QDC-2D: A Semi-Automatic Tool for 2D Analysis of Discontinuities for Rock Mass Characterization

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.

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Implementation of computation codes in geostructural surveys to evaluate rock mass stability aimed at the protection of cultural heritage

10.5194/egusphere-egu21-343 ◽

2021 ◽

Author(s):

Stefano Cardia ◽

Biagio Palma ◽

Mario Parise

Keyword(s):

World War Ii ◽

Point Clouds ◽

Digital Data ◽

Rock Masses ◽

Rock Outcrops ◽

Mean Values ◽

Phlegraean Fields ◽

Planar Surfaces ◽

Novel Approach ◽

Computation Codes

Instability of rock masses is a frequent problem in Italy, which territory is naturally predisposed to a variety of geological hazards. Therefore, issues related to the study of rock masses have always been of primary importance, since their consequences directly affect human lives and the urbanized areas, causing severe losses to society. In order to identify the areas most susceptible to gravity-related phenomena in such settings, the traditional approaches are often not sufficient, and need to be integrated by new tools and techniques aimed at properly and quantitatively describe the structural arrangement of rock masses. These include the use of close range remote sensing techniques. It is now many years that various attempts have been made to standardize processes to extract volumetric shapes from digital data, in order to individuate geometrical features in point clouds and, eventually, to identify discontinuities on rock outcrops.&#160; We present an attempt to develop and experimentally implement an application of computation codes and software control via command line, to carry out geomechanical investigations on rock masses, starting from 3D surveys. The final goal is to provide reliable results on the likely instability processes in surface and underground settings, as a contribution to the mitigation of the related risks. For this aim, a novel approach is proposed: in order to combine user observation made in situ and on digital results of scanning, our attention was focused on developing non-automatic methods, which could allow, giving a tolerance angle for both dip and dip direction, the extraction of discontinuities on well-structured datasets representing point clouds. This approach could be considered a fully supervised type of classification, because the user can specify the query by placing a numerical input representing an interval of tolerance in degrees; then, it has as output a cluster of planar surfaces belonging to the given interval for each set. The code, organized in a basic software called GEODS (alpha version), which runs on Windows operating systems, also utilizes the results to represent the rocky surfaces on charts and stereographic projections, and is able to calculate standard deviation and mean values of the classified clusters. It is useful to identify the density of each identified discontinuity and to evaluate potential kinematics as well, based on geometric relationships, through analyses carried by a skilled user. This approach was tested at the Cocceio cave, in Campania, southern Italy: this site has historical importance since the Roman age. Reused during World War II, it is now part of a redevelopment project of the Phlegraean Fields, an area renowned for its natural beauty, which includes numerous archaeological sites. At the cave, with this new method, we were able to recognize an additional set, with minor frequency than the other sets, and which was not identified during previous studies.&#160; As a final result, it is thus expected to contribute in an innovative way to the implementation of alternative and accurate methods in structural analysis and the geomechanical characterization of rock masses.

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3D Thermal Monitoring of Jointed Rock Masses through Infrared Thermography and Photogrammetry

Remote Sensing ◽

10.3390/rs13050957 ◽

2021 ◽

Vol 13 (5) ◽

pp. 957

Author(s):

Guglielmo Grechi ◽

Matteo Fiorucci ◽

Gian Marco Marmoni ◽

Salvatore Martino

Keyword(s):

Surface Temperature ◽

Infrared Thermography ◽

Point Cloud ◽

Engineering Geology ◽

Point Clouds ◽

Jointed Rock ◽

Geometric Accuracy ◽

Rock Masses ◽

Natural Systems ◽

Temperature Distributions

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

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2D quantitative analysis of fractures from high-resolution photos for the geomechanical characterization of rock masses

10.5194/egusphere-egu21-2589 ◽

2021 ◽

Author(s):

Emmanuel Wyser ◽

Lidia Loiotine ◽

Charlotte Wolff ◽

Gioacchino Francesco Andriani ◽

Michel Jaboyedoff ◽

...

