Slope Stability Analyses and Risk Assessment for Rainfall-Induced Landslides

Dear Colleagues,

Rainfall-induced landslides are common geological disasters worldwide, often posing a significant threat to mining safety and slope stability. The accurate and effective monitoring, early warning, and prevention of such disasters are currently of the utmost importance. In recent years, similar physical model experiments, numerical simulations (FEM, DEM), machine learning techniques (CNN, ANN, SVM, etc.), and computer vision algorithms (IRGSM, SLIC, K-means, etc.) have been applied to various scenarios such as mines, tailings ponds, dams, and highway slopes in order to advance the development of relevant theories and advanced technologies for rainfall-induced landslides. Herein, the key point of slope stability analysis and landslide risk assessment lie in accurately predicting or reducing landslide risks caused by heavy rainfall and providing necessary information in conjunction with reasonable rules, regulations, and emergency measures.

Therefore, the purpose of this Special Issue is to provide original research and review articles on the study of complex failure mechanisms associated with rainfall-induced landslides, the formulation of reasonable and effective measures for risk mitigation, as well as advanced theoretical and technical analysis of slope stability. In particular, we encourage researchers and engineers to share their advanced research on the monitoring, assessing, early warning, and evacuation of rainfall-induced landslides.

Potential topics include, but are not limited to, the following:

• Monitoring and identification technologies for areas prone to rainfall-induced landslides.
• Laboratory testing methods for geotechnical properties associated with rainfall-induced landslides.
• Stability analysis and evaluation of mine slopes under heavy rainfall.
• Numerical simulation of mine slope stability under multi-field coupling, regarding rainwater and other factors.
• Advanced computer vision algorithms related to rainfall-induced landslides.
• Machine learning algorithm for predicting rainfall-induced landslide disasters.
• Investigation and theoretical analysis of the failure mechanism of rainfall-induced landslides.
• Comprehensive assessment of risks and hazards associated with rainfall-induced landslides.
• Policies and measures to mitigate landslide hazards caused by rainfall.
• Methods and feasibility analysis for personnel evacuation after rainfall-induced landslide disasters.

Dr. Qihang Li
Prof. Dr. Xiaoshuang Li
Prof. Dr. Jiang Song
Guest Editors

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