A review of laser scanning for geological and geotechnical applications in underground mining

Laser scanning can provide timely assessments of mine sites despite adverse challenges in the operational environment. Although there are several published articles on laser scanning, there is a need to review them in the context of underground mining applications. To this end, a holistic review of laser scanning is presented including progress in 3D scanning systems, data capture/processing techniques and primary applications in underground mines. Laser scanning technology has advanced significantly in terms of mobility and mapping, but there are constraints in coherent and consistent data collection at certain mines due to feature deficiency, dynamics, and environmental influences such as dust and water. Studies suggest that laser scanning has matured over the years for change detection, clearance measurements and structure mapping applications. However, there is scope for improvements in lithology identification, surface parameter measurements, logistic tracking and autonomous navigation. Laser scanning has the potential to provide real-time solutions but the lack of infrastructure in underground mines for data transfer, geodetic networking and processing capacity remain limiting factors. Nevertheless, laser scanners are becoming an integral part of mine automation thanks to their affordability, accuracy and mobility, which should support their widespread usage in years to come

Fracture mapping in challenging environment: a 3D virtual reality approach combining terrestrial LiDAR and high definition images

ArticleThis is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record.The latest technological developments in computer vision allow the creation of georeferenced, non-immersive desktop virtual reality (VR) environments. VR uses a computer to produce a simulated three-dimensional world in which it is possible to interact with objects and derive metric and thematic data. In this context, modern geomatic tools enable the remote acquisition of information that can be used to produce georeferenced high-definition 3D models: these can be used to create a VR in support of rock mass data processing, analysis, and interpretation. Data from laser scanning and high quality images were combined to map deterministically and characterise discontinuities with the aim of creating accurate rock mass models. Discontinuities were compared with data from traditional engineering-geological surveys in order to check the level of accuracy in terms of the attitude of individual joints and sets. The quality of data collected through geomatic surveys and field measurements in two marble quarries of the Apuan Alps (Italy) was very satisfactory. Some fundamental geotechnical indices (e.g. joint roughness, alteration, opening, moisture, and infill) were also included in the VR models. Data were grouped, analysed, and shared in a single repository for VR visualization and stability analysis in order to study the interaction between geology and human activities.The authors gratefully acknowledge the assistance of the personal of the Romana Quarry and particularly Corniani M. This paper was possible because of support from the Tuscany Region Research Project known as “Health and safety in the quarries of ornamental stones—SECURECAVE”. The authors acknowledge Pellegri M and Gullì D (Local Sanitary Agency n.1, Mining Engineering Operative Unit—Department of Prevention) and Riccucci S (Centre of GeoTechnologies, University of Siena) for their support of this research

Potential applications of deep learning in automatic rock joint trace mapping in a rock mass

In blasted rock slopes and underground openings, rock joints are visible in different forms. Rock joints are often exposed as planes confining rock blocks and visible as traces on a well-blasted, smooth rock mass surface. A realistic rock joint model should include both visual forms of joints in a rock mass: i.e., both joint traces and joint planes. Imaged-based 2D semantic segmentation using deep learning via the Convolutional Neural Network (CNN) has shown promising results in extracting joint traces in a rock mass. In 3D analysis, research studies using deep learning have demonstrated outperforming results in automatically extracting joint planes from an unstructured 3D point cloud compared to state-of-the-art methods. We discuss a pilot study using 3D true colour point cloud and their source and derived 2D images in this paper. In the study, we aim to implement and compare various CNN-based networks found in the literature for automatic extraction of joint traces from laser scanning and photogrammetry data. Extracted joint traces can then be clustered and connected to potential joint planes as joint objects in a discrete joint model. This can contribute to a more accurate estimation of rock joint persistence. The goal of the study is to compare the efficiency and accuracy between using 2D images and 3D point cloud as input data. Data are collected from two infrastructure projects with blasted rock slopes and tunnels in Norway.Potential applications of deep learning in automatic rock joint trace mapping in a rock masspublishedVersio

Increasing geotechnical data confidence through the Integration of laser scanner face mapping data into the Sishen iron ore mine geotechnical database

