INFERRING THE LANDSLIDE SLIDING SURFACE MOVEMENT CHARACTERISTICS BASED ON INSAR DEFORMATION-EXAMPLE OF THE BUWA VILLAGE LANDSLIDE IN WENCHUAN COUNTY

Currently, the contact method is mostly used to obtain the motion characteristics of the sliding surface of a landslide, which is time-consuming and costly. It can only provide information on the motion state of the sliding surface at sparse point positions. In this paper, a non-contact method is proposed to obtain the landslide sliding surface movement characteristics. The basic idea is to establish a relationship model between landslide surface deformations and sliding surface movement based on the dislocation theory. Simultaneously, a sliding surface movement smoothness constraint condition is introduced. Finally, the surface deformation obtained by InSAR and other technologies is used as constraints to estimate the motion characteristics of the sliding surface. The landslide in Buwa Village, Wenchuan County, Sichuan Province, is chosen as the research object in this paper. The geometric and kinematic parameters of the landslide slide surface of Buwa Village were obtained based on the developed theory and method, constrained by the observed surface deformation. The reliability of inversion results was verified through field surveys, Lidar observations, and model residuals. The residuals of the ascending and descending inversion model are only 3.1 mm ·a^-1 and 3.4 mm ·a^-1, respectively. The inversion results indicate that the sliding surface of the Buwa Village landslide is located at an average depth of ~15.0 m below the slope surface. The sliding surface mainly moves along the slope, with a maximum movement of ~80 mm ·a^-1. Additionally, vertical movement is observed in the middle and lower part of the west side of the slope. The method proposed in this paper enables the quick and easy acquisition of the spatial continuous motion characteristics of the landslide sliding surface. It provides a more direct and reliable scientific reference for landslide disaster warning and risk assessment.