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Enhanced dynamic landslide hazard mapping using MT-InSAR method in the Three Gorges Reservoir Area

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Abstract

Landslide hazard mapping is essential for disaster reduction and mitigation. The hazard map produced by the spatiotemporal probability analysis is usually static with false-negative and false-positive errors due to limited data resolution. Here we propose a new method to obtain dynamic landslide hazard maps over the Wushan section of the Three Gorges Reservoir Area by introducing the ground deformation measured by the spaceborne Copernicus Sentinel-1 synthetic aperture radar (SAR) imagery collected from 9/30/2016 to 9/13/2017. We first determine the spatial probability of landslide occurrence predicted by the support vector machine algorithm. We also conducted the statistical analysis on the temporal probability of landslide occurrence under various rainfall conditions (0, 0–50, 50–100, and > 100 mm for the antecedent 5-day total). We initialize a preliminary landslide hazard map by combining the spatial and temporal landslide probabilities. Meanwhile, the ground deformation velocities during the representative dry and wet seasons can be extracted from multi-temporal interferometric SAR (MT-InSAR). Thereafter, the landslide hazard map can be finalized by an empirical assessment matrix considering both the preliminary landslide hazard map and deformation velocities. Our results demonstrate that false-negative and false-positive errors in the landslide hazard map can be effectively reduced with the assistance of the deformation information. Our proposed method can be used to assess the dynamic landslide hazard at higher accuracy.

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Acknowledgements

The first author thanks Prof. Andy Hooper in Leeds University for his help in MT-InSAR processing. We thank the assistance of Chongqing Bureau of Planning and Natural Resources and Dr. Xin Liang for data collection. We appreciate the reviewers for their suggestions that significantly improved the quality of this paper.

Funding

This research is funded by the National Natural Science Foundation of China (No. 41907253 and No. 41702330) and Key Research and Development Program of Hubei Province (No. 2021BCA219).

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Authors and Affiliations

  1. School of Geography and Information Engineering, China University of Geosciences, Wuhan, 430078, China

    Chao Zhou

  2. Research Center of Geohazard Monitoring and Warning in the Three Gorges Reservoir, Chongqing, 40400, China

    Chao Zhou, Ying Cao, Kunlong Yin & Yue Wang

  3. Faculty of Engineering, China University of Geosciences, Wuhan, 430074, China

    Ying Cao, Kunlong Yin & Yue Wang

  4. College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China

    Xie Hu

  5. Department of Geosciences, University of Padova, Via Gradenigo 6, 35131, Padova, Italy

    Filippo Catani

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  1. Chao Zhou
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  2. Ying Cao
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  3. Xie Hu
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  4. Kunlong Yin
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Correspondence to Kunlong Yin.

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Zhou, C., Cao, Y., Hu, X. et al. Enhanced dynamic landslide hazard mapping using MT-InSAR method in the Three Gorges Reservoir Area. Landslides 19, 1585–1597 (2022). https://doi.org/10.1007/s10346-021-01796-1

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