Assessing Reservoir-Induced Landslide Dynamics Using Integrated Sentinel-1, TerraSAR-X, and Optical Remote Sensing

Reservoir-induced landslides pose a significant threat to the safety of nearby residential areas and infrastructure. Understanding the relationship between reservoir water level fluctuations and landslide deformation is therefore critical for effective hazard assessment and early warning. In this study, we investigate the spatiotemporal evolution of the Wangjiasha Landslide using a multi-sensor remote sensing approach. Sentinel-1 (C-band) and TerraSAR-X (X-band) Synthetic Aperture Radar (SAR) data were combined to monitor surface deformation over different temporal scales, with Sentinel-1 observations spanning from 2017 to 2025 and TerraSAR-X data covering the period from 2022 to 2024. In addition, Sentinel-2 optical imagery was processed on the Google Earth Engine (GEE) platform to extract variations in reservoir water surface area. By integrating InSAR-derived deformation measurements with water body dynamics, we analyze the spatial patterns of slope instability and examine the relationship between reservoir water area changes and landslide motion. Particular attention is given to the influence of reservoir water level fluctuations on landslide kinematics, including potential variations in deformation rate and spatial distribution. The results demonstrate the effectiveness of multi-sensor remote sensing for characterizing reservoir-induced landslide dynamics and provide valuable insights for deformation monitoring and hazard assessment.