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Two-dimensional deformation monitoring for spatiotemporal evolution and failure mode of Lashagou landslide group, Northwest China

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Abstract

The Lashagou landslide group in Gansu Province, China, is a typical shallow loess landslide group caused by artificial slope cutting. In April 2018, local sliding of the landslide group damaged houses and blocked the G310 highway, leading to the relocation of the Lashagou village, which aroused widespread concern. Unfortunately, the spatiotemporal displacement characteristics and failure modes of the landslide remain unknown. In this study, a method for the estimation of two-dimensional deformation of landslides, based on the local parallel flow model, was presented. This method only needs two orbital synthetic aperture radar (SAR) images with different imaging geometries, and has high accuracy verified by global satellite navigation system (GNSS) observations. In practice, we first obtained the surface velocity and time series deformation of the ascending and descending orbits. The best-fit sliding direction and inclination of the landslide movement were then inverted by combining satellite imaging geometry and surface velocity. Furthermore, the two-dimensional deformation of the Lashagou landslide group in the sliding and normal directions was obtained. We found that the landslide was in the accelerated deformation stage during the wet season and the deformation was mainly concentrated in the northern part of the Lashagou village. The snowmelt and continuous rainfall were the main factors in the landslide deformation. In addition, the landslide surface displacement characteristics and deep stress states can be linked using a combination of two-dimensional deformation, combined deformation, and inclination, which provides evidence that landslide movement is controlled by one or more deep continuous structural planes. Our research shows that the two-dimensional deformation retrieval method can be applied to gravity-driven translational landslides to help prevent and mitigate landslide hazards.

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Acknowledgements

Sentinel-1A data used in this study were provided by European Space Agency (ESA) through the Sentinel-1 Scientific Data Hub. The geological data of the Lashagou landslide group was provided by the School of Petrochemical Engineering. The precipitation data was provided by China Meteorological Administration and China Meteorological Data Network. We are very grateful for the above support. In addition, we also thank Andy Hooper for StaMPS.

Funding

This research was funded by the National Natural Science Foundation of China Projects (Grant No. 42074041, 42174032); National Key Research and Development Program of China (Grant No. 2020YFC1512000, 2019YFC1509802); State Key Laboratory of Geo-Information Engineering (Grant No. SKLGIE 2019-Z-2–1); and Shaanxi Natural Science Research Program (Grant No. 2020JM-227). This research was also supported in part by the Fundamental Research Funds for the Central Universities, Chang’an University (Grant No. 300102260301, 300102262401, 300102262206), in part by the Shaanxi Province Science and Technology Innovation Team (Grant No. 2021 TD-51), and in part by the European Space Agency through the ESA-MOST DRAGON-5 Project (Grant No. 59339).

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Authors and Affiliations

  1. School of Geology Engineering and Geomatics, Chang’an University, Xi’an, 710054, China

    Shuangcheng Zhang, Qianyou Fan, Shican Qiu, Jinzhao Si, Yihang Feng, Shengqiu Zhang, Zhiwei Song & Zhenhong Li

  2. Big Data Center for Geosciences and Satellites (BDCGS), Chang’an University, Xi’an, 710054, China

    Shuangcheng Zhang & Zhenhong Li

  3. Key Laboratory of Western China’s Mineral Resource and Geological Engineering, Ministry of Education, Xi’an, 710054, China

    Shuangcheng Zhang & Zhenhong Li

  4. School of Mining and Geomatics Engineering, Hebei University of Engineering, Handan, 056038, China

    Yufen Niu

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  1. Shuangcheng Zhang
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Correspondence to Qianyou Fan.

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Zhang, S., Fan, Q., Niu, Y. et al. Two-dimensional deformation monitoring for spatiotemporal evolution and failure mode of Lashagou landslide group, Northwest China. Landslides 20, 447–459 (2023). https://doi.org/10.1007/s10346-022-01979-4

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