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The first borehole 5071_1_B of the ICDP‐Drilling the Ivrea‐Verbano zonE (DIVE) project in Italy, which intersects the Massone antiform, provides a unique opportunity to integrate downhole geophysical measurements with observations from 100% recovered drill core in rarely drilled lithologies. The objective of this study is to petrophysically and structurally characterize the rock mass and constrain factors influencing the seismic velocity in the lower continental crust. A comprehensive data set, comprising core, well log and vertical seismic profiling data, was collected. The structural analysis indicates that the axial plane of the intersected tightly folded antiform is slightly tilted at the borehole location and thus the borehole intersects the hinge zone at the top and its limb in the lower part of 5071_1_B. Numerous open natural fractures with variable dips and two dominant dip azimuthal orientations are identified along the borehole, which affect the electrical and acoustic properties. The velocities at the core, well log and seismic scale are consistent but lower than intrinsic seismic velocities of the lower continental crust, since they are not only affected by fractures but also by micro cracks at the 5071_1_B in situ conditions. A systematic lithology correlation is not evident for these properties. However, a cluster analysis of gamma ray and magnetic susceptibility logs shows an excellent agreement with the logged core lithologies in the presence of remarkable spatial variability. Furthermore, the main lithologies are grouped into three distinct clusters, suggesting two types of kinzigites with distinct magnetic and radiogenic properties. Plain Language Summary: The first borehole 5071_1_B of the ICDP‐Drilling the Ivrea‐Verbano zone (DIVE) project in Italy, which intersects a prominent fold structure, provides a unique opportunity to integrate downhole geophysical measurements with observations from 100% recovered drill core in rarely drilled rock types. This study aims to characterize the structural properties and rock types encountered in 5071_1_B as well as factors that influence seismic velocity in the lower continental crust. The structural analysis shows that the axis of the fold is tilted at the borehole location. This means that the borehole intersects its hinge zone at the top and its limb in the lower part of 5071_1_B. Many open fractures are found with different dip angles and two main orientations. These fractures affect the electrical and acoustic properties. Gamma ray and magnetic susceptibility logs are used in a geostatistical analysis to identify different rock types. The results match the rock types identified on the drill cores very well. The P‐ and S‐wave velocities at the core, well log and seismic scale are consistent but lower than the velocities of the lower continental crust at great depth. This is because they are affected by fractures and microcracks at the 5071_1_B pressure conditions. Key Points: The axial plane of the Massone antiform dips a few degrees to the west‐northwest in the vicinity of the borehole 5071_1_BThe cluster analysis of gamma and magnetic susceptibility logs agrees well with core lithologies given the notable spatial variabilityVelocities are consistent across the core, log and seismic scales, governed by brittle deformation and locally correlate with lithologies [ABSTRACT FROM AUTHOR]

Determining the mechanical characteristics of rocks is crucial in various civil engineering sectors. Traditionally, the mechanical properties of rocks are determined through on-site and laboratory tests carried out during geotechnical surveys. However, these extensive surveys require considerable time and resources. In contrast, hyperspectral remote sensing techniques offer a rapid and simple means to determine the mineral composition and crystallographic structure of rocks. These features, in turn, influence the rocks' mechanical properties. This study focuses on characterizing the mechanical properties of carbonate rocks in a laboratory setting, using hyperspectral sensors. Approximately 150 cylindrical carbonate rock samples, spanning a wide strength range, were collected from diverse Israeli rock outcrops. Employing a point spectrometer (0.4 to 2.5 µm) and a spectral image sensor (8.0 to 12.0 µm), we captured samples' light reflections and spectral emissivity. Mechanical attributes, including density, porosity, water absorption, and uniaxial compressive strength (UCS), were measured. Advanced data mining techniques identified statistical correlations between hyperspectral signatures and mechanical properties, pinpointing key wavelengths for prediction. The developed models exhibited excellent predictability for the specified properties, attributing accuracy to discernible mineralogy and internal crystalline structure through spectroscopy. However, predicting UCS showed slightly weaker results due to influences from internal flaws not entirely reflected in spectroscopic data. Nonetheless, outcomes regarding rock UCS were deemed satisfactory. These findings open avenues for non-destructive tools in assessing the mechanical properties of rocks in quarrying operations. Highlights: We developed a new method for evaluating the mechanical properties of carbonate rocks using non-destructive spectroscopy. We applied sophisticated data mining techniques to identify statistical correlations between the hyperspectral signatures and mechanical properties of rock samples. We found the key wavelengths for predicting density, porosity, water absorption, and uniaxial compressive strength of the rock samples. The ability to assess the mechanical properties of intact rocks through remote sensing can improve the fieldwork of an engineering geologist. [ABSTRACT FROM AUTHOR]

Rockfall phenomena are considered highly dangerous due to their rapid evolution and difficult prediction without applying preventive monitoring and mitigation actions. This research investigates a hazardous site in the Municipality of Vecchiano (Province of Pisa, Italy), characterized by vertical rock walls prone to instability due to heavy fracturing and karst phenomena. The presence of anthropical structures and a public road at the bottom of the slopes increases the vulnerability of the site and the site's risk. To create a comprehensive geological model of the area, Unmanned Aircraft System (UAS) photogrammetric surveys were conducted to create a 3D model useful in photointerpretation. In accessible and safe areas for personnel, engineering–geological surveys were carried out to characterize the rock mass and to define the portion of rock walls to be monitored. Results from nine multitemporal Robotic Total Station (RTS) measurement campaigns show that no monitoring prisms recorded significant displacement trends, both on the horizontal and vertical plane and in differential slope distance. Additionally, satellite Persistent Scatterer Interferometry (PSI) analysis indicates that the slopes were stable over the two years of study. The integration of these analysis techniques has proven to be an efficient solution for assessing slope stability in this specific rockfall-prone area. [ABSTRACT FROM AUTHOR]

Abstract The first borehole 5071_1_B of the ICDP‐Drilling the Ivrea‐Verbano zonE (DIVE) project in Italy, which intersects the Massone antiform, provides a unique opportunity to integrate downhole geophysical measurements with observations from 100% recovered drill core in rarely drilled lithologies. The objective of this study is to petrophysically and structurally characterize the rock mass and constrain factors influencing the seismic velocity in the lower continental crust. A comprehensive data set, comprising core, well log and vertical seismic profiling data, was collected. The structural analysis indicates that the axial plane of the intersected tightly folded antiform is slightly tilted at the borehole location and thus the borehole intersects the hinge zone at the top and its limb in the lower part of 5071_1_B. Numerous open natural fractures with variable dips and two dominant dip azimuthal orientations are identified along the borehole, which affect the electrical and acoustic properties. The velocities at the core, well log and seismic scale are consistent but lower than intrinsic seismic velocities of the lower continental crust, since they are not only affected by fractures but also by micro cracks at the 5071_1_B in situ conditions. A systematic lithology correlation is not evident for these properties. However, a cluster analysis of gamma ray and magnetic susceptibility logs shows an excellent agreement with the logged core lithologies in the presence of remarkable spatial variability. Furthermore, the main lithologies are grouped into three distinct clusters, suggesting two types of kinzigites with distinct magnetic and radiogenic properties.

