Remote Sensing for Rock Slope and Rockfall Analysis II

Dear Colleagues,

Rock slope instability is a major and widespread phenomenon that can represent significant hazards, especially in areas characterized by high and steep natural or engineered slopes. As a consequence, depending on magnitude, size and velocity, slope failure and rockfall events can cause severe damage, injuries, and casualties. As such, effective mitigation measures are essential to control their effect. Over the last two decades, with the advent of more sophisticated remote sensing and numerical modelling techniques, the approach to rock slope investigation and monitoring has changed substantially. Remote sensing techniques such as LiDAR, radar, and photogrammetry in rock slope analysis have allowed for the rapid and safe acquisition of a huge amount of high-quality information to be used for slope analyses and monitoring. Such techniques represent valuable tools in rock mechanics. However, it is important to highlight that the use of these data both in conventional and more sophisticated numerical analyses can be complex. In this context, this Special Issue will present novel contributions including original research, case studies, and new approaches in rock slope and rockfall analysis and monitoring that take advantage of remote sensing techniques. This will also comprise the use of recent statistical and geotechnical methods, such as a discrete fracture network and advanced rock laboratory testing, that are able to improve understanding surrounding rock behavior.

Therefore, contributions related to the following topic will be welcome:

• The integration of different remote sensing techniques for rock slope and rockfall analyses;
• Rock mass characterization;
• Rock slope stability assessment;
• Back analysis;
• Rockfall intensity, velocity, and probability assessment;
• Rockfall hazard and risk assessment;
• Rockfall mitigation measures design;
• Rock slope and rockfall monitoring;
• Early warning systems and evacuation planning;
• Numerical modelling.

Dr. Mirko Francioni
Dr. Pooya Hamdi
Dr. Davide Donati
Guest Editors

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