Failure process and three-dimensional motions of mining-induced Jianshanying landslide in China observed by optical, LiDAR and SAR datasets

ABSTRACT

The occurrence of collapses and landslides due to underground mining has its unique failure mechanism, especially in the Karst mountainous regions of China. Spaceborne and airborne remote sensing observations provide rapid and effective tools for assessing surface changes and monitoring surface deformation of such landslides. In this study, we take the Jianshanying landslide, a typical mining-induced and fast-deformed landslide, as an example, and reveal the failure mechanism of such landslide by investigating the historical surface displacement. First, the complete evolution of the landslide surface was investigated from its original state to the overall sliding. The data include the satellite and Unmanned Aerial Vehicle (UAV) optical images, UAV three-dimensional (3-D) real scene models, high-resolution Light Detection and Ranging (LiDAR) DEM, and field survey. The results show that the head region entered the high deformation stage after 2019, the maximum deformation rate was 12.3 m/yr. The landslide morphology was formed after the overall slide occurred in September 2020. Then, the pre-event 3-D surface deformation after the landslide entered the high deformation stage was recovered using Interferometric Synthetic Aperture Radar (InSAR), differential DEM, and SAR/optical offset-tracking techniques. The vertical deformation was recovered around −30 m from 2019 to 2020. In particular, we solved the problem of unequal accuracy of SAR and optical offset-tracking observations in 3-D deformation inversion by employing the Helmert variance component estimation method. The maximum deformation was 6 m and 3 m within 4 months in the NS and EW directions, respectively. Finally, we revealed the failure mechanism of the Jianshanying landslide based on the disparity of horizontal and vertical deformation. That is, underground mining causes a significant subsidence of the rear part of the landslide body, resulting in different stress changes in the rear and front parts of the landslide body, which eventually led to sliding of the front part of the slope along the free surface. This work investigates and monitors the typical underground mining-induced Jianshanying landslide by using multi-sensor remote sensing approaches to trace the pre-event surface motions and to reveal its failure mechanism.

KEYWORDS:

• Optical remote sensing
• SAR
• DEM
• mining-induced landslide
• deformation monitoring
• failure mechanism

Acknowledgments

The authors would like to thank JAXA, Japan for providing the ALOS/PALSAR-2 data and the European Space Agency for providing the Sentinel-2 optical images free of charge. In addition, thanks to MicMac software, which can be download from website https://github.com/micmacIGN/micmac.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The Sentinel-2 images used in this paper are available from the website https://scihub.copernicus.eu/dhus/#/home. The ALOS/PALSAR-2 data can be acquired from https://gportal.jaxa.jp/gpr/search?tab=1 after applying to JAXA, Japan. Other data are available from the corresponding author [Chaoying Zhao] upon reasonable request.

Additional information

Funding

This work was funded by the National Key R&D Program of China (No.2022YFC3004302), the National Natural Science Foundation of China (Grant No. 41929001), and the Fundamental Research Foundation of the Central Universities (No. 300203211262).