Ischia (Southern Italy) is a volcanic island of the Phlegrean Volcanic District that was historically affected by multiple geological hazards, including floodings, landslides, rockfalls, and earthquakes. In this study, rockfall stability is analysed with an integrated approach aimed at investigating the rockfall source, the propagation, and the deposition areas. The case study is represented by two outcrops over a 400-m-wide cliff made of Green Tuff and located on the western area of Mt. Epomeo. They are respectively located at 280 and 420 m a.s.l., just uphill the village of Frassitelli, Forio d’Ischia, which is an area of high residential, tourist, and agricultural importance. We analysed the fracture systems of the tuff cliff to compute the kinematic analysis of the potential failure mechanisms and to perform numerical simulations of rockfall scenarios. Successively, numerical simulations of rockfall scenarios were computed based on the acquired structural information. This allowed us to identify the most hazardous scenarios based on the rock trajectories and the percentage of rock blocks affecting the urban area. The influence of the rock shape and volume on the rockfall trajectories was analysed. In the most likely scenarios, we observed that 15–25% of the rock blocks bypass the geomorphological barriers and reach the urban area, with kinetic energy values spanning between 102 and 104 kJ. Such detailed rockfall hazard analysis allowed the definition of the mitigation interventions necessary for the protection of the nearby residential area. [ABSTRACT FROM AUTHOR]

Technological advancements have made rock engineering more data-driven, leading to increased use of machine learning (ML). While the use of ML in rock engineering has the potential to transform the industry, several methodological issues should first be addressed: (i) rock engineering's use of biased (poor quality) data, resulting in biased ML models and (ii) limited rock mass classification and characterization data. If these issues are not addressed, rock engineering risks using unreliable ML models that can have potential real-life adverse impacts. This paper aims to provide an overview of these methodological issues and demonstrate their impact on the reliability of ML models using surrogate models. To take full advantage of the benefits of ML, rock engineers should make sure that their ML models are reliable by ensuring that there are sufficient unbiased data to develop reliable ML models. In the context of this paper, the term sufficient retains a relative meaning since the amount of data that is sufficient to develop reliable a ML models depends on the problem under consideration and the application of the ML model (e.g., pre-feasibility, feasibility, design stage). [ABSTRACT FROM AUTHOR]

Mudurnu County, situated in northwestern Turkey, is a prominent settlement area because it is located on major trade routes (i.e., the Silk Road and the Crimean Road) and has served as a trading town and a military base in the Byzantine, Seljuk, and Ottoman periods. Mudurnu County is affected by regional complex rock slope instabilities that pose a substantial hazard to the settlement area and generate regional risk to human life, buildings, houses, and industrial facilities. Mudurnu, because of its invaluable historical structures, has been nominated for the UNESCO World Heritage List. Yet, those historical structures are threatened by the rock instabilities. The aim of the paper is to characterize the rock mass on the western slopes of the Mudurnu Valley, through geomechanical evaluation of the rock and empirical assessment of the slope instabilities. The engineering geological and geomechanical properties of the area were acquired via a 3D point cloud together with field scan-line surveys. The western slope of the Mudurnu Valley was divided into 11 geomechanically uniform sectors. Classification of the sectors using the SMR and Q-slope methods demonstrated that the rock mass was prone to complex planar, wedge, and toppling failures. Proper identification of such complex failures was performed using a decision tree methodology. Estimation of the probabilities of the complex failures was accomplished using empirical classifications and field observations. It was found that Sector 8 was the most critical for combined toppling and wedge failures, as well as toppling with a combination of planar and wedge failures. In addition, Sector 6 was the most critical for combined toppling and planar failures. [ABSTRACT FROM AUTHOR]

Stope design is an important part of mine planning, and it aims to balance ore recovery, ore dilution, and production costs without compromising the safety aspects. This paper summarizes the main results from the research, which aims to introduce new techniques to describe the ore body and surrounding rock mass at the tunnel face prior to stope excavation. The research comprises a literature review and a survey among mining professionals to assess current stope design practices. The study identifies geotechnical data, software improvements, and integration of design into mine planning as the most critical areas for improvement. The empirical part of the study proposes new techniques for fast data acquisition. The laser-induced breakdown spectrometry (LIBS) technique is developed for measurements at the tunnel face and from core boxes to provide mineralogical and geometallurgical data. Ground-penetrating radar (GPR) studies are conducted to improve discontinuity characterization, and rapid photogrammetric methods are proposed for efficient tunnel geometry characterization. The techniques discussed in this paper already have many industrial applications. This study reveals their potential to be adopted and further developed to serve ore and rock mass characterization for stope design. [ABSTRACT FROM AUTHOR]

Abstract In heterogeneous and fractured rock masses, joints are the most important elements controlling the hydraulic conductivity. Joints parameters are therefore crucial for estimating transport of mass and energy in many technical problems (e.g., slope stability, tunnels, geothermal and oil and gas studies). Hydraulic conductivity conceptual models follow well understood generalizations, but their quantitative estimation is not simple. Both laboratory and field tests have many limitations due to representativeness and scale effects. This study proposes a methodology for a preliminary hydraulic conductivity estimation in fractured and/or heterogeneous rock masses through a combination of in-situ geomechanical and geophysical measurements. Contact and no-contact geomechanical surveys were coupled with electric resistivity topographies in two selected test sites within a Mexican geothermal area in the framework of the Ge-Mex H2020 project. The test sites are representative of two different geological settings: a faulted rock mass with expected high hydraulic conductivity in proximity of the faulted areas and an abandoned marble quarry, with very good mechanical characteristics and negligible degree of fracturing. Moreover, both of them are located in remote areas with limited accessibility, in which rapid, time and cost-effective procedures are welcomed and recommended. The preliminary findings of this study were promising: estimated hydraulic conductivities were compared with independent laboratory measurements performed by other researchers showing a good correspondence and reliability. The proposed methodology demonstrated its reliability in decision making, in the technical support and its economical applicability also in similar difficult logistic situations. Article Highlights A combination of in-situ geomechanical and geophysical measurements was adopted for a preliminary hydraulic conductivity estimation; Obtained field data were compared with independent laboratory estimations to assess the reliability of the proposed approach and compare representativeness and scale effects; Even given the difficult logistic conditions and the limitations of the available comparisons the proposed methodology demonstrated its reliability in decision making.