Keyword(s):

High Resolution ◽

Point Clouds ◽

Mitigation Measures ◽

Future Perspective ◽

Rock Masses ◽

Sampling Errors ◽

Discontinuity Sets ◽

Adverse Weather ◽

Geomechanical Characterization

The identification of discontinuity sets and their properties is among the key factors for the geomechanical characterization of rock masses, which is fundamental for performing stability analyses, and for planning prevention and mitigation measures as well. In practice, discontinuity data are collected throughout difficult and time-consuming field surveys, especially when dealing with areas of wide extension, difficult accessibility, covered by dense vegetation, or with adverse weather conditions. Consequently, even experienced operators may introduce sampling errors or misinterpretations, leading to biased geomechanical models for the investigated rock mass. In the last decades, new remote techniques such as photogrammetry, Light Detection and Ranging (LiDAR), Unmanned Aerial Vehicle (UAV) and InfraRed Thermography (IRT) have been introduced to overcome the limits of conventional surveys. We propose here a new tool for extracting information on the fracture pattern in rock masses, based on remote sensing methods, with particular reference to the analysis of high-resolution georeferenced photos. The first step consists in applying the Structure from Motion (SfM) technique on photos acquired by means of digital cameras and UAV techniques. Once aligned and georeferenced, the orthophotos are exported in a GIS software, to draw the fracture traces at an appropriate scale. We developed a MATLAB routine to extract information on the geostructural setting of rock masses by performing a quantitative 2D analysis of the fracture traces, based on formulas reported in the literature. The code was written by testing few experimental and simple traces and was successively validated on an orthophoto from a real case study. Currently, the script plots the fracture traces as polylines and calculates their orientation (strike) and length. Subsequently, it detects the main discontinuity sets by fitting an experimental composite Gaussian curve on histograms showing the number of discontinuities according to their orientation, and splitting the curve in simpler Gaussian curves, with peaks corresponding to the main discontinuity sets. Then, for each set, a linear scanline intersecting the highest number of traces is plotted, and the apparent and real spacing are calculated. In a second step, a grid of circular scanlines covering the whole area where the traces are located is plotted, and the mean trace intensity, trace density and trace length estimators are calculated. It is expected to test the presented tools on other case studies, in order to optimize them and calculate additional metrics, such as persistence and block sizes, useful to the geomechanical characterization of rock masses. As a future perspective, a similar approach could be investigated for 3D analyses from point clouds.

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Quantitative evaluation of mechanical properties of the natural rock joints for analyzing behavior of structures in discontinuous rock masses.

Doboku Gakkai Ronbunshu ◽

10.2208/jscej.1999.624_231 ◽

1999 ◽

pp. 231-243 ◽

Cited By ~ 3

Author(s):

Yujing JIANG ◽

Mitsuo NAKAGAWA ◽

Tetsuro ESAKI

Keyword(s):

Mechanical Properties ◽

Quantitative Evaluation ◽

Rock Joints ◽

Rock Masses ◽

Natural Rock ◽

Discontinuous Rock

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A Stereological Study on Crack Geometry of Discontinuous Rock Masses

Science on Form ◽

10.1007/978-94-009-3757-4_24 ◽

1986 ◽

pp. 183-189

Author(s):

Masanobu Oda

Keyword(s):

Rock Masses ◽

Crack Geometry ◽

Discontinuous Rock

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An Improved Computing Method for 3D Mechanical Connectivity Rates Based on a Polyhedral Simulation Model of Discrete Fracture Network in Rock Masses

Rock Mechanics and Rock Engineering ◽

10.1007/s00603-018-1423-3 ◽

2018 ◽

Vol 51 (6) ◽

pp. 1789-1800 ◽

Cited By ~ 6

Author(s):

Mingchao Li ◽

Shuai Han ◽

Sibao Zhou ◽

Ye Zhang

Keyword(s):

Simulation Model ◽

Fracture Network ◽

Discrete Fracture Network ◽

Rock Masses ◽

Discrete Fracture ◽

Computing Method

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Intact Planar Abstraction of Buildings via Global Normal Refinement from Noisy Oblique Photogrammetric Point Clouds

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi7110431 ◽

2018 ◽

Vol 7 (11) ◽

pp. 431 ◽

Cited By ~ 1

Author(s):

Qing Zhu ◽

Feng Wang ◽

Han Hu ◽

Yulin Ding ◽

Jiali Xie ◽

...

