InSAR-aided mapping and zonation of deep-seated gravitational slope deformation (DSGSD) in slate slopes

Abstract

Deep-seated gravitational slope deformation (DSGSD) is a rock mass wasting process featuring a slow movement rate at the mountain scale. In Taiwan, DSGSD has often been reported in the slate belt of Taiwan’s backbone Range because of the inherent cleavage characteristic. When a slate slope undergoes the DSGSD process, it can accumulate large deformation displacements and transform into a rockslide. In this circumstance, the slope movement could change from the cleavage orientation-dominated to the downslope direction, such as in the famous case of the Lushan North Slope. A critical issue for Taiwan’s authority in dealing with hazards associated with DSGSD is the efficient identification of hidden active DSGSD within the wide mountainous area for further detailed investigation/monitoring. This study aims to detect DSGSDs and zonate the present-day slope activity at the regional scale. Based on the Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique, we propose a hot-spot-like DSGSD mapping and zonation approach. The analysis was applied to Sentinel-1 radar data acquired in ascending and descending orbits between 2018 and 2020 centered on the Chingjing region, Taiwan. Combined with LiDAR terrain data and optical images, we recognized five DSGSD domains with higher deformation kinematics, which include a site that has yet to be investigated/monitored as DSGSD by relevant government agencies. In addition, we calculated the decomposed displacement vectors from two acquisition MT-InSAR data to establish each domain’s geometrical and kinematical model. Combined with borehole interpretation, inclinometer data, and simplified mechanical simulation, the models characterize the present-day moving phenomena and driving mechanisms for the observed DSGSDs. Overall, the MT-InSAR technique can aid the region-wide hazard assessment for the DSGSD in slate slopes regarding mapping and zonation. The results also highlight the potential of InSAR-assisted observation for understanding short-term movement kinematics and formulating a site-specific monitoring strategy.