The deformation characteristics analyses of reactivate water-rich landslide based on DS-InSAR monitoring technology

Yongwei Huang, Xianchun Ma (), Qiang Li, Ming Chang, Shibo Huang and Lingjie Lu
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Yongwei Huang: China Railway Southwest Research Institute Co., Ltd
Xianchun Ma: China Railway Southwest Research Institute Co., Ltd
Qiang Li: China Railway Southwest Research Institute Co., Ltd
Ming Chang: Chengdu University of Technology
Shibo Huang: Chengdu University of Technology
Lingjie Lu: Chengdu University of Technology

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2025, vol. 121, issue 17, No 25, 20129-20146

Abstract: Abstract To investigate the deformation patterns and mechanisms of water-rich accumulation landslides under the heavy rainfall conditions, the Distributed Scatterer Interferometric Synthetic Aperture Radar (DS-InSAR) monitoring technology was employed to monitor the surface deformation of a water-rich accumulation landslide on a highway in Qinba Mountain area from April 2023 to April 2024. The four characteristic points in the landslide area were selected for InSAR deformation analyses, and the results were compared and analyzed comprehensively with Global Navigation Satellite System (GNSS) surface monitoring and deep displacement monitoring datas. The results indicate that the ancient landslide accumulation body exhibited clear zoning characteristics, with the primary deformation areas concentrated on the right side below the highway. Accelerated deformation of the landslide occurred between August 17 and October 17, 2023, which was strongly correlated with the rainfall conditions. The reactivation of the landslide was attributed to the loose ancient landslide deposits, abundant groundwater, and the direct impact of the heavy rainfal. The ground monitoring datas validated the effectiveness of DS-InSAR monitoring technology in tracking deformation of highway accumulation landslides. The results provided data supports and theoretical references for comprehensive monitoring, feature analysis, and triggering factors assessment of water-rich highway accumulation landslides.

Keywords: Qinba mountain area; Water-rich accumulation landslides; DS-InSAR; GNSS monitoring; Ancient landslide resurrection (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11069-025-07614-4

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