Landslide Monitoring by Integrating Multi-Sensor InSAR Time Series Datasets and Corner Reflectors in the Three Gorges Area

Landslide is one of the major geohazards in the Three Gorges area as a result of steep valley-side slopes and environmental conditions, e.g., high precipitation. To monitor and detect the landslides and rock falls at a regional scale as Three Gorges area, the differential Synthetic Aperture Radar Interferometry (D-InSAR) technology could be more effective and efficient than other conventional geological and geodetic measurements that can be performed only at a few sites with proper accessibility and conditions.

Over the past few decades, InSAR technology and advanced SAR Interferometry techniques such as Persistent Scatterer Interferometry (PSI) and Small Baseline Subsets (SBAS) have been developed to derive ground displacement over large areas with high-resolution measurement points and acceptable accuracy (cm to mm level). Both PSI and SBAS methods are based on a network of coherent pixels, including natural persistent scatterer (NPS) and artificial corner reflector (CR). NPSs can be easily found in urban areas or rocky regions. However, for landslide monitoring, the NPSs are usually difficult to be identified due to the steepness, vegetated and vulnerable moisture content among the high-risk locations. In this work, multiple SAR datasets including C-band Sentinel-1, L-band ALOS-2 and X-band TerraSAR-X (TSX) are exploited for landslide monitoring along the Yangtze River in the Three Gorges area in China.  Both PSI and SBAS methods are utilized. Besides, stable artificial CRs are deployed on selected sites to evaluate their performance in deriving landslide kinematics. Results are presented and discussed for a better assessment of landslide hazards in the Three Gorges region.