The study of strain effects in thermally-forced rock masses has gathered growing interest from engineering geology researchers in the last decade. In this framework, digital photogrammetry and infrared thermography have become two of the most exploited remote surveying techniques in engineering geology applications because they can provide useful information concerning geomechanical and thermal conditions of these complex natural systems where the mechanical role of joints cannot be neglected. In this paper, a methodology is proposed for generating point clouds of rock masses prone to failure, combining the high geometric accuracy of RGB optical images and the thermal information derived by infrared thermography surveys. Multiple 3D thermal point clouds and a high-resolution RGB point cloud were separately generated and co-registered by acquiring thermograms at different times of the day and in different seasons using commercial software for Structure from Motion and point cloud analysis. Temperature attributes of thermal point clouds were merged with the reference high-resolution optical point cloud to obtain a composite 3D model storing accurate geometric information and multitemporal surface temperature distributions. The quality of merged point clouds was evaluated by comparing temperature distributions derived by 2D thermograms and 3D thermal models, with a view to estimating their accuracy in describing surface thermal fields. Moreover, a preliminary attempt was made to test the feasibility of this approach in investigating the thermal behavior of complex natural systems such as jointed rock masses by analyzing the spatial distribution and temporal evolution of surface temperature ranges under different climatic conditions. The obtained results show that despite the low resolution of the IR sensor, the geometric accuracy and the correspondence between 2D and 3D temperature measurements are high enough to consider 3D thermal point clouds suitable to describe surface temperature distributions and adequate for monitoring purposes of jointed rock mass.

Highlights We used array-based ambient vibration modal analysis and eigenfrequency modeling to characterize the dynamic behavior and structural conditions of a partly collapsed lava tube roof. Multiple resonance modes were identified from spectral and cross-correlation analyses, and used to calibrate a heterogeneous numerical model of the lava tube. Our study shows that the combination of experimental and numerical modal analysis is a valuable tool for mapping and structural characterization of underground cavity roofs.

The Maltese archipelago is renowned for its spectacular coasts, characterized by vertical cliffs and scree slopes. In the western sector of Malta and the eastern region of Gozo, a marly clay formation with ductile properties underlying a stiff limestone unit has led to relevant lateral spreading. Utilizing drone aerial photogrammetry, digital elevation models, and satellite imagery, we analyzed the ongoing geomorphological processes across five promontories, selected as case studies. Our analysis reveals a complex interaction between geological structures, Quaternary sea level fluctuations, and lateral spreading processes. Photogrammetric models show that once detached, blocks from the plateaus tend to topple and fall or experience subsidence and backtilting. At Rdum il-Qammieħ, fractures up to 250 m long and openings of up to 2 m were observed, while at Sopu, detached blocks exhibit subsidence of up to 50% and rotations nearing 60°. In all the studied promontories, rotational slides predominantly occur at the frontal sectors, while toppling mechanisms are more common along scarp-edged plateaus. The thickness ratio between the stiff and the ductile formation, ranging from 0.13 to 1.12, along with slope gradients between 10° and 41°, further influence the stability of these coastal features. We discuss the structural and sea level influences on Maltese coastal cliff development over the last 125 ky. We propose a conceptual model outlining the evolution of the Malta Graben promontories through a three-stage evolutionary model: proto-promontories, cliff demolition, and isolation. This model emphasizes the significant role of predisposing, preparatory, and triggering factors in the geomorphological evolution of the Maltese coastline. Our findings provide essential insights into the landscape changes in the Maltese archipelago and represent a useful tool for coastal management and hazard mitigation strategies.

The study of the deformation of rock masses in response to near-surface thermal stresses is nowadays considered crucial in the field of geological risk mitigation. The superposition of heating and cooling cycles can influence the mechanical behavior of rock masses by inducing inelastic deformations that can trigger shallow slope instabilities, such as rockfalls and rock topples. This study reports the main outcomes obtained from the analysis of 20 month long microseismic monitoring at the Acuto field laboratory (Central Italy), where an integrated geotechnical and geophysical monitoring system has been operating since 2015. A preliminary event classification was performed through the analysis of time- and frequency-domain characteristic features of the extracted waveforms. Furthermore, the evolution of the local microseismicity was explored as a function of environmental factors (i.e., rock and air temperature, thermal gradients and ranges, and rainfalls) to highlight potential correlations. The here presented results highlight nontrivial insights into the role played by continuous near-surface temperature fluctuations and extreme thermal transients in influencing the stability of rock masses. In particular, the comparison of monitoring periods characterized by the most intense microseismic activity highlights a peculiar distribution of microseismicity during the heating and cooling phases of the rock mass in relation to different environmental conditions. These behaviors can be interpreted as the consequence of different driving mechanisms at the base of local failures.

Progressive fracturing contributes to structural degradation of natural rock arches and other freestanding rock landforms. However, methods to detect structural changes arising from fracturing are limited, particularly at sites with difficult access and high cultural value, where non-invasive approaches are essential. This study aims to determine how fractures affect the dynamic properties of rock arches, focusing on resonance modes as indicators of structural health conditions. We hypothesize that damage resulting from fracture propagation may influence specific resonance modes that can be identified through ambient vibration modal analysis. We characterized the dynamic properties (i.e., resonance frequencies, damping ratios, and mode shapes) of Hunter Canyon Arch, Utah (USA), using spectral and cross-correlation analyses of data generated from an array of nodal geophones. Results revealed properties of nine resonance modes with frequencies between 1 and 12 Hz. Experimental data were then compared to numerical models with homogeneous and heterogeneous compositions, the latter implementing weak mechanical zones in areas of mapped fractures. All numerical solutions replicated the first two resonance modes of the arch, indicating these modes are insensitive to structural complexity derived from fractures. Meanwhile, heterogenous models with discrete fracture zones succeeded in matching the frequency and shape of one additional higher mode, indicating this mode is sensitive to the presence of fractures and thus most likely to respond to structural change from fracture propagation. An evolutionary crack damage model was then applied to simulate fracture propagation, confirming that only this higher mode is sensitive to structural damage resulting from fracture growth. While examination of fundamental modes is common practice in structural health monitoring studies, our results suggest that analysis of higher-order resonance modes can be more informative for characterizing fracture-driven structural damage.