Abstract: Giant deep-seated landslides are sudden and highly hazardous, making it difficult to grasp their spatial dynamics through ground surveys or single remote sensing methods. Taking the Nuole landslide as an example, this study employs multiple remote sensing technologies such as airborne LiDAR, optical remote sensing, and small baseline subset InSAR (SBAS-InSAR) for landslide interpretation. Initially, using LiDAR data, shaded relief maps are generated to interpret the development of the landslide, revealing three terraces, 29 cracks, 4 collapse areas, and 4 newly formed sliding areas. By analyzing optical images from different periods and DEM data, the horizontal displacement of typical feature points is explored to reveal the spatiotemporal evolution of planar deformation over an 11-year period. It is discovered that the lower part of the landslide area exhibits active deformation, with a maximum horizontal displacement of 6.2 meters. SBAS-InSAR technology is used to obtain line-of-sight (LOS) deformation from ascending and descending orbits between January 2019 and May 2023. Furthermore, slope direction data is introduced to decompose the LOS displacement results into two dimensions, revealing the true deformation of the landslide. The maximum vertical deformation is -650 mm, and the maximum horizontal deformation along the slope direction is 500 mm, indicating that the landslide has been in a long-term active state. Additionally, the study found that erosion affects the front edge of the landslide, while surface water infiltration affects the rear edge, resulting in deformation primarily along the slope and vertical directions, consistent with the mechanism of traction-induced landslide deformation. This research provides important references for identifying and studying the development mechanism of traction-induced landslides.

Key words: landslide, SBAS-InSAR, LiDAR, deformation analysis