Prediction analysis of landslide displacement trajectory based on the gradient descent method with multisource remote sensing observations

Abstract

Landslides can result in extensive casualties and huge economic losses. The accurate discrimination of the main slip direction and deformation trajectory is an important prerequisite for studying landslide formation mechanisms and designing landslide control schemes. In the process of landslide evolution over time, the main slip direction also changes dynamically and provides a comprehensive reflection of the landslide displacement state. However, few studies on this topic have been published. In this paper, a new methodology for analyzing slope stability is proposed based on three techniques: interferometric synthetic aperture radar (InSAR), unmanned aerial vehicle (UAV), and ground-based interferometric synthetic aperture radar (GB-InSAR). The Small Baseline Subset Interferometric SAR (SBAS-InSAR) technique is combined with an overall analysis of the study area to identify the regions of interest (ROIs) with large deformation and the starting target points, and the fusion results of radar deformation data (RDD) and digital surface model (DSM) data are used to fit the deformation surface field of the ROIs. The gradient descent approach is executed to obtain the running trajectory points of the target masses so that the main slip direction and displacement trajectory in the study area can be predicted at small scales. The measured data for the Hongshiyan landslide in Yunnan Province are used to verify the effectiveness of the method, and the predicted results are consistent with the actual landslide direction. The experimental results show that the method can exactly identify the deformation area, especially in the case of a fast-changing deformation trend. This approach can provide more accurate monitoring area results to support the rapid control and prevention of landslide hazards by analyzing the minimum pixel grid (i.e. points), as the smallest spatial unit at a time interval of minutes. The study shows that the method can efficiently combine space–Earth multisource monitoring data to clarify the main slide direction and improve the postslide trajectory prediction of the slope, which is beneficial for assessing disaster risks and improving landslide prevention and control effects, reflecting the engineering application value of the approach.

Keywords:

• main slip direction
• deformation trajectory
• slope stability
• space–earth multisource monitoring data
• landslide monitoring

Acknowledgments

We would like to thank Tong Jiang of the College of Surveying and Geo-informatics, North China University of Water Resources and Electric Power (Zhengzhou), for providing comments and writing suggestions. We would also like to thank the anonymous reviewers and the editors for their comments.

Authors’ contributions

All authors contributed to the manuscript and discussed the results. Jiabao Wang and Tianjie Lei developed the idea that led to this paper. Jiabao Wang performed Sentinel-1A data processing, designed the experiments, analyzed the data, and wrote the first draft. Wenkai Liu provided critical comments and contributed to the final revision of the paper. Yijin Chen, Baoyin Liu, and Jianwei Yue gave suggestions for modifications to the manuscript. In addition, all authors contributed to the final revision of the manuscript.

Disclosure statement

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

Data availability statement

Self‐collected datasets that support the findings of this study are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by The Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences.