InSAR-based detection and deformation factor analysis of landslide clusters in the Jinsha River
WU Dehong1(), HAO Lina1(), YAN Lihua1, TANG Fengshun1, ZHENG Guang2
1. School of Earth Sciences, Chengdu University of Technology, Chengdu 610059, China 2. State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu 610059, China
The Jinsha River basin is a typical area with a high incidence of geologic hazards in China. To accurately identify the potential landslide hazards in the basin, this study processed the data of Sentinel-1A’s ascending and descending orbits using the SBAS-InSAR technique. From two detection directions, it conducted early landslide identification and deformation monitoring of the Baige landslide on the bank of the Jinsha River and its lower reaches covering approximately 100 km. The results show that: ① The combined detection based on Sentinel-1A’s ascending and descending orbits effectively reduced the interference of geometric distortions, enabling the identification of long-term creep hazard sites; ② The deformation rates along the line-of-sight (LOS) of ascending and descending orbits ranged from -142 to 80 mm/a and -71 to 56 mm/a, respectively. Combined with the visual interpretation of optical remote sensing images, two large landslide clusters consisting of nine landslides were detected; ③ The analysis of surface deformation characteristics was conducted on three typical landslides: the Sela landslide, the Shadong (Xiongba) landslide, and the Nimasi talus slide. The analysis results reveal that the maximum deformation was associated with the peak rainfall and river runoff, which constituted the significant factors influencing landslide deformation. The results of this study serve as a reference for the prediction, early warning, prevention, and control of basin-scale geologic hazards in flood seasons.
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2024, Vol. 36 
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