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Ancient landslide in Wanzhou District analysis from 2015 to 2018 based on ALOS-2 data by QPS-InSAR

Author

Listed:
  • Changjun Huang

    (Hunan City University
    Key Laboratory of Key Technologies of Digital Urban-Rural Spatial Planning of Hunan Province)

  • Qingshan Zhou

    (Hunan City University)

  • Lv Zhou

    (Guilin University of Technology)

  • Yuanzhi Cao

    (Hunan City University)

Abstract

Landslide is a global environmental geological hazard caused by natural or human activities. Since the impoundment of the Three Gorges reservoir area, the geological disasters such as collapses, landslides and other kinds of geological disasters increased obviously due to the periodic fluctuation of the water level in the Yangtze River. Wanzhou District is located in the center of the Three Gorges Reservoir Area, which plays an important role in the prevention and control of geological hazards in the whole Three Gorges Reservoir Area. This is because a large number of deep bedrocks old landslides are distributed among this region, such as Taibaiyan ancient landslide, Caojiezi ancient landslide, Anlesi ancient landslide, Pipaping ancient landslide, and Diaoyanping ancient landslide. In this study, Quasi-Persistent Scatterers InSAR (QPS-InSAR) time-series method is proposed to identify and monitor the ancient landslides in Wanzhou. In this method, the High-coherent test is applied to Quasi-Persistent Scatterers (PSC) selection, and PSC and persistent scatterer are combined to improve the density of measurement points in vegetation area. The QPS-InSAR method is also characterized by the appropriate combination of differential interferograms produced by a Minimum Spanning Tree and the employment of the phase triangulation algorithm to estimate the optimal phase. This technique was performed on 8 scenes of L-band ALOS PALSAR ascending data acquired during 2015–2018, then deformation rate maps and time series for ancient landslide were generated, which were applied to retrieve time series displacement for the large-scale landslide in Wanzhou District. The experiment results show that there are obvious landslide deformation patterns detected in this region with displacement velocity larger than − 21 mm/yr during the observation period. Finally, the influencing factors such as geological conditions, distribution of rainfall and reservoir water level change in the Three Gorges Reservoir area, and deformation mechanism of Wanzhou landslide are analyzed. The monitoring results will help the local government to carry out regular landslide inspection and strengthen landslide disaster early warning.

Suggested Citation

  • Changjun Huang & Qingshan Zhou & Lv Zhou & Yuanzhi Cao, 2021. "Ancient landslide in Wanzhou District analysis from 2015 to 2018 based on ALOS-2 data by QPS-InSAR," 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. 109(2), pages 1777-1800, November.
    • Handle: RePEc:spr:nathaz:v:109:y:2021:i:2:d:10.1007_s11069-021-04898-0
    DOI: 10.1007/s11069-021-04898-0
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    Citations

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    Cited by:

    1. Lan Xiao & Liang Yang & Yang Wang, 2024. "Deformation characteristics and stability of the Sifangbei landslide based on the shape renewal of longitudinal profile," 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. 120(4), pages 3677-3697, March.
    2. 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.
    3. Song Yingze & Song Yingxu & Zhang Xin & Zhou Jie & Yang Degang, 2024. "Comparative analysis of the TabNet algorithm and traditional machine learning algorithms for landslide susceptibility assessment in the Wanzhou Region of 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. 120(8), pages 7627-7652, June.

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