A research report submitted in partial fulfilment of the requirements for the degree of Master of Science in Engineering to the Faculty of Engineering and the Built Environment, School of Mining Engineering at the University of the Witwatersrand, Johannesburg, 2018Face mapping is a simple but invaluable means of geological and geotechnical data acquisition whereby intact rock properties, rock mass properties, discontinuity properties and structural orientation can be assessed. Although traditionally done via direct contact with the mapping face through techniques such as line mapping or window mapping, remote face mapping using various digital techniques has become increasingly popular in recent years. Sishen Mine is a large open pit mining operation requiring a comprehensive geotechnical data set to evaluate pit wall design and stability with the necessary level of confidence. Geotechnical borehole data, face mapping data, geotechnical lab testing data and implicit structural models provide the main sources of this information. Although a large geotechnical borehole database has always been maintained at the mine, face mapping has in the past been restricted to sporadic and isolated stability assessments. In 2013 the mine acquired a Maptek 8810 terrestrial laser scanner with the resolution, photographic capabilities and software required to carry out geotechnical face mapping. The aims of this research project were to evaluate the capabilities of the Maptek scanner and system, set up a standard face mapping procedure, integrate face mapping data in the mine’s geotechnical database and compare face mapping acquired rock mass data with the mine’s existing borehole data set. Further potential uses for the laser scanner system and face mapping data were also explored throughout the course of the dissertation. A face mapping procedure was set up and faces were mapped from 86 individual scans, acquired between October 2015 and April 2017. The mapping data obtained from the scans was integrated into the Acquire Geological Data Management System, a purpose designed Structured Query Language (SQL) database system used for storing the mine’s geotechnical data. Open Database Connectivity (ODBC) database links with the Micromine Computer Aided Design (CAD) package allowed for spatial overlays of mapping data with other geotechnical data as well as survey and mine planning data. In terms of data analysis mapping parameters such as joint spacing, Rock Quality Designation and Rock Mass Rating could be directly compared with borehole logging values for the same rock types. The comparison indicated that in general borehole measurements tend to slightly under estimate joint spacing and rock mass rating values while face mapping assessments tend to slightly over estimate these values. This is due to various intricacies of the two data capture techniques that tend to skew the data in one way or the other. Face mapping data was compared with Sishen’s existing structural model, which is based mainly on interpretation and implicit data. Structural orientations and features correlate well between the implicit model and actual mapped values gathered during the data collection phase of this project. Within the geotechnical design process, having actual mapping data in combination with increased confidence in the structural model allows for better definition of geotechnical design sectors. Overall the face mapping and geotechnical analysis features of the Maptek 8810 terrestrial laser scanner make it an invaluable geotechnical data capture tool, providing a system is in place to store mapping data in a manner that allows for meaningful rock mass and structural information to be produced.XL201

Detection and geometric characterization of rock mass discontinuities using a 3D high-resolution digital outcrop model generated from RPAS imagery – Ormea rock slope, Italy

Abstract The use of a remotely piloted aircraft system (RPAS) and digital photogrammetry is valuable for the detection of discontinuities in areas where field mapping and terrestrial photogrammetry or laser scanner surveys cannot be employed because the slope is unsafe, inaccessible, or characterized by a complex geometry with areas not visible from the ground. Using the Structure-from-Motion method, the acquired images can be used to create a 3D texturized digital outcrop model (TDOM) and a detailed point cloud representing the rock outcrop. Discontinuity orientations in a complex rock outcrop in Italy were mapped in the field using a geological compass and by manual and automated techniques using a TDOM and point cloud generated from RPAS imagery. There was a good agreement between the field measurements and manual mapping in the TDOM. Semi-automated discontinuity mapping using the point cloud was performed using the DSE, qFacet FM, and qFacet KD-tree methods applied to the same 3D model. Significant discrepancies were found between the semi-automatic and manual methods. In particular, the automatic methods did not adequately detect discontinuities that are perpendicular to the slope face (bedding planes in the case study). These differences in detection of discontinuities can adversely influence the kinematic analysis of potential rock slope failure mechanisms. We use the case study to demonstrate a workflow that can accurately map discontinuities with results comparable to field measurements. The combined use of TDOM and RPAS dramatically increases the discontinuity data because RPAS can supply a good coverage of inaccessible or hidden portions of the slope and TDOM is a powerful representation of the reality that can be used to map discontinuity orientations including those that are oriented perpendicular to the slope