Rockfall phenomena are considered highly dangerous due to their rapid evolution and difficult prediction without applying preventive monitoring and mitigation actions. This research investigates a hazardous site in the Municipality of Vecchiano (Province of Pisa, Italy), characterized by vertical rock walls prone to instability due to heavy fracturing and karst phenomena. The presence of anthropical structures and a public road at the bottom of the slopes increases the vulnerability of the site and the site’s risk. To create a comprehensive geological model of the area, Unmanned Aircraft System (UAS) photogrammetric surveys were conducted to create a 3D model useful in photointerpretation. In accessible and safe areas for personnel, engineering–geological surveys were carried out to characterize the rock mass and to define the portion of rock walls to be monitored. Results from nine multitemporal Robotic Total Station (RTS) measurement campaigns show that no monitoring prisms recorded significant displacement trends, both on the horizontal and vertical plane and in differential slope distance. Additionally, satellite Persistent Scatterer Interferometry (PSI) analysis indicates that the slopes were stable over the two years of study. The integration of these analysis techniques has proven to be an efficient solution for assessing slope stability in this specific rockfall-prone area.

The assessment of landslide hazard related to slopes in fractured rock masses is generally correlated with the probability of occurrence of potential rockfall phenomena. The propensity to detachment of rock blocks can be defined through direct or indirect approaches. The first, widely used for decades, is regulated by the International Society for Rock Mechanics recommendations, and provides for the definition of a series of parameters for discontinuities that cross a line designated by the operator, according to the so-called “scanline” methodology. The most applied indirect approaches are based on the construction of a 3D model of the studied front through input data acquired by a digital camera, laser scanner or radar. These two different approaches were used to analyze the discontinuities orientation of a rocky slope on the west side of Mt. Pellegrino (northern Sicily). In this context, it is essential to anticipate rockfall, given the presence of densely urbanized areas at the foot of the rocky slope. The main discontinuity sets were obtained from traditional geo-structural analysis and 3D Point Cloud model of the slope; the latter were derived by applying the Structure from Motion technique on frames captured during the surveys. The kinematic analysis applied to the obtained data allowed us to define from a geomechanical perspective, the main modes of failure. Moreover, back analyses were carried out on the already collapsed blocks to reveal the most likely rockfall volume and reached distance. [ABSTRACT FROM AUTHOR]

In heterogeneous and fractured rock masses, joints are the most important elements controlling the hydraulic conductivity. Joints parameters are therefore crucial for estimating transport of mass and energy in many technical problems (e.g., slope stability, tunnels, geothermal and oil and gas studies). Hydraulic conductivity conceptual models follow well understood generalizations, but their quantitative estimation is not simple. Both laboratory and field tests have many limitations due to representativeness and scale effects. This study proposes a methodology for a preliminary hydraulic conductivity estimation in fractured and/or heterogeneous rock masses through a combination of in-situ geomechanical and geophysical measurements. Contact and no-contact geomechanical surveys were coupled with electric resistivity topographies in two selected test sites within a Mexican geothermal area in the framework of the Ge-Mex H2020 project. The test sites are representative of two different geological settings: a faulted rock mass with expected high hydraulic conductivity in proximity of the faulted areas and an abandoned marble quarry, with very good mechanical characteristics and negligible degree of fracturing. Moreover, both of them are located in remote areas with limited accessibility, in which rapid, time and cost-effective procedures are welcomed and recommended. The preliminary findings of this study were promising: estimated hydraulic conductivities were compared with independent laboratory measurements performed by other researchers showing a good correspondence and reliability. The proposed methodology demonstrated its reliability in decision making, in the technical support and its economical applicability also in similar difficult logistic situations. Article Highlights: A combination of in-situ geomechanical and geophysical measurements was adopted for a preliminary hydraulic conductivity estimation; Obtained field data were compared with independent laboratory estimations to assess the reliability of the proposed approach and compare representativeness and scale effects; Even given the difficult logistic conditions and the limitations of the available comparisons the proposed methodology demonstrated its reliability in decision making. [ABSTRACT FROM AUTHOR]

A procedure to recognize individual discontinuities in rock mass from measurement while drilling (MWD) technology is developed, using the binary pattern of structural rock characteristics obtained from in-hole images for calibration. Data from two underground operations with different drilling technology and different rock mass characteristics are considered, which generalizes the application of the methodology to different sites and ensures the full operational integration of MWD data analysis. Two approaches are followed for site-specific structural model building: a discontinuity index (DI) built from variations in MWD parameters, and a machine learning (ML) classifier as function of the drilling parameters and their variability. The prediction ability of the models is quantitatively assessed as the rate of recognition of discontinuities observed in borehole logs. Differences between the parameters involved in the models for each site, and differences in their weights, highlight the site-dependence of the resulting models. The ML approach offers better performance than the classical DI, with recognition rates in the range 89% to 96%. However, the simpler DI still yields fairly accurate results, with recognition rates 70% to 90%. These results validate the adaptive MWD-based methodology as an engineering solution to predict rock structural condition in underground mining operations.

This work describes a procedure for building a high-quality 3D model of a rocky pinnacle in the Dolomites, Italy, using Structure from Motion (SfM) techniques. The pinnacle, known as "Campanile di Val Montanaia", is challenging to survey due to its high elevation and sub-vertical cliffs. The construction of the 3D model is the first step in a multi-disciplinary approach to characterize the rock mass and understand its behavior and evolution. This paper discusses the surveying operations, which involved climbing the pinnacle to collect Ground Control Points (GCPs) and using a UAV to capture aerial imagery. The photographs were processed using SfM software to generate point clouds, mesh, and texture, which were then used for rock mass discontinuity mapping. The study compares models of different qualities and point densities to determine the optimal trade-off between processing time and accuracy in terms of discontinuity mapping. The results show that higher quality models allow for more detailed mapping of discontinuities, with some drawbacks due to noise in the case of the densest solution (e.g., increase in frequency of outliers across the point cloud). These pros and cons are also discussed in relation to the computational cost necessary to build the models. The study also examines the limitations and challenges of performing discontinuity mapping in the different models, including subjectivity in interpretation. A further element of interest is the publication of a high-quality 3D georeferenced model of the "Campanile di Val Montanaia" to be used for several potential further applications, such as stability analyses and numerical modeling. [ABSTRACT FROM AUTHOR]

