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Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique

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Abstract

Locating potential landslides accurately is vital for developing mitigation strategies in advance to avoid catastrophic damages. This task typically requires intensive human efforts in detecting or monitoring the deformation or pore water pressure at various points of a slope, which is difficult to cover slopes over a wide area on a regional scale. This study investigates the potential of integrating small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technique into rainfall-induced slope movement characterization, with the goal of locating potential landslides accurately on a regional scale. The surface deformation of the slopes is first obtained using SBAS-InSAR technique, through which the soils with large downwards deformation that is prone to separate with the stable slope soils can be identified. Then, an index of separating trend is proposed to quantify the degree of separation, which is further used to characterize the potential landslides. The locations of potential landslides are then identified through the trend of separation. The proposed method is verified on 14 slopes in Shenzhen, China. The analysis on a mountain area of 4 km × 2 km in Shenzhen identified 2 potential landslides in May 2018 which collapsed after a heavy rainfall in August 2018. A separating trend keeping lower than 0.5 for at least 3 months is a reliable criterion to identify potential rainfall-induced landslides. A limitation of this study is that the proposed method cannot be used to identify the landslides caused by earthquakes and human activities. This study provides a quantified method to locate the potential landslides over a wide slope area rigorously, paving the way for a more cost-effective landslide mitigation strategy.

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Data availability

Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request.

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Acknowledgements

The financial support is greatly acknowledged. Appreciation is also expressed to Planning and Natural Bureau, and Meteorological Bureau of Shenzhen and Beijing Vastitude Technology Co., Ltd for providing the data in this study.

Funding

This work was supported by the National Key Research and Development Program of China (Grant No. 2021YFC3001002) and The State Key Program of National Natural Science Foundation of China (Grant number 52239008).

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China

    Jinhui Li, Xinfu Xing & Jinping Ou

  2. Guangdong Provincial Key Laboratory of Intelligent and Resilient Structures for Civil Engineering, Shenzhen, 518055, China

    Jinhui Li

  3. Shenzhen Key Laboratory of Intelligent Structure System in Civil Engineering, Harbin Institute of Technology (Shenzhen), Shenzhen, 518055, China

    Jinping Ou

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  1. Jinhui Li
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Correspondence to Jinhui Li.

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Li, J., Xing, X. & Ou, J. Locating and characterizing potential rainfall-induced landslides on a regional scale based on SBAS-InSAR technique. Bull Eng Geol Environ 82, 329 (2023). https://doi.org/10.1007/s10064-023-03356-4

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