Three-dimensional modelling of artificial caves for geomechanical analysis

In the Apulia region (southeastern Italy) we are monitoring a soft-rock coastal cliff using webcams and strain sensors. In this urban and touristic area, coastal recession is extremely rapid and rockfalls are very frequent. In our work we are using low-cost and open-source hardware and software, trying to correlate both meteorological information with measures obtained from crack meters and webcams, aiming to recognize potential precursor signals that could be triggered by instability phenomena.

Based on stability charts proposed by Perrotti et al. (2018), preliminary assessment of stability/instability of underground quarries in soft carbonate rocks is discussed with reference to six case studies of underground artificial cavities, including three affected by sinkhole failures in the past and three in stable conditions at present. When underground quarries are suitably surveyed and mapped, a quantitative assessment of the stability conditions is possible.

We compare three different instruments used to collect snow depth, i.e., photogrammetric surveys using Unmanned Aerial Systems (UAS), a 3D laser scanning, and manual probing. The relatively high density of manual data (135 pt over 6700 m², i.e., 2 pt/100 m²) enables to assess the performance of UAS in capturing the marked spatial variability of snow. Results suggest that UAS represent a competitive choice among existing techniques for high-precision, high-resolution remote sensing of snow.