Proximity remote sensing techniques, both land- and drone-based, allow for a significant improvement of the quality and quantity of raw data employed in the analysis of rockfall phenomena. In particular, the large amount of data these techniques can provide allows for the use of probabilistic approaches to rock mass characterization, with particular reference to block volume and shape definition. These, in return, are key parameters required for a proper rockfall hazard assessment and the optimization of countermeasures design. This study aims at providing a sort of guide, starting from the data gathering phase to the processing, up to the implementation of the outputs in a probabilistic-based scenario, which is able to associate a probability of not being exceeded with total kinetic energy values. By doing so, we were able to introduce a new approach for the choice of design parameters and the evaluation of the effectiveness of mitigation techniques. For this purpose, a suitable case study located in Varaita Valley (Cuneo, Italy) has been selected. The area has been surveyed, and a model of the slope and a digital model of the rock faces have been defined. The results show that a 6.5 m3 block has a probability of not being exceeded of 75%; subsequent simulations show that the level of kinetic energy involved in such a rockfall is extremely high. Some mitigation techniques are discussed. [ABSTRACT FROM AUTHOR]

Over the past two decades, advances in remote sensing methods and technology have enabled larger and more sophisticated datasets to be collected. Due to these advances, the need to effectively and efficiently communicate and visualize data is becoming increasingly important. We demonstrate that the use of mixed- (MR) and virtual reality (VR) systems has provided very promising results, allowing the visualization of complex datasets with unprecedented levels of detail and user experience. However, as of today, such visualization techniques have been largely used for communication purposes, and limited applications have been developed to allow for data processing and collection, particularly within the engineering–geology field. In this paper, we demonstrate the potential use of MR and VR not only for the visualization of multi-sensor remote sensing data but also for the collection and analysis of geological data. In this paper, we present a conceptual workflow showing the approach used for the processing of remote sensing datasets and the subsequent visualization using MR and VR headsets. We demonstrate the use of computer applications built in-house to visualize datasets and numerical modelling results, and to perform rock core logging (XRCoreShack) and rock mass characterization (EasyMineXR). While important limitations still exist in terms of hardware capabilities, portability, and accessibility, the expected technological advances and cost reduction will ensure this technology forms a standard mapping and data analysis tool for future engineers and geoscientists. [ABSTRACT FROM AUTHOR]

A fracture network consists of individual fractures within a defined volume. The degree of connectivity observed in a volumetric sample from a discrete fracture network (DFN) is dependent on fracture intensity and sample size. If small enough, most volumetric samples from any DFN will be unfractured and, if relatively large, samples from a DFN will contain multiple, connected fractures. The sample size where fractured samples transition to unfractured samples is observed in this work to propose a characteristic fractured volume (CFV). The CFV is the size of a random sample that contains at least one fracture and is most likely to contain the equivalent cumulative fracture surface area of no more than one fracture. It is an emergent property of a DFN model that demonstrates connectivity of a fracture network. For this research, a series of eight DFN models were parameterized to consider the sensitivity of fracture intensity, orientation dispersion, and fracture size distribution to the observed CFV. These models were assessed by sequential spatial discretization with progressively smaller sub-volumes. The fracture intensity of each sample was calculated and categorized as unfractured, fractured, or intersected, based on predefined volumetric intensity thresholds. The coefficient of variation (CV%) was determined for each discretization size to consider variability of fracture intensity within sample sets. Sensitivity of the CFV size was observed for fracture intensity and fracture size distribution and not for orientation dispersion. For each DFN, the CFV was equivalent to the sample size with a measured CV% of 1. The potential of a relationship between CV% and CFV will allow for estimation of CFV from limited data and has potential for applications in geotechnical design. The CFV serves as a useful tool for DFN model validation. [ABSTRACT FROM AUTHOR]

A discrete fracture network (DFN) model based on non-parametric kernel density estimators (KDE) and directional-linear statistics is developed. The model provides a characterization of the fracture network with distributions of fracture orientation and size jointly. A solution to the Bertrand paradox is used for the calculation of disk sizes from trace lengths, the latter calculated from the intersection of disks and highwall faces by triangulation. A Poisson point process is applied for the generation of the model, with fractures assumed to be flat and circular in shape, the number of fractures per unit volume (P30) adjusted to match the experimental length of fractures per unit area (P21). Length censoring of traces due to the surface dimension is considered in the calculations by including semi-bounded traces, i.e., traces censored in one of their ends. Orientation and size biases are corrected with a weighting function in the random sampling. The truncation effect whereby no traces shorter than some cut-off length are recorded, is addressed by a randomized optimization algorithm. The joint fracture orientation-size distribution model developed is tested with trace maps of discontinuities measured from photogrammetric models of twelve highwall faces of quarry benches, with outstanding results. Computational advantages over traditional parametric fracture models are addressed. Highlights: Nonparametric directional-linear statistics has been used for the construction of DFN models. The mathematical analysis of this new approach is described in detail. A new link between distributions of disc size and pseudo-trace lengths is established. Relationships between means and variances for the distributions of trace length and disc size are discussed. Censoring bias is corrected by a mixed random variable and truncation bias is corrected by including semibounded traces and using a probabilistic filter. The nonparametric DFN model developed is applied to photogrammetric discontinuity data maps. Consistency of the results is assessed and thoroughly discussed. [ABSTRACT FROM AUTHOR]

Technological advancements have made rock engineering more data-driven, leading to increased use of machine learning (ML). While the use of ML in rock engineering has the potential to transform the industry, several methodological issues should first be addressed: (i) rock engineering’s use of biased (poor quality) data, resulting in biased ML models and (ii) limited rock mass classification and characterization data. If these issues are not addressed, rock engineering risks using unreliable ML models that can have potential real-life adverse impacts. This paper aims to provide an overview of these methodological issues and demonstrate their impact on the reliability of ML models using surrogate models. To take full advantage of the benefits of ML, rock engineers should make sure that their ML models are reliable by ensuring that there are sufficient unbiased data to develop reliable ML models. In the context of this paper, the term sufficient retains a relative meaning since the amount of data that is sufficient to develop reliable a ML models depends on the problem under consideration and the application of the ML model (e.g., pre-feasibility, feasibility, design stage).

Stope design is an important part of mine planning, and it aims to balance ore recovery, ore dilution, and production costs without compromising the safety aspects. This paper summarizes the main results from the research, which aims to introduce new techniques to describe the ore body and surrounding rock mass at the tunnel face prior to stope excavation. The research comprises a literature review and a survey among mining professionals to assess current stope design practices. The study identifies geotechnical data, software improvements, and integration of design into mine planning as the most critical areas for improvement. The empirical part of the study proposes new techniques for fast data acquisition. The laser-induced breakdown spectrometry (LIBS) technique is developed for measurements at the tunnel face and from core boxes to provide mineralogical and geometallurgical data. Ground-penetrating radar (GPR) studies are conducted to improve discontinuity characterization, and rapid photogrammetric methods are proposed for efficient tunnel geometry characterization. The techniques discussed in this paper already have many industrial applications. This study reveals their potential to be adopted and further developed to serve ore and rock mass characterization for stope design.

Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry is a viable method to digitize underground spaces for inspection, documentation, or remote mapping. However, the conventional image acquisition process can be laborious and time-consuming. Previous studies confirmed that the acquisition time can be reduced when using a 360-degree camera to capture the images. This paper demonstrates a method for rapid photogrammetric reconstruction of tunnels using a 360-degree camera. The method is demonstrated in a field test executed in a tunnel section of the Underground Research Laboratory of Aalto University in Espoo, Finland. A 10 m-long tunnel section with exposed rock was photographed using the 360-degree camera from 27 locations and a 3D model was reconstructed using SfM-MVS photogrammetry. The resulting model was then compared with a reference laser scan and a more conventional digital single-lens reflex (DSLR) camera-based model. Image acquisition with a 360-degree camera was 3× faster than with a conventional DSLR camera and the workflow was easier and less prone to errors. The 360-degree camera-based model achieved a 0.0046 m distance accuracy error compared to the reference laser scan. In addition, the orientation of discontinuities was measured remotely from the 3D model and the digitally obtained values matched the manual compass measurements of the sub-vertical fracture sets, with an average error of 2–5°. [ABSTRACT FROM AUTHOR]

This work describes a procedure for building a high-quality 3D model of a rocky pinnacle in the Dolomites, Italy, using Structure from Motion (SfM) techniques. The pinnacle, known as “Campanile di Val Montanaia”, is challenging to survey due to its high elevation and sub-vertical cliffs. The construction of the 3D model is the first step in a multi-disciplinary approach to characterize the rock mass and understand its behavior and evolution. This paper discusses the surveying operations, which involved climbing the pinnacle to collect Ground Control Points (GCPs) and using a UAV to capture aerial imagery. The photographs were processed using SfM software to generate point clouds, mesh, and texture, which were then used for rock mass discontinuity mapping. The study compares models of different qualities and point densities to determine the optimal trade-off between processing time and accuracy in terms of discontinuity mapping. The results show that higher quality models allow for more detailed mapping of discontinuities, with some drawbacks due to noise in the case of the densest solution (e.g., increase in frequency of outliers across the point cloud). These pros and cons are also discussed in relation to the computational cost necessary to build the models. The study also examines the limitations and challenges of performing discontinuity mapping in the different models, including subjectivity in interpretation. A further element of interest is the publication of a high-quality 3D georeferenced model of the “Campanile di Val Montanaia” to be used for several potential further applications, such as stability analyses and numerical modeling.

Proximity remote sensing techniques, both land- and drone-based, allow for a significant improvement of the quality and quantity of raw data employed in the analysis of rockfall phenomena. In particular, the large amount of data these techniques can provide allows for the use of probabilistic approaches to rock mass characterization, with particular reference to block volume and shape definition. These, in return, are key parameters required for a proper rockfall hazard assessment and the optimization of countermeasures design. This study aims at providing a sort of guide, starting from the data gathering phase to the processing, up to the implementation of the outputs in a probabilistic-based scenario, which is able to associate a probability of not being exceeded with total kinetic energy values. By doing so, we were able to introduce a new approach for the choice of design parameters and the evaluation of the effectiveness of mitigation techniques. For this purpose, a suitable case study located in Varaita Valley (Cuneo, Italy) has been selected. The area has been surveyed, and a model of the slope and a digital model of the rock faces have been defined. The results show that a 6.5 m3 block has a probability of not being exceeded of 75%; subsequent simulations show that the level of kinetic energy involved in such a rockfall is extremely high. Some mitigation techniques are discussed.

Geotechnical issues due to inappropriate support designs of underground drift will affect mining developments and production. The aim of this study was to provide a systematic support design method for deep hard-rock drifts in China. Field investigations and laboratory studies were carried out on the engineering geological properties of the rock masses along drifts in the Sanshandao Gold Mine. Potential wedge analysis and safety factors were determined using Unwedge software. The rock mass properties and support requirements were analyzed accordingly using different rock mass classification systems; then, an updated combined support system including rock bolts, wire mesh, and shotcrete was proposed. Numerical methods were used to quantify the plastic zone and principal stress of the drift, the plastic zone was reduced, and the rock stress state was improved after installing the support systems. Field monitoring data also confirmed that the updated support system prevented excessive rock mass deformation in drift. This study provides a reliable method for deep hard-rock drift support at Sanshandao Gold Mine and will also be helpful for the optimization of subsequent support. [ABSTRACT FROM AUTHOR]

Abstract To conduct a successful geomechanical characterization of rock masses, an appropriate interpretation of lithological heterogeneity should be attained by considering both the geological and geomechanical data. In order to clarify the reliability and applicability of geological surveys for rock mechanics purposes, a geomechanical characterization study is conducted on the heterogeneous rock mass of Niobec Mine (Quebec, Canada), by considering the characteristics of its various identified lithological units. The results of previous field and laboratory test campaigns were used to quantify the variability associated to intact rock geomechanical parameters for the different present lithological units. The interpretation of geomechanical similarities between the lithological units resulted in determination of three main rock units (carbonatite, syenite, and carbonatite-syenite units). Geomechanical parameters of these rock units and their associated variabilities are utilized for stochastic estimation of geomechanical parameters of the heterogeneous rock mass using the Monte Carlo Simulation method. A comparison is also made between the results of probabilistic and deterministic analyses to highlight the presence of intrinsic variability associated with the heterogeneous rock mass properties. The results indicated that, for the case of Niobec Mine, the carbonatite-syenite rock unit could be considered as a valid representative of the entire rock mass geology since it offers an appropriate geomechanical approximation of all the present lithological units at the mine site, in terms of both the magnitude and dispersion of the strength and deformability parameters. Article Highlights Evaluating the reliability and applicability of geological survey outcomes for rock mechanics purposes. A geomechanical characterization study is conducted on the heterogeneous rock mass by considering the various identified rock lithotypes. The geomechanical parameters of intact units and their associated variabilities are used to stochastically estimate the geomechanical parameters of the heterogeneous rock mass by employing the Monte Carlo Simulation. A comparison is also made between the results of probabilistic and deterministic geomechanical analyses. The results indicate that, in the case of Niobec Mine, the combined syenite-carbonatite rock unit could be considered as a valid representative of the entire rock mass.

Over the past two decades, advances in remote sensing methods and technology have enabled larger and more sophisticated datasets to be collected. Due to these advances, the need to effectively and efficiently communicate and visualize data is becoming increasingly important. We demonstrate that the use of mixed- (MR) and virtual reality (VR) systems has provided very promising results, allowing the visualization of complex datasets with unprecedented levels of detail and user experience. However, as of today, such visualization techniques have been largely used for communication purposes, and limited applications have been developed to allow for data processing and collection, particularly within the engineering–geology field. In this paper, we demonstrate the potential use of MR and VR not only for the visualization of multi-sensor remote sensing data but also for the collection and analysis of geological data. In this paper, we present a conceptual workflow showing the approach used for the processing of remote sensing datasets and the subsequent visualization using MR and VR headsets. We demonstrate the use of computer applications built in-house to visualize datasets and numerical modelling results, and to perform rock core logging (XRCoreShack) and rock mass characterization (EasyMineXR). While important limitations still exist in terms of hardware capabilities, portability, and accessibility, the expected technological advances and cost reduction will ensure this technology forms a standard mapping and data analysis tool for future engineers and geoscientists.

