Combination of satellite InSAR, stereo mapping, and LiDAR to improve the understanding of the Chuwangjing landslide in the Three Gorges Reservoir Area

• Published in: Natural hazards (Dordrecht) Vol. 120; no. 13; pp. 12203 - 12220
• Main Authors: Tu, Kuan, Ye, Shirong, Zou, Jingui, Guo, Jiming, Chen, Hua, He, Yifeng
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.10.2024; Springer Nature B.V
• Subjects: Aerial surveys; Canyons; Civil Engineering; Composition; Damage detection; Deformation; Deformation analysis; Deformation effects; Drawdown; Dynamic characteristics; Dynamic models; Earth and Environmental Science; Earth Sciences; Environmental Management; Geophysics/Geodesy; Geotechnical Engineering & Applied Earth Sciences; High water levels; Hydrogeology; Hydrologic data; Hydrologic surveys; Interferometric synthetic aperture radar; Kinematics; Landslides; Landslides & mudslides; Lidar; Mechanical properties; Natural Hazards; Original Paper; Radar detection; Rainfall; Remote sensing; Remote sensing techniques; Reservoirs; SAR (radar); Satellites; Sensing techniques; Stability analysis; Synthetic aperture radar; Synthetic aperture radar interferometry; Technology assessment; Unmanned aerial vehicles; Velocity; Water damage; Water levels; Water supply systems; Three Gorges Reservoir; Multiple remote sensing techniques; Triggering factors; Kinematic evolution; Chuwangjing landslide; Three Gorges Reservoir
• ISSN: 0921-030X; 1573-0840
• DOI: 10.1007/s11069-024-06680-4

Since its impoundment in 2003, more than 5,000 landslides have been identified in the Three Gorges Reservoir, and more than 600 slides have apparent activity, which causes significant damage and threats to residents and water infrastructure. Understanding the kinematic behavior and velocity characteristics, mechanisms, trigger factors, and dynamic models of landslides contribute to their instability evaluation and prevention. However, landslide stability analysis is challenging because of complex influencing factors and unclear structural features. The primary objectives of this study were to investigate the kinematic, mechanical, and dynamic characteristics of the Chuwangjing landslide and to identify the trigger factors. We applied multi-resource remote sensing techniques, including satellite Tri-Stereo, unmanned aerial vehicle (UAV) surveys, light detection and ranging (LiDAR) point clouds, and interferometric synthetic aperture radar (InSAR) techniques, to analyze morphological, kinematic, and dynamic features, combined with meteorological and hydrological data. The increased velocity during periods of intense rainfall and prolonged water function, particularly during periodic rapid drawdown periods at high water levels, indicates that deformation is primarily governed by these two factors. The composition of cracks and scrapes detected by LiDAR and satellite Tri-Stereo technology and the deformation distribution on the slope indicated a retrogressive model. We analyzed the landslide’s kinematic model and dynamic conditions by considering characteristics such as step-like deformation, influencing factors, and geological composition. Furthermore, by comparing the application effects of multi-remote sensing technology combinations in landslide analysis, this study proved the usefulness of an integrated method for landslide analysis and trending evaluation.