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Detection and characterization of active landslides with multisource SAR data and remote sensing in western Guizhou, China

Author

Listed:
  • Yifei Zhu

    (China University of Geosciences (Beijing)
    Chinese Academy of Geological Sciences
    Ministry of Natural Resources)

  • Xin Yao

    (Chinese Academy of Geological Sciences
    Ministry of Natural Resources)

  • Leihua Yao

    (China University of Geosciences (Beijing))

  • Chuangchuang Yao

    (Chinese Academy of Geological Sciences
    Ministry of Natural Resources)

Abstract

The western part of Guizhou is located in the second step of East Asia. Although the area is stratigraphically continuous and the surface is dominated by hard limestone and sandstone, catastrophic landslides often occur, seriously threatening residents' lives and the safety of property. Accurate identification of landslides and analysis of their developmental patterns are vital to prevent and reduce the threat of geological disasters. No active landslide survey data cover this region, so this paper identifies the active landslides in the western part of Guizhou by combining surface deformation information, multitemporal optical remote sensing images, geological lithology, and geomorphic features to obtain deformation information from multisource synthetic aperture radar surface data. This process increases the accuracy and reliability of identifying unstable slopes in areas with dense vegetation and steep terrain. By processing 283 Sentinel-1 and PALSAR-2 synthetic aperture radar data, 578 active landslides, 18 of which are high-risk large-scale landslides (landslide groups), are delineated for the first time in a range of 4.64 × 104 km2 in the study area. The active landslides mainly include natural landslides, reservoir landslides, and mining-induced landslides, accounting for 2.4%, 4.2 %, and 93.4%, respectively. The spatial distribution of landslides is banded along the cuesta at the edge of an outcrop of coal strata. Landslides are mainly distributed at elevations of 1800–2000 m, with an elevation difference of 50 ~ 100 m and a slope range of 35° ~ 40°. The landslides are characterized by steep slopes, small scales, mass occurrences, and no dominant slope direction, classifying them as cuesta landslides induced by mining disturbance. Furthermore, nuanced remote sensing interpretation of the disaster elements, such as cuesta cliff, tensile cracks, deep and sizeable tensile channels, isolated rock masses, and collapse debris, and their processes of change, reveals that coal mining-disturbed landslides in this region have experienced four primary stages: natural unloading, mining disturbance, displacement acceleration, and slope failure. This is of great significance for understanding the genetic mechanism and developmental patterns, as well as the risk assessment, of this region.

Suggested Citation

  • Yifei Zhu & Xin Yao & Leihua Yao & Chuangchuang Yao, 2022. "Detection and characterization of active landslides with multisource SAR data and remote sensing in western Guizhou, China," 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. 111(1), pages 973-994, March.
  • Handle: RePEc:spr:nathaz:v:111:y:2022:i:1:d:10.1007_s11069-021-05087-9
    DOI: 10.1007/s11069-021-05087-9
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    References listed on IDEAS

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    1. Lingjing Li & Xin Yao & Jiaming Yao & Zhenkai Zhou & Xin Feng & Xinghong Liu, 2019. "Analysis of deformation characteristics for a reservoir landslide before and after impoundment by multiple D-InSAR observations at Jinshajiang River, China," 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. 98(2), pages 719-733, September.
    2. Xin Yao & Lingjing Li & Yongshuang Zhang & Zhenkai Zhou & Xinghong Liu, 2017. "Types and characteristics of slow-moving slope geo-hazards recognized by TS-InSAR along Xianshuihe active fault in the eastern Tibet Plateau," 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. 88(3), pages 1727-1740, September.
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    Cited by:

    1. Chong Niu & Wenping Yin & Wei Xue & Yujing Sui & Xingqing Xun & Xiran Zhou & Sheng Zhang & Yong Xue, 2023. "Multi-Window Identification of Landslide Hazards Based on InSAR Technology and Factors Predisposing to Disasters," Land, MDPI, vol. 12(1), pages 1-15, January.

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