Rock discontinuities significantly impact the mechanical and hydraulic behavior of rock masses. A crucial aspect of rock engineering involves classifying discontinuities with similar orientations into groups. For this purpose, clustering algorithms, such as K-Means and Fuzzy K-Means (FKM), have been employed. However, the outcomes of these algorithms are influenced by the selection of initial cluster centers. This paper proposes an improved FKM algorithm to automatically identify rock discontinuity sets based on the Fisher distribution (FFKM). The algorithm uses the Fisher distribution to generate and select appropriate initial cluster centers. The performance of FFKM was initially validated using a published data set, and its results were compared with other clustering methods commonly used for grouping discontinuities. Results demonstrated the superior performance of FFKM over the FKM algorithm, comparable to other methods. Subsequently, the proposed algorithm was employed to analyze a fracture data set sampled at an open-pit iron mine. The FFKM facilitated identifying the correct number of sets and produced results consistent with the fracture sets observed in the field. Finally, the algorithm was verified using an artificial discontinuity data set, and the results demonstrated that the method correctly identified the number of sets and provided discontinuity sets similar to the original data set. The FFKM algorithm offers significant advantages: it maintains the essential characteristics of the FKM algorithm, effectively addresses the challenge of selecting suitable initial cluster centers, requires only the expected number of discontinuity sets as an input parameter, processes data within an acceptable computation time, serves as a tool for defining the number of discontinuity sets, and mitigates the drawbacks of the stereographic projection method. • Mitigation of challenges associated with identifying discontinuity sets. • Accurate definition of the number of discontinuity sets. • The algorithm preserves the Fuzzy K-Means features. • Assistant tool in rock engineering and mining applications. • Determination of fracture sets in an open-pit iron mine. [ABSTRACT FROM AUTHOR]

This study wants to give a contribution to the semi-automatic evaluation of rock mass discontinuities, orientation and spacing, as important parameters used in Engineering. In complex and inaccessible study areas, a traditional geological survey is hard to conduct, therefore, remote sensing techniques have proven to be a very useful tool for discontinuity analysis. However, critical expert judgment is necessary to make reliable analyses. For this reason, the open-source Python tool named DCS (Discontinuities Classification and Spacing) was developed to manage point cloud data. The tool is written in Python and is based on semi-supervised clustering. By this approach the users can: (a) estimate the number of discontinuity sets (here referred to as "clusters") using the Error Sum of Squares (SSE) method and the K-means algorithm; (b) evaluate step by step the quality of the classification visualizing the stereonet and the scatterplot of dip vs. dip direction from the clustering; (c) supervise the clustering procedure through a manual initialization of centroids; (d) calculate the normal spacing. In contrast to other algorithms available in the literature, the DCS method does not require complex parameters as inputs for the classification and permits the users to supervise the procedure at each step. The DCS approach was tested on the steep coastal cliff of Ancona town (Italy), called the Cardeto–Passetto cliff, which is characterized by a complex fracturing and is largely affected by rockfall phenomena. The results of discontinuity orientation were validated with the field survey and compared with the ones of the FACETS plug-in of CloudCompare. In addition, the algorithm was tested and validated on regular surfaces of an anthropic wall located at the bottom of the cliff. Eventually, a kinematic analysis of rock slope stability was performed, discussing the advantages and limitations of the methods considered and making fundamental considerations on their use. [ABSTRACT FROM AUTHOR]

Rock mass characterization is the cornerstone of informed engineering analysis and design. Consequently, it is imperative to have access to quality data and understand the implications of mischaracterization and uncertainty of collected geotechnical data. This paper presents the results of an investigation on the influence of alteration on the mechanical properties of a rock mass. Field data from an underground hard rock mine illustrated that variations in type, fabric and intensity of alteration had a significant influence the rock mass strength as reported by point load testing. An analysis of alteration data systematically collected from core logging provided valuable insights on the impact of alteration on the strength anisotropy of the rock mass. The spatial distribution of foliation planes and the type, fabric and intensity of alteration varies significantly in the mine. The impact of alteration on rock mass strength contributed to areas of high convergence and high seismicity during mining. [ABSTRACT FROM AUTHOR]

The InfraRed Thermography (IRT) technique is gaining increasing popularity in the geosciences. Although several studies on the use of this technique for rock mass characterization were reported in the literature, its applicability is challenging in complex environments, characterized by poor accessibility, lithological heterogeneity, karst features and disturbances, such as vegetation and human activities. This paper reports the results of specific tests carried out to explore the application of IRT methods, supported by UAV surveys, for rock mass characterization in complex conditions. In detail, a 24-h monitoring was performed on an appropriate case study to assess which type of information can be collected and what issues can be expected. The results of the thermograms were compared with data reported in the literature and discussed. A novel method to detect correlations between the temperature profiles at the air-rock interfaces and the rock mass properties is presented. The main advantages, limitations and suggestions in order to take full advantage of the IRT technique in complex conditions are reported in the final section. [ABSTRACT FROM AUTHOR]

Amberg Engineering was involved in numerous subsurface in frastructure projects in Sweden, predominantly in the Stockholm metropolitan area. Our rock mechanical and engineering expertise represented and represents our key contribution to the projects, while we came in touch with valuable, and sometimes very different tunnelling approaches. While certain technical solutions still appear exotic, majority of them have to be valued as correct and consequent answers to the predominant geological conditions in Scandinavia. The present publication will show our experience based on one case study. Special attention is given to rock mass characterisation, design processes and tunnelling philosophy. The issues of support, water ingress control and vibration control are treated in detail, and a comparison with our local practice is presented. The paper attempts to deliver an objective treatise and honest presentation of our experience, and a summary of "lessons learned". [ABSTRACT FROM AUTHOR]

Geotechnical issues due to inappropriate support designs of underground drift will affect mining developments and production. The aim of this study was to provide a systematic support design method for deep hard-rock drifts in China. Field investigations and laboratory studies were carried out on the engineering geological properties of the rock masses along drifts in the Sanshandao Gold Mine. Potential wedge analysis and safety factors were determined using Unwedge software. The rock mass properties and support requirements were analyzed accordingly using different rock mass classification systems; then, an updated combined support system including rock bolts, wire mesh, and shotcrete was proposed. Numerical methods were used to quantify the plastic zone and principal stress of the drift, the plastic zone was reduced, and the rock stress state was improved after installing the support systems. Field monitoring data also confirmed that the updated support system prevented excessive rock mass deformation in drift. This study provides a reliable method for deep hard-rock drift support at Sanshandao Gold Mine and will also be helpful for the optimization of subsequent support.

Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry is a viable method to digitize underground spaces for inspection, documentation, or remote mapping. However, the conventional image acquisition process can be laborious and time-consuming. Previous studies confirmed that the acquisition time can be reduced when using a 360-degree camera to capture the images. This paper demonstrates a method for rapid photogrammetric reconstruction of tunnels using a 360-degree camera. The method is demonstrated in a field test executed in a tunnel section of the Underground Research Laboratory of Aalto University in Espoo, Finland. A 10 m-long tunnel section with exposed rock was photographed using the 360-degree camera from 27 locations and a 3D model was reconstructed using SfM-MVS photogrammetry. The resulting model was then compared with a reference laser scan and a more conventional digital single-lens reflex (DSLR) camera-based model. Image acquisition with a 360-degree camera was 3× faster than with a conventional DSLR camera and the workflow was easier and less prone to errors. The 360-degree camera-based model achieved a 0.0046 m distance accuracy error compared to the reference laser scan. In addition, the orientation of discontinuities was measured remotely from the 3D model and the digitally obtained values matched the manual compass measurements of the sub-vertical fracture sets, with an average error of 2–5°.

In this paper, the slope rock mass is numerically characterized by considering hydraulic and mechanical properties using two distinct element models. The flow rate and permeability are calculated from localized fluxes through rock masses with varied fracture orientations and scales. Flow models suggest that rock mass permeability is predominantly controlled by fracture size. High rock mass permeability is simulated when the fractures are enlarged. Hydraulic anisotropy is captured when the difference in the fracture size is amplified. The mechanical properties of the slope rock mass are characterized through numerical shearing tests. In general, high permeability corresponds to low shearing resistance of the rock mass. The fractures obliquely distributed to shearing direction lead to additional shearing resistance. Enlarged fractures reflect high conductivity of the rock mass structure and decrease the shearing resistance. Mechanical anisotropy of the rock mass is also captured and attributed to the difference in the fracture size. The relations between hydraulic and mechanical properties are examined, and negative exponential relations are fitted between rock mass cohesion and permeability. The research introduces permeability as reference to slope rock mass characterization and provides reliable methods to this challenging issue. [ABSTRACT FROM AUTHOR]

Rock mass classification systems are used to categorize and estimate the role of the most significant parameters influencing rock mass behavior to represent an equivalent continuum. Generally, in these methods, the impact of the related parameters is considered uniform in all directions. Hence, these systems describe the rock mass as an isotropic medium. In some cases, in particular, for layered strata and systematically fractured rocks, the assumption of isotropic behavior may not provide realistic results. Hence, in this paper, to characterize the rock mass anisotropy, a directional rock mass rating (DRMR) has been proposed based on the well-known rock mass rating (RMR). So, DRMR provides a three-dimensional rock mass rating, quantitatively. By means of statistical distribution of DRMR, a classification for the degree of anisotropy of rock mass has been proposed. Furthermore, a criterion to identify the prominent rock mass, isotropic/transversely isotropic/anisotropic situation, is presented. Then the stereonet has been used to demonstrate an all-round graphical representation of DRMR. This with DRMR provides an illustrative insight into the actual rock mass condition and can assist to select the appropriate method for further analysis. Also, the method can be used as a basis to develop practical solutions for many rock engineering issues, such as characterizing the mechanical parameters of rock mass as an anisotropic equivalent continuum, selective directional rock mass improvement, and proper selection of rock tunnel and rock cavern alignments. Finally, the results of some practical applications of the method, based on field data, are presented. [ABSTRACT FROM AUTHOR]

The in situ block size distribution is an essential characteristic of fractured rock masses and impacts the assessment of rockfall hazards and other fields of rock mechanics. The block size distribution can be estimated rather easily for fully persistent fractures, but it is a challenge to determine this parameter when non-persistent fractures in a rock mass should be considered. In many approaches, the block size distribution is estimated by assuming that the fractures are fully persistent, resulting in an underestimation of the block sizes for many fracture geometries. In addition, the block size distribution is influenced by intact rock bridge failure, especially in rock masses with non-persistent fractures, either in a short-term perspective during a slope failure event when the rock mass increasingly disintegrates or in a long-term view when the rock mass progressively weakens. The quantification of intact rock bridge failure in a rock mass is highly complex, comprising fracture coalescence and crack growth driven by time-dependent changes of the in situ stresses due to thermal, freezing-thawing, and pore water pressure fluctuations. This contribution presents stochastic analyses of the two-dimensional in situ block area distribution and the mean block area of non-persistent fracture networks. The applied 2D discrete fracture network approach takes into account the potential failure of intact rock bridges based on a pre-defined threshold length and relies on input parameters that can be easily measured in the field by classical discontinuity mapping methods (e.g., scanline mapping). In addition, on the basis of these discrete fracture network analyses, an empirical relationship was determined between (i) the mean block area for persistent fractures, (ii) the mean block area for non-persistent fractures, and (iii) the mean interconnectivity factor. The further adaptation of this 2D approach to 3D block geometries is discussed on the basis of general considerations. The calculations carried out in this contribution highlight the large impact of non-persistent fractures and intact rock bridge failure for rock mass characterization, e.g., rockfall assessment. [ABSTRACT FROM AUTHOR]

This study wants to give a contribution to the semi-automatic evaluation of rock mass discontinuities, orientation and spacing, as important parameters used in Engineering. In complex and inaccessible study areas, a traditional geological survey is hard to conduct, therefore, remote sensing techniques have proven to be a very useful tool for discontinuity analysis. However, critical expert judgment is necessary to make reliable analyses. For this reason, the open-source Python tool named DCS (Discontinuities Classification and Spacing) was developed to manage point cloud data. The tool is written in Python and is based on semi-supervised clustering. By this approach the users can: (a) estimate the number of discontinuity sets (here referred to as “clusters”) using the Error Sum of Squares (SSE) method and the K-means algorithm; (b) evaluate step by step the quality of the classification visualizing the stereonet and the scatterplot of dip vs. dip direction from the clustering; (c) supervise the clustering procedure through a manual initialization of centroids; (d) calculate the normal spacing. In contrast to other algorithms available in the literature, the DCS method does not require complex parameters as inputs for the classification and permits the users to supervise the procedure at each step. The DCS approach was tested on the steep coastal cliff of Ancona town (Italy), called the Cardeto–Passetto cliff, which is characterized by a complex fracturing and is largely affected by rockfall phenomena. The results of discontinuity orientation were validated with the field survey and compared with the ones of the FACETS plug-in of CloudCompare. In addition, the algorithm was tested and validated on regular surfaces of an anthropic wall located at the bottom of the cliff. Eventually, a kinematic analysis of rock slope stability was performed, discussing the advantages and limitations of the methods considered and making fundamental considerations on their use.