Keyword(s):

Global Optimization ◽

Three Dimensional ◽

Region Growing ◽

Point Clouds ◽

Spatial Relations ◽

Global Scale ◽

Surface Boundary ◽

Planar Surfaces ◽

Normal Vectors ◽

Almost All

Oblique photogrammetric point clouds are currently one of the major data sources for the three-dimensional level-of-detail reconstruction of buildings. However, they are severely noise-laden and pose serious problems for the effective and automatic surface extraction of buildings. In addition, conventional methods generally use normal vectors estimated in a local neighborhood, which are liable to be affected by noise, leading to inferior results in successive building reconstruction. In this paper, we propose an intact planar abstraction method for buildings, which explicitly handles noise by integrating information in a larger context through global optimization. The information propagates hierarchically from a local to global scale through the following steps: first, based on voxel cloud connectivity segmentation, single points are clustered into supervoxels that are enforced to not cross the surface boundary; second, each supervoxel is expanded to nearby supervoxels through the maximal support region, which strictly enforces planarity; third, the relationships established by the maximal support regions are injected into a global optimization, which reorients the local normal vectors to be more consistent in a larger context; finally, the intact planar surfaces are obtained by region growing using robust normal and point connectivity in the established spatial relations. Experiments on the photogrammetric point clouds obtained from oblique images showed that the proposed method is effective in reducing the influence of noise and retrieving almost all of the major planar structures of the examined buildings.

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Automatic Workflow for Roof Extraction and Generation of 3D CityGML Models from Low-Cost UAV Image-Derived Point Clouds

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9120743 ◽

2020 ◽

Vol 9 (12) ◽

pp. 743

Author(s):

Arnadi Murtiyoso ◽

Mirza Veriandi ◽

Deni Suwardhi ◽

Budhy Soeksmantono ◽

Agung Budi Harto

Keyword(s):

3D Modeling ◽

Low Cost ◽

Point Clouds ◽

3D Models ◽

Additional Advantage ◽

Planar Surfaces ◽

Modeling Process ◽

Point Cloud Segmentation ◽

Segmentation Approach ◽

Uav Image

Developments in UAV sensors and platforms in recent decades have stimulated an upsurge in its application for 3D mapping. The relatively low-cost nature of UAVs combined with the use of revolutionary photogrammetric algorithms, such as dense image matching, has made it a strong competitor to aerial lidar mapping. However, in the context of 3D city mapping, further 3D modeling is required to generate 3D city models which is often performed manually using, e.g., photogrammetric stereoplotting. The aim of the paper was to try to implement an algorithmic approach to building point cloud segmentation, from which an automated workflow for the generation of roof planes will also be presented. 3D models of buildings are then created using the roofs’ planes as a base, therefore satisfying the requirements for a Level of Detail (LoD) 2 in the CityGML paradigm. Consequently, the paper attempts to create an automated workflow starting from UAV-derived point clouds to LoD 2-compatible 3D model. Results show that the rule-based segmentation approach presented in this paper works well with the additional advantage of instance segmentation and automatic semantic attribute annotation, while the 3D modeling algorithm performs well for low to medium complexity roofs. The proposed workflow can therefore be implemented for simple roofs with a relatively low number of planar surfaces. Furthermore, the automated approach to the 3D modeling process also helps to maintain the geometric requirements of CityGML such as 3D polygon coplanarity vis-à-vis manual stereoplotting.

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