EGU General Assembly 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Characteristics of a rapid landsliding area along Jinsha River revealed by multi-temporal remote sensing and its risks

Jiaming Yao, Hengxing Lan, Langping Li, Yiming Cao, Yuming Wu, Yixing Zhang, and Chaodong Zhou
Jiaming Yao et al.
  • State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China (

Large paleolandslides are developed in the upper reaches of Jinsha River, which seriously threaten the safety of nearby residents and engineering facilities. It is important to study the movement characteristics of these landslides. In this work, we inspect the deformation characteristics of a rapid landsliding area along the Jinsha River by using multi-temporal remote sensing, and analyzed its future development. Surface deformations and damage features between January 2016 and October 2020 were obtained using multi-temporal InSAR and multi-temporal correlations of optical images, respectively. Deformation and failure signs obtained from the field investigation were highly consistent. Results showed that cumulative deformation of the landsliding area is more than 50 cm, and the landsliding area is undergoing an accelerated deformation stage. The external rainfall condition is an important factor controlling the deformation. The increase of rainfall will accelerate the deformation of slope. The geological conditions of the slope itself affect the deformation of landslide. Due to fault development and groundwater enrichment, slopes are more likely to slide along weak structural plane. The Jinsha River continuously scours the concave bank of the slope, causing local collapses and forming local free surfaces. Numerical simulation results show that once the landsliding area fails, the landslide body may form a 4 km long dammed lake, and the water level could rise about 200 m.

How to cite: Yao, J., Lan, H., Li, L., Cao, Y., Wu, Y., Zhang, Y., and Zhou, C.: Characteristics of a rapid landsliding area along Jinsha River revealed by multi-temporal remote sensing and its risks, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6748,, 2023.