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In the last two decades, significant research has been conducted in the field of automated extraction of rock mass discontinuity characteristics from three-dimensional (3D) models. This provides several methodologies for acquiring discontinuity measurements from 3D models, such as point clouds generated using laser scanning or photogrammetry. Howev...
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... four issues that need to be considered while planning data collection using laser scanners: (i) location, (ii) number of stations to overcome occlusions, (iii) resolution, and (iv) reference system. TLS is also used for detecting rockfalls in an urban area by comparison of point clouds collected at different times ( Abellán et al., 2011). Fig. 2 depicts the Leica RTC360 which is a high-performance 3D laser scanning system. Riquelme et al. (2017) performed an analysis comparing the results of discontinuity characteristics acquired using TLSgenerated point cloud and unmanned aerial vehicle (UAV) datagenerated point cloud, and found out that TLS data are more reliable. Further, ...
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... In recent years, geospatial technologies such as Light Detection and Ranging (LiDAR) and aerial and mobile close-range photogrammetry have been used to measure discontinuities as they allow for offline precise measurements of large regions after a short field campaign. LiDAR sensors produce high-precision 3D point cloud data [13] and reliable results on discontinuity sets [14]. However, since a study area may not be fully scanned by a LiDAR sensor, it is necessary to establish multiple measurement stations on unfavorable rock mass terrains or to adapt multisensory data to acquire a complete scene. ...
Discontinuity is a key element used by geoscientists and civil engineers to characterize rock masses. The traditional approach to detecting and measuring rock discontinuity relies on fieldwork , which poses dangers to human life. Photogrammetric pattern recognition and 3D measurement techniques offer new possibilities without direct contact with rock masses. This study proposes a new approach to detect discontinuities using close-range photogrammetric techniques and convolutional neural networks (CNNs) trained on a small amount of data. Investigations were conducted on basalts in Bala, Ankara, Türkiye. A total of 34 multi-view images were collected with a remotely piloted aircraft system (RPAS), and discontinuity lines were manually delineated on a point cloud generated from these images. The lines were back-projected onto the raw images to increase the amount of data, a process we call multi-view (3D) augmentation. We further evaluated radiometric and geometric augmentation methods, the contribution of multi-view augmentation to the proposed model, and the transfer learning performance of six different CNN architectures. The highest performance was achieved with U-Net + SE-ResNeXt-50 with an F1-score of 90.6%. The CNN model trained from scratch with local features also yielded a similar F1-score (91.7%), which is the highest performance reported in the literature.
... This solves the problems of time-consuming, laborious, biased, dangerous, and limited data of traditional measurements (Haneberg, 2008;Battulwar et al., 2021). Digital images were used earlier than 3D point clouds to characterize rock discontinuities. ...
... The 3D point cloud is a collection of XYZ coordinates of the physical object natural rock discontinuities appear as planes with similar orientations, algorithms related to plane detection are employed to identify these discontinuities. The methods mainly include voxel-based (VB), region-growing (RG), clustering-based (CB), and a few other methods (Battulwar et al., 2021;Daghigh et al., 2022). Gigli and Casagli (2011) pioneered the use of VB methods for discontinuity identification. ...
... (1) The timely feedback between engineers and algorithms cannot be realized. Geostructural analysis from point clouds is a complex task and the algorithms do not have the corresponding geologic knowledge, so the results need to be judged and adjusted manually (Battulwar et al., 2021). However, at present engineers can merely make result judgments and parameter adjustments at the beginning and end of the algorithm, which increases the time and difficulty of parameter adjustments when multiple computational parameters are involved. ...
Rock discontinuities control rock mechanical behaviors and significantly influence the stability of rock masses. However, existing discontinuity mapping algorithms are susceptible to noise, and the calculation results cannot be fed back to users timely. To address this issue, we proposed a human-machine interaction (HMI) method for discontinuity mapping. Users can help the algorithm identify the noise and make real-time result judgments and parameter adjustments. For this, a regular cube was selected to illustrate the workflows: (1) point cloud was acquired using remote sensing; (2) the HMI method was employed to select reference points and angle thresholds to detect group discontinuity; (3) individual discontinuities were extracted from the group discontinuity using a density-based cluster algorithm; and (4) the orientation of each discontinuity was measured based on a plane fitting algorithm. The method was applied to a well-studied highway road cut and a complex natural slope. The consistency of the computational results with field measurements demonstrates its good accuracy, and the average error in the dip direction and dip angle for both cases was less than 3. Finally, the computational time of the proposed method was compared with two other popular algorithms, and the reduction in computational time by tens of times proves its high computational efficiency. This method provides geologists and geological engineers with a new idea to map rapidly and accurately rock structures under large amounts of noises or unclear features.
... 10 Therefore, to make up for the shortcomings of traditional measurement, the current method which usually uses photogrammetry and laser scanning, adopts non-contact measurement. 14 And the corresponding structural plane extraction technology is developing. 15 The current method has the following two advantages. ...
