About this Research Topic
In recent decades, natural and engineering disasters such as earthquakes, landslides, rockfall, debris flow, rainstorms, floods, tunnel collapse, dam failure, and wildfires have brought many challenging engineering geologic and geotechnical problems to the design, construction, and service of infrastructures in mountainous areas. Landslides are one of the most prevalent natural catastrophes on Earth, with strong concealment, wide distribution, and suddenness, posing great risks to people’s life and property. As a result, it has significant theoretical and application value to conduct a risk assessment and stability analysis for landslide disasters, as well as to realize early warning and implement effective control measures.
Many new numerical methods, such as CDEM (continuum-based discrete element method), 3D-DDA (three-dimensional discontinuous deformation analysis), NMM (numerical manifold method), SPH (smoothed particle hydrodynamics), MPM (material point method), and LBM (Lattice Boltzmann Method), have emerged in response to the characteristics of landslide disasters. Advanced assessment methods, e.g., deep learning and artificial intelligence, have attracted great attention from academia and industry. Advanced monitoring tools, including InSAR (Interferometric Synthetic Aperture Radar), UAV (Unmanned Aerial Vehicle), Fiber Optics, Beidou, and MEMS (Micro-Electro-Mechanical System) have been employed in terms of prevention technologies.
This Research Topic aims to better the quantitative understanding of landslide processes and dynamics. We welcome submissions of Original Research and Review articles addressing theoretical derivations, field investigations, laboratory tests, and numerical and physical modeling. Key themes include, but are not limited to:
• Structural and geomorphological features of landslides at various scales
• Indoor laboratory physical modeling of landslides
• Theoretical analysis on the formation mechanism of landslides
• Risk and stability assessment method for landslides
• Applications of advanced earth observation technologies in landslides
• Numerical simulation of landslides subjected to rainfall and earthquake
• In-depth controlling factor analysis of landslides
• Time-series analysis of sensor data for landslides monitoring
Many new numerical methods, such as CDEM (continuum-based discrete element method), 3D-DDA (three-dimensional discontinuous deformation analysis), NMM (numerical manifold method), SPH (smoothed particle hydrodynamics), MPM (material point method), and LBM (Lattice Boltzmann Method), have emerged in response to the characteristics of landslide disasters. Advanced assessment methods, e.g., deep learning and artificial intelligence, have attracted great attention from academia and industry. Advanced monitoring tools, including InSAR (Interferometric Synthetic Aperture Radar), UAV (Unmanned Aerial Vehicle), Fiber Optics, Beidou, and MEMS (Micro-Electro-Mechanical System) have been employed in terms of prevention technologies.
This Research Topic aims to better the quantitative understanding of landslide processes and dynamics. We welcome submissions of Original Research and Review articles addressing theoretical derivations, field investigations, laboratory tests, and numerical and physical modeling. Key themes include, but are not limited to:
• Structural and geomorphological features of landslides at various scales
• Indoor laboratory physical modeling of landslides
• Theoretical analysis on the formation mechanism of landslides
• Risk and stability assessment method for landslides
• Applications of advanced earth observation technologies in landslides
• Numerical simulation of landslides subjected to rainfall and earthquake
• In-depth controlling factor analysis of landslides
• Time-series analysis of sensor data for landslides monitoring
Keywords: landslides, laboratory experiments, computational geosciences, numerical simulation, stability analysis, spatial distribution, monitoring method, disaster mitigation
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.