Geostructural and Geomechanical Study of the Piastrone Quarry (Seravezza, Italy) Supported by Photogrammetry to Assess Failure Mode

The use of non-contact-techniques for rock mass characterization has been growing significantly over the last decade. However, their application to stability assessment of ornamental stone has not yet received much attention from researchers. This study utilizes rock mass data both in terms of slope orientations and degree of fracturing obtained from a point cloud, a set of three-dimensional (3D) points representing a rock mass surface, to (1) investigate the influence of geostructures at different scales and (2) assess quarry stability by determining areas susceptible to different failure types. Multi-resolution point clouds are obtained through several photogrammetric survey techniques to identify important structural elements of the site. By integrating orientation data of discontinuity planes, obtained with a traditional survey, and of traces, outlined on point clouds, several joint sets were identified. Kinematic tests revealed various potential failure modes of the rock slope. Moreover, an analysis of the influence of the discontinuity strength determined by the presence of rock bridges was carried out. The study revealed that the strength of the quarry face is governed by the presence of rock bridges that act to improve the stability condition of the rock fronts

Geostructural and geomechanical study of the piastrone quarry (Seravezza, Italy) supported by photogrammetry to assess failure mode

The use of non-contact-techniques for rock mass characterization has been growing significantly over the last decade. However, their application to stability assessment of ornamental stone has not yet received much attention from researchers. This study utilizes rock mass data both in terms of slope orientations and degree of fracturing obtained from a point cloud, a set of three-dimensional (3D) points representing a rock mass surface, to (1) investigate the influence of geostructures at different scales and (2) assess quarry stability by determining areas susceptible to different failure types. Multi-resolution point clouds are obtained through several photogrammetric survey techniques to identify important structural elements of the site. By integrating orientation data of discontinuity planes, obtained with a traditional survey, and of traces, outlined on point clouds, several joint sets were identified. Kinematic tests revealed various potential failure modes of the rock slope. Moreover, an analysis of the influence of the discontinuity strength determined by the presence of rock bridges was carried out. The study revealed that the strength of the quarry face is governed by the presence of rock bridges that act to improve the stability condition of the rock fronts

Rock fractures analysis using Structure from Motion technology: new insight from Digital Outcrop Models

