About this Research Topic
Advances in experimental, analytical, and numerical techniques for characterizing and modeling geohazard evolution mechanism in this field are necessary. The issue seeks articles that address innovative approaches for analyzing slope stability, predicting failure mechanisms, designing effective stabilization measures, and assessing landslides risk. Additionally, we encourage research that explores various engineering geological problems throughout the entire lifecycle of geohazards, such as new protective materials for geohazards, eco-friendly slope stabilization methods, geotechnical aspects of renewable energy projects, or life cycle assessment of geotechnical works. The goal of this special issue is to provide a platform for researchers and practitioners to share their experiences, knowledge, and research outcomes in geomechanics, slope stability, and geohazards.
In this Research Topic, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:
• Mechanical Property of Rock Mass/Soil Mass of Landslide.
• Analytical, Physical and Numerical Techniques in Slope Stability.
• Physical Model Testing and Numerical Simulation.
• Landslide Evolution Mechanism.
• Artificial Intelligence for Geohazards.
• Advances in Sensors and Monitoring Techniques for Geohazards.
• Landslide Multi-source Remote Sensing Identification.
• Landslide Susceptibility Mapping.
• Stability of Rock Mass Surrounding Tunnel.
• Reliability Analysis of Geohazards.
• New Protective Materials for Geohazards.
• Risk Assessment and Hazard Evaluation.
• Causes and Physical Processes of Geohazards.
• Engineering Records of Geohazard Events.
• Monitoring, Forecast and Early Warning Technologies and Methods for Geohazards.
• Prevention and Control Technologies and Methods for Geohazards.
• Big data and Artificial Intelligence Technologies for Geohazard Prevention and Mitigation.
Keywords: Mechanics property, Physical model test, Numerical simulation, Slope stability, Monitoring, Landslide susceptibility mapping, Artificial intelligence, Risk assessment
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.