In tunnelling, rock mass support is designed based on the observed rock mass conditions. These conditions are determined by rock mass characterization. Measurement while drilling (MWD), one such characterization method, acquires drill parameter data during drilling. These data can be used to predict rock mass conditions ahead of the face. In this study, grout-hole MWD data are collected at one of the main tunnels in the large infrastructural project Stockholm bypass tunnels. The normalized and filtered MWD data are correlated to the rock mass characteristics using multilinear regression and the Levenberg-Marquardt method. Although a strong numerical correlation cannot be obtained, the results are promising. As a result, a holistic visual approach, which linked the MWD parameters with the rock mass classification and rock support requirements, was developed. [ABSTRACT FROM AUTHOR]

The InfraRed Thermography (IRT) technique is gaining increasing popularity in the geosciences. Although several studies on the use of this technique for rock mass characterization were reported in the literature, its applicability is challenging in complex environments, characterized by poor accessibility, lithological heterogeneity, karst features and disturbances, such as vegetation and human activities. This paper reports the results of specific tests carried out to explore the application of IRT methods, supported by UAV surveys, for rock mass characterization in complex conditions. In detail, a 24-h monitoring was performed on an appropriate case study to assess which type of information can be collected and what issues can be expected. The results of the thermograms were compared with data reported in the literature and discussed. A novel method to detect correlations between the temperature profiles at the air-rock interfaces and the rock mass properties is presented. The main advantages, limitations and suggestions in order to take full advantage of the IRT technique in complex conditions are reported in the final section.

The trend today to ever increasing modelling sophistication demands that much more attention be paid by practitioners to achieving better appreciation and characterization of geology and rockmass variability, so that rock–structure interaction effects can be analysed more realistically in better calibrated models. This paper is thus directed towards focussing attention on risk-based geological characterization as basis for helping modellers and designers improve calibration of their models. A sequential approach of appropriate input parameter refinement is outlined as a path forward methodology for consistently achieving maximum reliability in modelling. Processes that are needed for identifying key controlling geological structural features and rockmass domain characteristics that may be critical influences on true rockmass behaviour are explored so that rationalization steps can be followed in model building to ensure that actual behaviour drivers are not only properly represented, but are reliably characterized through rigorous calibration. Suggestions for the use of the observational and quantitative GSI charts at various scales appropriate to specific geological domains are presented as a means for achieving such calibration. Illustration is then given of how quantification can be achieved of rock quality variability throughout the complete range of rock competence, from intact pseudo-homogeneous high strength rockmasses subject to brittle spalling, through blocky, folded or foliated rockmasses, where kinematic controls are typically of paramount importance, through to completely degraded, fault process core zones and saprolites, where material matrix strength almost entirely dominates behaviour. Guidelines are given for suggested ranges of classification applicability for use with the Hoek–Brown failure criterion. [ABSTRACT FROM AUTHOR]

Rockfalls are one of the most dominant geological hazards in mountainous rocky regions with the potential to turn catastrophic if they occur in an anthropogenic environment. Therefore, the identification of potential rockfall locations is of high importance. Susceptibility is the magnitude that describes these locations and its qualitative and quantitative assessment is necessary for the timely treatment of potential events. Quantitative susceptibility assessment can be conducted using either data-driven methods such as bivariate and multivariate statistics as well as artificial neural networks or numerical methods such as static and dynamic models. In both approaches mathematical assumptions have to be made concerning the predisposing factors distribution and so there is an inherent need to achieve the higher possible confidence level in the input data. Such high-resolution data can be acquired using light detection and ranging (LiDAR) scanners. In the current study, LiDAR technology was implemented, and the data processing technique is analyzed step by step providing the reader with a view of the whole procedure. The results produced by the current methodology are validated and interpreted according to in situ measurements and observations based on unmanned aerial vehicle imagery. Post data processing, joint orientation, joint spacing and potential block volumes were extracted considering both persistent and non-persistent joints. The proposed methodology provides the creation of detailed high-resolution spatial distribution maps of the previously mentioned parameters, considering the variability of their values along the slope. The results can be used in a space-resolved susceptibility assessment providing higher-resolution input data for the subsequent susceptibility analysis. [ABSTRACT FROM AUTHOR]

Rock mass characterization is important to identify the condition of rock especially in major infrastructure like a tunnel. Rock mass characterization can be done either before, during or after construction completed. In this case study, this characterization was done after almost 20 years of tunnel operation. Characterization could not be done directly to the field as half of the rock mass along tunnel was covered by shotcrete layer. To overcome this problem, three integration methods which are field mapping, satellite image interpretation and geoelectrical tomography resistivity survey been approached. Satellite image interpretation is to emphasise negative lineament structure tracing while field mapping is to emphasis the location of groundwater intrusion and major tectonic structures like fault, joint and shear zone. Geoelectrical tomography resistivity survey was conducted using ABEM SAS 400 system and dipole-dipole array while raw data were processed using Res2DINV software. Data analysis showed three difference resistivity values which are high resistivity (> 1500 O.m), moderate (100-500 O.m) and low (<25 O.m). Findings from field mapping and lineament interpretation were used to interpret pseudosection. All three resistivity values were interpreted as high water content zone (low resistivity), lineament effected and highly fractured granitic rock mass (moderate resistivity) and low fractured granitic rock (high resistivity). [ABSTRACT FROM AUTHOR]

Rock slope failures in urban areas may represent a serious hazard for human life, as well as private and public property, even on the occasion of sporadic episodes. Prevention and mitigation measures indispensably require a proper rock mass characterization, which is often achieved by means of time-consuming, costly and dangerous field surveys. In the last decades, remote sensing devices such as high-resolution digital cameras, laser scanners and drones have been widely used as supplementary techniques for rock slope analysis and monitoring, especially in poorly accessible areas, or in sites of large extension. Although several methods for rock mass characterization by means of remote sensing techniques have been reported in specific studies, there are very few contributions that focused on comparing the different methods in an attempt to establish their advantages and limitations. With this study, we performed digital photogrammetry, Terrestrial Laser Scanning and Unmanned Aerial Vehicle surveys on a cliff located in a popular tourist attraction site, characterized by complex geological and geomorphological settings, as well as by disturbance elements such as vegetation and human activities. For each point cloud, we applied geostructural analysis by means of semi-automatic methods, and then compared multi-temporal acquisitions for cliff monitoring. By quantitative comparison of the results and validation by means of conventional geostructural field surveys, the pros and cons of each method were outlined in attempt to depict the conditions and goals the different techniques seem to be more suitable for.

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.