Fractures are one of the most important features of the rocks of the upper crust since they strongly influence their physical and chemical behavior and reflect their tectonic history. For this reason, fracture study plays a key role in different branches of the geosciences. Notwithstanding, the quantification of the features and parameters describing fractures could be unsatisfactory using the standard field techniques because they are mainly based on direct-contact methodologies that are affected by errors, as orientation bias and trace censoring, and scarce representativeness, due to the limited possibility of acquiring information of outcrops partially or totally inaccessible. Recently new remote sensing technologies, such as Terrestrial Laser Scanner (TLS) and Digital Photogrammetry (DP), can help to overcome these limitations. Whereas TLS could be very expensive and difficult to use in geological study, DP permits to obtain similar results in an easier way due to cheaper and lighter equipment and more straightforward procedures. Moreover, DP becomes even more useful when combined with Unmanned Aerial Vehicle (UAV) because permits to acquire digital images from positions inaccessible to humans, allowing to analyze geological objects from points of view previously unimaginable. The images acquired from the ground and/or by the UAV can be then processed using different digital algorithms, such as Structure from Motion (SfM), that permit to create 3D model of the studied outcrop. In geosciences, the 3D model representing the surface of the outcrop is often called Digital Outcrop Model (DOM). Despite DOMs can be really useful in different branches of geosciences, their applications are quite well limited because the procedures of their development and sampling/analysis are scarcely analyzed in literature. It is important to highlight that whereas the UAV-based SfM approach is fairly discussed in literature for simple flat areas, is scarcely treated for application to near vertical and not-planar slopes. Moreover, the validity of some procedures of fracture sampling on 3D model, with special regards to the automatic ones, that have been recently presented in literature, is not well treated for real cases of study. The scarce knowledge about these approaches could cause different troubles to the scientific-users: from the application of avoidable time-consuming routine, to the acquisition and interpretation of erroneous data. This research aims to contribute to the scientific knowledge of the use of digital photogrammetry for fractured rock mass analysis, creating and defining new approaches and procedures for the development, analysis and application of DOMs. Here, a workflow for the fracture analysis of steep rocky outcrops and slopes using the 3D DOM is presented. In particular, the following steps are discussed: (i) image acquisition; (ii) development of 3D model; (iii) sampling of DOM; (iv) quantification and parametrization of the 3D measures; (v) application of the 3D quantitative data and parameters to different case of study. Four different cases of study were selected to validate the proposed method: the upper Staffora Valley and Ponte Organasco (Northern Apennines, Italy), Ormea (Ligurian Alps, Italy), and Gallivaggio (Western Alps, Italy) cases of study. However, this methodology could not completely replace the 'direct-contact' field activity, because some information as roughness, infilling and aperture of fractures cannot be measured satisfactory, and because, where possible, field control measures to validate the 3D data are necessary. However, this methodology could be considered as a new necessary procedure for rock-fracture studies because it allows to overcome the inevitable errors of the ground-based traditional methodology and because the DOMs are always available for the analysis, promoting data sharing and comparison, two fundamental principles on which science have and will have to be basedFractures are one of the most important features of the rocks of the upper crust since they strongly influence their physical and chemical behavior and reflect their tectonic history. For this reason, fracture study plays a key role in different branches of the geosciences. Notwithstanding, the quantification of the features and parameters describing fractures could be unsatisfactory using the standard field techniques because they are mainly based on direct-contact methodologies that are affected by errors, as orientation bias and trace censoring, and scarce representativeness, due to the limited possibility of acquiring information of outcrops partially or totally inaccessible. Recently new remote sensing technologies, such as Terrestrial Laser Scanner (TLS) and Digital Photogrammetry (DP), can help to overcome these limitations. Whereas TLS could be very expensive and difficult to use in geological study, DP permits to obtain similar results in an easier way due to cheaper and lighter equipment and more straightforward procedures. Moreover, DP becomes even more useful when combined with Unmanned Aerial Vehicle (UAV) because permits to acquire digital images from positions inaccessible to humans, allowing to analyze geological objects from points of view previously unimaginable. The images acquired from the ground and/or by the UAV can be then processed using different digital algorithms, such as Structure from Motion (SfM), that permit to create 3D model of the studied outcrop. In geosciences, the 3D model representing the surface of the outcrop is often called Digital Outcrop Model (DOM). Despite DOMs can be really useful in different branches of geosciences, their applications are quite well limited because the procedures of their development and sampling/analysis are scarcely analyzed in literature. It is important to highlight that whereas the UAV-based SfM approach is fairly discussed in literature for simple flat areas, is scarcely treated for application to near vertical and not-planar slopes. Moreover, the validity of some procedures of fracture sampling on 3D model, with special regards to the automatic ones, that have been recently presented in literature, is not well treated for real cases of study. The scarce knowledge about these approaches could cause different troubles to the scientific-users: from the application of avoidable time-consuming routine, to the acquisition and interpretation of erroneous data. This research aims to contribute to the scientific knowledge of the use of digital photogrammetry for fractured rock mass analysis, creating and defining new approaches and procedures for the development, analysis and application of DOMs. Here, a workflow for the fracture analysis of steep rocky outcrops and slopes using the 3D DOM is presented. In particular, the following steps are discussed: (i) image acquisition; (ii) development of 3D model; (iii) sampling of DOM; (iv) quantification and parametrization of the 3D measures; (v) application of the 3D quantitative data and parameters to different case of study. Four different cases of study were selected to validate the proposed method: the upper Staffora Valley and Ponte Organasco (Northern Apennines, Italy), Ormea (Ligurian Alps, Italy), and Gallivaggio (Western Alps, Italy) cases of study. However, this methodology could not completely replace the 'direct-contact' field activity, because some information as roughness, infilling and aperture of fractures cannot be measured satisfactory, and because, where possible, field control measures to validate the 3D data are necessary. However, this methodology could be considered as a new necessary procedure for rock-fracture studies because it allows to overcome the inevitable errors of the ground-based traditional methodology and because the DOMs are always available for the analysis, promoting data sharing and comparison, two fundamental principles on which science have and will have to be base