Geomorphological transformations and future deformation estimations of a large potential landslide in the high-order position area of Diexi, China

Abstract

Landslides in high-order position areas pose a serious threat to residents located below the area. Therefore, research on the evolution process and underlying dynamic mechanisms is crucial. The majority of relevant studies are based on landslides that have already occurred, however, the investigation of potential landslides is of higher value. In this study, a progressive potential landslide identification method is proposed with the application of SBAS-InSAR (Small Baseline Subset InSAR) and subsequently combined with Google Earth, GF-1 (Gaofen-1), GF-2 (Gaofen-2), ZY-3 (Ziyuan-3)and UAV (Unmanned Aerial Vehicle) imagery, and DEM (Digital elevation model) for further validation. The proposed method is employed to determine the potential landslide in Tuanjiecun by integrating the multi-period data to simultaneously analyze the evolution and mechanism of the potential landslide. The LSTM (Long Short-Term Memory) method is then adopted to predicted the evolution trend based on accumulative deformation from SBAS-InSAR. The results suggest that the Tuanjiecun potential landslide will be relatively stable in the next five years although the largest deformation increased to -238.57mm. The analyses presented here aims to identify the current stage and future development of this potential landslide in terms of the underlying mechanism and transformation, so as to provide effective guidance for disaster prevention and mitigation across the globe.