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Combining Soil Moisture and MT-InSAR Data to Evaluate Regional Landslide Susceptibility in Weining, China

Author

Listed:
  • Qing Yang

    (China Siwei Surveying and Mapping Technology Co., Ltd., Beijing 100086, China)

  • Zhanqiang Chang

    (College of Resource, Environment &Tourism, Capital Normal University, Beijing 100048, China
    Key Lab of 3D Information Acquisition of Education Ministry of China, Beijing 100048, China)

  • Chou Xie

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China
    Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Deqing 313200, China)

  • Chaoyong Shen

    (The Third Surveying and Mapping Institute of Guizhou Province, Guiyang 550004, China)

  • Bangsen Tian

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
    Laboratory of Target Microwave Properties, Deqing Academy of Satellite Applications, Deqing 313200, China)

  • Haoran Fang

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yihong Guo

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China)

  • Yu Zhu

    (Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China)

  • Daoqin Zhou

    (The Third Surveying and Mapping Institute of Guizhou Province, Guiyang 550004, China)

  • Xin Yao

    (The Third Surveying and Mapping Institute of Guizhou Province, Guiyang 550004, China)

  • Guanwen Chen

    (The Third Surveying and Mapping Institute of Guizhou Province, Guiyang 550004, China)

  • Tao Xie

    (The Third Surveying and Mapping Institute of Guizhou Province, Guiyang 550004, China)

Abstract

Landslide susceptibility maps (LSMs) play an important role in landslide hazard risk assessments, urban planning, and land resource management. While states of motion and dynamic factors are critical in the landslide formation process, these factors have not received due attention in existing LSM-generation research. In this study, we proposed a valuable method for dynamically updating and refining LSMs by combining soil moisture products with Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) data. Based on a landslide inventory, we used time-series soil moisture data to construct an index system for evaluating landslide susceptibility. MT-InSAR technology was applied to invert the displacement time series. Furthermore, the surface deformation rate was projected in the direction of the steepest slope, and the data was resampled to a spatial resolution consistent with that of the LSM to update the generated LSM. The results showed that varying soil moisture conditions were accompanied by dynamic landslide susceptibility. A total of 22% of the analyzed pixels underwent significant susceptibility changes (either increases or decreases) following the updating and refining processes incorporating soil moisture and MT-InSAR compared to the LSMs derived based only on static factors. The relative landslide density index obtained based on actual landslides and the analyses of Dongfeng, Haila town, and Dajie township confirmed the improved slow landslide prediction reliability resulting from the reduction of the false alarm and omission rates.

Suggested Citation

  • Qing Yang & Zhanqiang Chang & Chou Xie & Chaoyong Shen & Bangsen Tian & Haoran Fang & Yihong Guo & Yu Zhu & Daoqin Zhou & Xin Yao & Guanwen Chen & Tao Xie, 2023. "Combining Soil Moisture and MT-InSAR Data to Evaluate Regional Landslide Susceptibility in Weining, China," Land, MDPI, vol. 12(7), pages 1-34, July.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:7:p:1444-:d:1198115
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    References listed on IDEAS

    as
    1. Daniela Piacentini & Stefano Devoto & Matteo Mantovani & Alessandro Pasuto & Mariacristina Prampolini & Mauro Soldati, 2015. "Landslide susceptibility modeling assisted by Persistent Scatterers Interferometry (PSI): an example from the northwestern coast of Malta," 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. 78(1), pages 681-697, August.
    2. Ram Ray & Jennifer Jacobs & Thomas Ballestero, 2011. "Regional landslide susceptibility: spatiotemporal variations under dynamic soil moisture conditions," 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. 59(3), pages 1317-1337, December.
    3. Chen Jun & Yifang Ban & Songnian Li, 2014. "Open access to Earth land-cover map," Nature, Nature, vol. 514(7523), pages 434-434, October.
    Full references (including those not matched with items on IDEAS)

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