Quantitative characterization of discontinuities is fundamental to define the mechanical behavior of discontinuous rock masses. Several techniques for the semi-automatic and automatic extraction of discontinuities and their properties from raw or processed point clouds have been introduced in the literature to overcome the limits of conventional field surveys and improve data accuracy. However, most of these techniques do not allow characterizing flat or subvertical outcrops because planar surfaces are difficult to detect within point clouds in these circumstances, with the drawback of undersampling the data and providing inappropriate results. In this case, 2D analysis on the fracture traces are more appropriate. Nevertheless, to our knowledge, few methods to perform quantitative analyses on discontinuities from orthorectified photos are publicly available and do not provide a complete characterization. We implemented scanline and window sampling methods in a digital environment to characterize rock masses affected by discontinuities perpendicular to the bedding from trace maps, thus exploiting the potentiality of remote sensing techniques for subvertical and low-relief outcrops. The routine, named QDC-2D (Quantitative Discontinuity Characterization, 2D) was compiled in MATLAB by testing a synthetic dataset and a real case study, from which a high-resolution orthophoto was obtained by means of Structure from Motion technique. Starting from a trace map, the routine semi-automatically classifies the discontinuity sets and calculates their mean spacing, frequency, trace length, and persistence. The fracture network is characterized by means of trace length, intensity, and density estimators. The block volume and shape are also estimated by adding information on the third dimension. The results of the 2D analysis agree with the input used to produce the synthetic dataset and with the data collected in the field by means of conventional geostructural and geomechanical techniques, ensuring the procedure’s reliability. The outcomes of the analysis were implemented in a Discrete Fracture Network model to evaluate their applicability for geomechanical modeling.

Foreseeing the failure of important unstable volumes is a major concern in the Alps, especially due to the presence of people and infrastructures in the valleys. The use of monitoring and remote sensing techniques is aimed at detecting potential instabilities and the combination of several techniques permits the cross-validation of the detected movements. Supplemented with field mapping and structural analysis, it is possible to define possible scenarios of rupture in terms of volume, mechanisms of failure and susceptibility. A combined observation strategy was applied to the study of major instability located in the Ticinese Alps (Switzerland), Cima del Simano, where the monitoring started in 2006 with the measurement of opened cracks with extensometers. Since 2021, the monitoring has been completed by LiDAR, satellite and GB-InSAR observations and structural analysis. Here, slow but constant movements of about 7 mm/yr were detected along with rockfall activities near the Simano summit. Eight failure scenarios of various sizes ranging from 2.3 × 10⁵ m³ to 51 × 10⁶ m³, various mechanisms (toppling, planar, wedge and circular sliding) and various occurrence probabilities were defined based on the topography and the monitoring results and by applying a Slope Local Base Level (SLBL) algorithm. Weather acquisition campaigns by means of thermologgers were also conducted to suggest possible causes that lead to the observed movements and to suggest the evolution of the instabilities with actual and future climate changes.

Based on a previous risk calculation study conducted along a road corridor, risk is recalculated using a stochastic simulation by introducing variability into most of the parameters in the risk equation. This leads to an exceedance curve comparable to those of catastrophe models. This approach introduces uncertainty into the risk calculation in a simple way, and it can be used for poorly documented cases to compensate for a lack of data. This approach tends to minimize risk or question risk calculations.

Synthetic Aperture Radar (SAR) acquisition can be performed from satellites or from the ground by means of a so-called GB-InSAR (Ground-Based Interferometry SAR), but the signal emission and the output image geometry slightly differ between the two acquisition modes. Those differences are rarely mentioned in the literature. This paper proposes to compare satellite and GB-InSAR in terms of (1) acquisition characteristics and parameters to consider; (2) SAR image resolution; and (3) geometric distortions that are foreshortening, layover, and shadowing. If in the case of satellite SAR, the range and azimuth resolutions are known and constant along the orbit path, in the case of GB-InSAR their values are terrain-dependent. It is worth estimating the results of a GB-InSAR acquisition that one can expect in terms of range and azimuth resolution, line of sight (LoS) distance, and geometric distortions to select the best installation location when several are possible. We developed a novel tool which estimates those parameters from a digital elevation model (DEM), knowing the GB-InSAR and the slope of interest (SoI) coordinates. This tool, written in MATLAB, was tested on a simple synthetic point cloud representing a cliff with a progressive slope angle to highlight the influence of the SoI geometry on the acquisition characteristics and on two real cases of cliffs located in Switzerland, namely one in the Ticino canton and one in the Vaud canton.

Synthetic Aperture Radar (SAR) acquisition can be performed from satellites or from the ground by means of a so-called GB-InSAR (Ground-Based Interferometry SAR), but the signal emission and the output image geometry slightly differ between the two acquisition modes. Those differences are rarely mentioned in the literature. This paper proposes to compare satellite and GB-InSAR in terms of (1) acquisition characteristics and parameters to consider; (2) SAR image resolution; (3) geometric distortions that are foreshortening, layover and shadowing. If in the case of satellites SAR, the range and azimuth resolutions are known and constant along the orbit path, in the case of GB-InSAR their values are terrain-dependent. It is worth estimating the results of a GB-InSAR acquisition one can expect in terms of range and azimuth resolution, Line of Sight (LoS) distance and geometric distortions to select the best installation location when several are possible. We developed a tool which estimates those parameters from a Digital Elevation Model (DEM), knowing the GB-InSAR and the Slope of Interest (SoI) coordinates. This tool, written in MATLAB, was tested on a simple synthetic point cloud representing a cliff with a progressive slope angle to highlight the influence of the SoI geometry on the acquisition characteristics and on two real cases; cliffs located in Switzerland, one in the Ticino canton and on in the Vaud canton.

Rock avalanches, characterized by rapid, high-energy flows of fragmented rock, pose significant hazards and risks in mountainous regions. Anticipating their potential impact area and run-out distance is crucial in the scope of hazard assessment. Two main approaches, empirical and numerical, are commonly employed for this purpose. Most research uses these methods for back-analyzing past rock avalanche events, where the runout distance and impacted areas are known. In this study, focusing on the Cima del Simano instability (Swiss Alps), the potential impacted area and the maximum run-out distance are evaluated for two potential future scenarios of failure, S1 and SS1, characterized by a volume of 4.30 × 10 ⁶ m ³ and 2.30 × 10 ⁶ m ³ , respectively. Empirical power-law relationships are applied to estimate run-out distances. They are confronted with results obtained with numerical simulations, using the Voellmy rheology model where the two parameters describing the flow behavior are carefully selected based on a literature review. The analysis reveals challenges in matching empirical and numerical results in a context of propagation frontally obstructed by the presence of an opposite valley flank. Nonetheless, a maximum run-out distance is suggested by comparing the results. Additional information regarding the probability of run-out exceedance and the maximum distance impacted by the rock avalanche air blast is also provided. In addition, based on the numerical simulations, this work identifies potential locations in gullies where debris can accumulate during rock avalanche propagations. The accumulation of materials due to successive rockfall or rockslide events can fill the channels present on the west flank of the slope. They can trigger in the future more frequent debris flow events and/or mobilize larger volumes of materials. A debris flow susceptibility assessment through numerical simulations is conducted helping in the assessment of the maximum run-out distance susceptible to be impacted by future debris flow events. The results align with the locations of previous debris flow and snow avalanche events. This work offers valuable insights for hazard assessment and emphasizes the importance of the topography during the propagation and the complexity of cascading events.