The speed, distance and energy evolution of rapid and long-runout landslides are crucial indicators for evaluating the characteristics of these catastrophic landslides. The Shuicheng rapid and long-runout landslide was chosen as an example for further study, and the evolutionary process of landslide motion was simulated by PFC. The kinematic characteristics and dynamic mechanism were experimentally studied with the above three indicators, and the results indicated that the landslide lasted approximately 60 s and could be divided into four stages: uniform deformation, erosion-disintegration, block-spilt and convergence-accumulation. The speed of the landslide peaked at 36.1 m/s at 28 s. Controlled by the terrain, particles collided violently, and there was strong momentum transfer, which greatly promoted the long-runout movement of the landslide, with a maximum movement distance of 1303 m. During movement, gravitational potential energy was mainly converted into dissipated energy of friction and collision, accounting for 51.0 % and 39.6 %, respectively, of the total gravitational potential energy released during the landslide. After the landslide initiated, the apparent frictional coefficient reached a peak of 0.49 in 6 s. Then, the apparent frictional coefficient gradually decreased and stabilized at approximately 0.32. The factor leading to the decrease in the apparent frictional coefficient was the rapid increase in the dissipated energy of friction. In addition, it was found through quantitative calculation that the dissipated energy of friction generated in the propagation can cause the basal facies to rise by 65.08 °C. The results from the numerical simulations are in agreement with the findings from the field investigation, affirming the thermal pressurization impact associated with rapid and long-runout landslides. These simulations yield insights that are scientific merit for understanding the kinematics and dynamics underlying these types of landslides.
... Contrary to traditional manual field surveys, the primary challenge in utilizing 3D laser scanning for engineering geological surveys lies in the automatic extraction of linear and surface characteristics from point cloud data using computer algorithms [9,[13][14][15][16]. A recent review [17] provides a comprehensive overview of the digital surveying techniques utilized for capturing rockface imagery or point clouds, as well as the extraction of various rockface discontinuity features such as structural planes, joint persistence, distances, roughness, and block sizes. Notably, this review paper serves as the first extensive analysis within this particular field and emphasizes the significance of computer processing. ...
... For most researchers, planar discontinuities have primarily been used for studying the grouping of discontinuities at different yields, while linear discontinuities have mainly been utilized for characterizing trace lengths [17]. In fact, the form of the exposed discontinuity primarily depends on the orientation and contour shape of the drift [8]. ...
... In recent years, non-contact measurement methods have found widespread application in the acquisition of discontinuities information in tunnels and underground engineering rock masses (Xu et al., 2021a;Battulwar et al., 2021;Xu et al., 2021b;Xu et al., 2022;Xu et al., 2023). Non-contact measurements primarily involve two methods: la-ser scanning and close-range photogrammetry. ...
In the process of grading and dynamically optimizing the design and construction parameters of the surrounding rock mass of a rock tunnel face, efficiently and accurately acquiring the geometrical parameters of the rock discontinuities is an important basic task. To address the problems of time consuming, low accuracy, and high danger associated with traditional methods of obtaining the structural information of rock mass, this paper proposes a method for three-dimensional reconstruction and intelligent information extraction of tunnel face based on binocular stereo vision (BSV). First, the parallel binocular device with a single camera was improved, calibrated using the checkerboard calibration method. By integrating with the semi-global matching algorithm, the BSV based method for the three-dimensional reconstruction of the rock mass of the tunnel face was optimized. Furthermore, based on the results from on-site engineering applications, this study leveraged two parameters, point cloud density and algorithm runtime, to determine the optimal values for the disparity range and window size parameters within the semi-global stereo matching algorithm. This enhancement improved the performance of the 3D reconstruction method based on binocular stereo vision. Finally, efficient and refined intelligent methods for extracting structural parameters of the rock mass were proposed based on k-nearest neighbor search and kernel density estimation. The research results can provide reliable technical support for the intelligent and efficient acquisition of rock mass structural information in rock tunnel engineering faces.
... Based on the acquired point cloud data, engineering geological mapping can be done by applying manual and semi-automated mapping techniques for obtaining discontinuity orientation, spacing, and persistence data (Battulwar et al. 2021). Applying such methods enables the collection of large amounts of discontinuity data compared to traditional field surveys. ...
... The fracture network is a highly causative factor for rockfalls as it serves as a pathway for groundwater and determines erodibility and slope failure mechanisms [41,42]. The modelling of fracture system parameters like distribution, connectivity, length, and angle is crucial in slope instability studies [43]. The choice of method for determining cracks as well as tracing is based on a compromise between the required accuracy and detail and the absence of determination errors and processing costs [41,43]. ...
... The modelling of fracture system parameters like distribution, connectivity, length, and angle is crucial in slope instability studies [43]. The choice of method for determining cracks as well as tracing is based on a compromise between the required accuracy and detail and the absence of determination errors and processing costs [41,43]. Manual techniques are reasonable when the size of the study site is relatively small or high accuracy is required, while using them on large areas is time-consuming and impractical [44,45]. ...
