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Susceptibility evaluation of highway landslide disasters based on SBAS-InSAR: a case study of S211 highway in Lanping County

Author

Listed:
  • Yimin Li

    (Yunnan University
    Research Center of Domestic High-Resolution Satellite Remote Sensing Geological Engineering)

  • Peikun Ji

    (Yunnan University
    Basic Geological Survey Institute of Jiangxi Geological Survey and Exploration Institute
    Jiangxi Nonferrous Geological Mineral Exploration and Development Institute)

  • Shiyi Liu

    (Yunnan University
    Hainan Ecological Environmental Geological Survey Institute)

  • Juanzhen Zhao

    (Yunnan University)

  • Yiming Yang

    (Yunnan University)

Abstract

Evaluation of landslide susceptibility along highways is critical for risk management in engineering development, construction, and operation and maintenance. The research target is the S211 Highway in Lanping County, Nujiang Prefecture, Yunnan Province, with its buffer zone extending 10 km as the research area. Eight evaluation factors are selected for the study, including slope, slope aspect, vegetation coverage, distance from the water system, rock group, rainfall, distance from the fault, and elevation. The findings of the susceptibility evaluation were classified into five categories, and the susceptibility grades of landslide disasters in the study area were evaluated using the information value and logistic regression coupling model. The accuracy of the coupling model was evaluated by the ROC curve and AUC value. The deformation rate in the study area was estimated by processing 28 Sentinel-1 A satellite images captured from January to December 2019 using the SBAS-InSAR technology and was used to optimize the landslide susceptibility grade. The results show that the extremely high and high-risk areas of the information value-logistic regression coupling model account for 28.33% of the total area of the study area, which constitutes nearly 83.82% of the historical landslide disaster sites, mainly occupying areas along highways with low vegetation coverage and within 2000 m from rivers. The AUC values in the accuracy verification reach 0.843, indicating that the evaluation model can accurately predict the landslide susceptibility. The vulnerability grade of landslide geological disaster in the entire evaluation unit is significantly increased by optimizing the result of the surface deformation obtained by SBAS-InSAR technology. A total of 79,587 grid cells were added to the extremely high susceptibility level region. This technique may optimize the evaluation results of landslide hazard susceptibility and provide decision support for disaster prevention and maintenance along highways.

Suggested Citation

  • Yimin Li & Peikun Ji & Shiyi Liu & Juanzhen Zhao & Yiming Yang, 2025. "Susceptibility evaluation of highway landslide disasters based on SBAS-InSAR: a case study of S211 highway in Lanping County," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(3), pages 2587-2612, February.
    • Handle: RePEc:spr:nathaz:v:121:y:2025:i:3:d:10.1007_s11069-024-06807-7
    DOI: 10.1007/s11069-024-06807-7
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