Digital Rock Mass Analysis for the Evaluation of Rockfall Magnitude at Poorly Accessible Cliffs - Davide Caliò; Simone Mineo; Giovanna Pappalardo (Remote Sensing, 2023)
The analysis of a digital rock cliff model, built by airborne photogrammetric data and infrared thermal images, is herein presented as an alternative tool for rock mass study in restricted and poorly accessible areas. Photogrammetric and infrared thermography techniques were combined for the geostructural and morphological characterization of an unstable cliff located in a nature reserve, where the rock mass extension and the environmental preservation rules required the use of minimally invasive surveying solutions. This methodological approach provided quantitative and qualitative data on both the spatial orientation of discontinuities and the location of major structural features, jutting blocks and past rockfall source areas. The digitally derived spatial data were used to carry out a rock mass kinematic analysis, highlighting the most recurring unstable failure patterns. Thermal images were overlapped to the photogrammetric cliff model to exploit the data combination and to analyze the presence of protruding rock mass volumes to be referred to as potential unstable volumes. Based on this activity, rock volumes were quantified on the digital model and the results were used to provide a zonation map of the potential magnitude of future rockfalls threatening the reserve. Digital data were validated by a field surveying campaign, which returned a satisfactory match, proving the usefulness and suitability of the approach, as well as allowing the quick and reliable rock mass characterization in the frame of practical use and risk management purposes.