Gravitational processes on cut slopes located close to infrastructure are a high concern in mountainous regions. There are many techniques for survey, assessment, and prognosis of hazardous exogenous geological processes. The given research describes using UAV data and GIS morpho-metric analysis for delineation of hazardous rockfall zones and 3D modelling to obtain an enhanced, detailed evaluation of slope characteristics. Besides the slope geomorphometric data, we integrated discontinuity layers, including rock plains orientation and fracture network density. Cloud Compare software 2.12 was utilised for facet extraction. Fracture discontinuity analysis was performed in QGIS using the Network GT plugin. The presented research uses an Analytical Hierarchy Process (AHP) to determine the weight of each contributing factor. GIS overlay of weighted factors is applied for rockfall susceptibility mapping. This integrated approach allows for a more comprehensive GIS-based rockfall susceptibility mapping by considering both the structural characteristics of the outcrop and the geomorphological features of the slope. By combining UAV data, GIS-based mor-phometric analysis, and discontinuity analysis, we are able to delineate hazardous rockfall zones effectively.
... Combining RANSAC plane fitting and DBSCAN clustering with 3D convex hull calculations facilitates the volume computation of the rock block. The principle involves selecting any four non-coplanar points [21,22] within the rock block point cloud, forming an initial tetrahedron as the base of the convex hull. After establishing the initial convex hull, other points' spatial relation to this hull is assessed. ...
... In the first step, the first step is to use Canon EOS 5D Mark III camera for image acquisition of the color model, the resolution of the image film is 240 dpi, in order to obtain a fine and high-quality 3D model, it is necessary to capture a sufficient number of overlapping images from all directions, after completing the image acquisition, the 3D reconstruction software is used for the processing [25] in order to generate a 3D model, the software used in this experiment is ContextCapture, and then adjust the size of the model, and finally get the 3D digital model in OBJ format.OBJ files mainly support polygonal models, the complete color model also contains mtl files and img mapping files. The three lesions r were 9.4680mm, 8.9910mm, 9.5120mm, calculated from the original image resolution (150dpi) within 1.0mm accounted for at least 5.9055 pixels. ...
In recent years, with the development of three-dimensional digitization of cultural relics, most cultural relic protection units have a large number of fine three-dimensional data of cultural relics, especially complex geometric objects such as painted cultural relics. At present, how to automatically extract surface disease information from the fine three-dimensional color model of painted cultural relics and avoid the accuracy loss caused by reducing the dimension by conventional methods is an urgent problem to be solved in the investigation of cultural relics diseases.In view of the above problems, this paper proposes an automatic and high-precision extraction method for cultural relics surface shedding diseases based on three-dimensional fine data. Firstly, this paper designs a two-dimensional and three-dimensional integrated data conversion model based on OSG three-dimensional engine, which realizes the mutual conversion between three-dimensional color model texture and two-dimensional image. Secondly, a SLIC segmentation algorithm with adaptive K value is proposed, which solves the problem of superpixel K value setting and improves the accuracy of image segmentation. Finally, through the two-dimensional and three-dimensional integrated model, the disease is statistically analyzed and labeled on the three-dimensional model.Experiments show that for painted plastic objects with complex surfaces, the disease extraction method based on three-dimensional fine model proposed in this paper has improved geometric accuracy compared with the current popular orthophoto extraction method, and the disease investigation is more comprehensive ; compared with the current three-dimensional manual extraction method in commercial software, this method greatly improves the efficiency of disease extraction while ensuring the extraction accuracy. The research method of this paper activates a large number of existing three-dimensional fine data of cultural protection units, and converts data mining and analysis from conventional two-dimensional data to three-dimensional data, which is more in line with the scientific utilization of data in accuracy and efficiency, and has certain scientific research value, leading value and practical significance.
... The introduction of non-contact measurement technologies represented by laser scanning and photogrammetry brought some advantages to the fracture trace measurement (Gigli and Casagli, 2011;Umili et al., 2013;Abellán et al., 2014;Ferrero et al., 2014;Chen et al., 2017;Guo et al., 2018Guo et al., , 2019Buyer et al., 2020;Farmakis et al., 2020;Battulwar et al., 2021;Liu et al., 2022). Laser scanning can directly obtain point cloud data for extracting traces, but its disadvantage is the fact that it is difficult to cover steep or occluded areas, the equipment is expensive and its installation process is tedious . ...
This study utilizes a semantic-level computer vision-based detection to characterize fracture traces of hard rock pillars in underground space. The trace images captured by photogrammetry are used to establish the database for training two convolutional neural network (CNN)-based models, i.e., U-Net (University of Freiburg, Germany) and DeepLabV3+ (Google, USA) models. Chain code technology, polyline approximation algorithm, and the circular window scanning approach are combined to quantify the main characteristics of fracture traces on flat and uneven surfaces, including trace length, dip angle, density, and intensity. The extraction results indicate that the CNN-based models have better performances than the edge detection methods-based Canny and Sobel operators for extracting the trace and reducing noise, especially the DeepLabV3+ model. Furthermore, the quantization results further prove the reliability of extracting the fracture trace. As a result, a case study with two types of traces (i.e., on flat and uneven surfaces) demonstrates that the proposed semantic-level computer vision detection is an accurate and efficient approach for characterizing the fracture trace of hard rock pillars.
