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The present research illustrates the application of a methodological approach to studying the stress–strain distribution in a marble quarry of the Apuan Alps mining area (Italy). This study has been carried out in the framework of a project involving the University of Siena and the UOC Ingegneria Mineraria—USL Toscana Nord-Ovest, Tuscany Region. This stress–strain analysis aims foremost to monitor the slope stability conditions to guarantee a safe workplace for the personnel involved in mining activities, and to enable more sustainable long-term planning for excavation and production. The involved survey activities are as follows: (i) terrestrial laser scanning; (ii) engineering–geological data mapping; and (iii) in situ marble stress measuring through four CSIRO-type cell tests executed in different locations and at various depths within the underground excavation walls. The gathered data converged into numerical models of the quarry, both in 2D (DEM) and 3D (FEM), calibrated by in situ stress results through a rigorous back analysis assessment using least squares procedures. The created models represent a valuable tool for the identification and securing of risk areas and for future excavation planning in respect of the site efficiency and safety.

Cluster analysis of morphometric variable is reported in this paper to support characterization of rock masses and deposits. The first technique is related to fast mechanical characterization of bedrock and the second one on the mapping of the depth of superficial deposits. In order to extrapolate site-specific information to the whole study area two techniques are applied to morphometric space: supervised and unsupervised classifications through the algorithms maximum likelihood and ISODATA, respectively. The analysis of morphometric space with these techniques has provided significant results in order to discriminate bedrocks with different mechanical characteristics and the depth of superficial deposits.

Natural rock slopes require accurate engineering–geological characterization to determine their stability conditions. Given that a natural rock mass is often characterized by a non-uniform fracture distribution, the correct, detailed, and accurate characterization of the discontinuity pattern of the rock mass is essential. This is crucial, for example, for identifying the possibility and the probability of kinematic releases. In addition, complete stability analyses of possible rockfall events should be performed and used to create hazard maps capable of identifying the most dangerous parts of a rock mass. This paper shows a working approach that combines traditional geological surveys and remote sensing techniques for engineering–geological investigations in a natural rock slope in Northern Italy. Discontinuities were identified and mapped in a deterministic way by using semi-automatic procedures that were based on detailed 3D Unmanned Aerial Vehicle photogrammetric-based point cloud data and provided georeferenced representations of thousands of fractures. In this way, detailed documentation of the geo-mechanical and geo-structural characteristics of discontinuities were obtained and subsequently used to create fracture density maps. Then, traditional kinematic analyses and probabilistic stability analyses were performed using limit equilibrium methods. The results were then managed in a GIS environment to create a final hazard map that classifies different portions of the rock slope based on three factors: kinematic predisposition to rockfall (planar sliding, wedge sliding, toppling), fracture density, and probability of failure. The integration of the three hazard factors allowed the identification of the most hazardous areas through a deterministic and accurate procedure, with a high level of reliability. The adopted approach can therefore be very useful to determine the areas in which to prioritize remediation measures with the aim of reducing the level of risk.

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