,
Li Zhang,
Zhenyan Lai
School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
Search for more papers by this authorCorresponding Author
Xuguo Shi
School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
Correspondence
Xuguo Shi, School of Geography and Information Engineering, China University of Geosciences, Wuhan, China.
Email: [email protected]
Search for more papers by this authorDaqing Ge
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, China
Search for more papers by this authorMenghua Li
Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, China
Search for more papers by this authorChencheng Li
School of Geography and Information Engineering, China University of Geosciences, Wuhan, China
Search for more papers by this authorLi Zhang
China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing, China
Search for more papers by this authorFirst published: 08 May 2025
Funding information: This work was financially supported by the National Natural Science Foundation of China (Grant Nos. 42474061 and 42404036) and the National Key Research and Development Program of China (Grant No. 2021YFC3000400).
Abstract
The Baige landslide, which experienced two major collapses on October 10 and November 3, 2018, resulted in the formation of a landslide dam on the Jinsha River, causing significant socio-economic damage. Despite these catastrophic events, ongoing deformation has been observed, indicating persistent landslide activity and a continued risk of future failures. In this study, we integrated multi-source remote sensing imagery to investigate the post-failure kinematics of the Baige landslide from 2019 to 2023. Small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) was employed to derive slow moving displacement rates of Baige landslide from the Sentinel-1 and ALOS-2 PALSAR-2 datasets. Two-dimensional (2D) displacement by integration of InSAR measurements revealed maximum vertical and eastward displacement rates of −357.1 mm/yr and 382.1 mm/yr, respectively. Pixel offset tracking (POT) analysis of Sentinel-2 and ALOS-2 PALSAR-2 datasets further facilitated the derivation of three-dimensional (3D) displacement rates, with maximum vertical and horizontal displacements of −7.2 m/yr and 5.4 m/yr in the upper sections, respectively. The significant variations in displacement rates are related to the fractured surfaces within the landslide. A one-dimensional pore pressure diffusion model estimated the hydraulic diffusivity of the landslide as approximately 4.95 × 10−5 m2/s, with an unstable mass thickness of ~ 65 m near the head scarp. Seasonal accelerations correlated with rainfall highlight the role of hydrological factors in landslide dynamics. This study demonstrates the value of integrating multi-source remote sensing data to monitor landslides, providing critical insights for hazard assessment and mitigation in the Jinsha River Basin and similar high-risk regions.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflict of interest.
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.
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