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Remote Sensing
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3D Point Clouds in Rock Mechanics Applications
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3D Point Clouds in Rock Mechanics Applications

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 22335

Special Issue Editors

Prof. Dr. Roberto Tomás

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Guest Editor
Department of Civil Engineering, University of Alicante, Campus de San Vicente del Raspeig s/n, 03080 Alicante, Spain
Interests: rock mechanics; landslides; infrastructures; remote sensing; geotechnical engineering
Special Issues, Collections and Topics in MDPI journals
Dr. Adrián Riquelme

E-Mail
Guest Editor
Department of Civil Engineering, University of Alicante, Campus de San Vicente del Raspeig s/n, 03080 Alicante, Spain
Interests: 3d point clouds; remote sensing; rock mechanics; discontintuities
Dr. Antonio Abellan

E-Mail Website
Guest Editor
Director of the Centre for Research on the Alpine environment, Rue de l'Industrie 45, 1950 Sion, SwitzerlandInstitute of Applied Geosciences, School of Earth and Environment, University of Leeds, Leeds, UK
Interests: 3D point clouds; LiDAR; photogrammetry; ground deformation; rockfalls
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Michel Jaboyedoff

E-Mail Website
Guest Editor
Institute of Earth Sciences, University of Lausanne, Geopolis 3793, CH-1015 Lausanne, Switzerland
Interests: natural hazards and risks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We would like to invite you to contribute to a Special Issue of Remote Sensing that will be dedicated to the nascent field of using 3D point clouds in rock mechanics. Rock mechanics and rock engineering, as the branch of mechanics concerned with the response of the rock and rock masses to the surrounding forces, aims to model ground behavior to external disturbances, such as geometrical changes (road cuts, excavations, tunneling, mining, etc.) and subsequent external variations in the force fields. This is usually carried out through the evaluation of the rock mass properties (e.g., orientation of discontinuities, persistence, normal spacing, roughness) following labor-intensive traditional in situ procedures.

Today, the improvement of geometry acquisition techniques enables the generation of large, dense, and highly-accurate three-dimensional representation of the reality, e.g., 3D point clouds of rock masses. The use of diverse sensors and platforms (e.g., light detection and ranging, digital photogrammetry, airborne, ground-based, UAV) together with the development of innovative processing strategies is opening up new possibilities to improve the knowledge about the characteristics, behavior, and performance of rock masses, which is ultimately transforming well-stablished approaches in geotechnical and geological engineering.

Notwithstanding these advances, great challenges remain in the development of novel computational procedures to gain a more detailed knowledge about rock mass properties using 3D sensors, and new improvement on 3D point cloud acquisition, analysis, and feature extraction is still required. This information plays a key role in subsequent rock mass classifications, modeling and stability analysis of geohazards (e.g., landslides and sinkholes) civil works (e.g., tunnels, foundations or rock slopes) and mining (e.g. open pit mines and underground mining). Following on the incorporation of the above-mentioned procedures into risk management, design, calculation procedures and other applications in geological and geotechnical engineering can bring outstanding benefits.

This Special Issue invites contributions aiming to present new strategies for acquiring and exploiting 3D point clouds for investigating rock masses, including high-impact applications in civil works and geohazards. Submissions are encouraged to cover a broad range of topics, including, but not limited to, the following activities:

  • Novel techniques, sensors or procedures targeting a better acquisition and generation of 3D point clouds of rock masses;
  • Development of algorithms intended for the extraction of rock mass features either in laboratory or real scale;
  • Integration of different sensors with 3D point cloud for rock mass characterization, slope stability analysis, and feature extraction;
  • Development of comprehensive methodologies for the application of 3D point clouds for feature extraction, 3DPC to discrete fracture network, stability assessment, and modeling of tunnels, slopes, and foundations;
  • Case studies showing innovative experiences and validations in the use of 3D point clouds for the study of geohazards, rock mass characterization, and application of rock mass classifications;
  • Cutting-edge experiences in the creation of 3D databases, repositories, web visualization, and data sharing in rock mechanics;
  • Further related topics.

Prof. Roberto Tomás
Dr. Adrián Riquelme
Dr. Antonio Abellán
Prof. Michel Jaboyedoff
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • 3d point clouds
  • Lidar
  • Photogrammetry
  • Structure-from-motion
  • Rock mechanics
  • Rock mass
  • Characterization
  • Discrete fracture network
  • Civil works
  • Geohazards
  • Rock mass classification
  • Slope stability analysis
  • Tunneling
  • Foundations
  • Mining engineering

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Published Papers (5 papers)

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28 pages, 15598 KiB  
Article
QDC-2D: A Semi-Automatic Tool for 2D Analysis of Discontinuities for Rock Mass Characterization
by Lidia Loiotine, Charlotte Wolff, Emmanuel Wyser, Gioacchino Francesco Andriani, Marc-Henri Derron, Michel Jaboyedoff and Mario Parise
Remote Sens. 2021, 13(24), 5086; https://doi.org/10.3390/rs13245086 - 14 Dec 2021
Cited by 5 | Viewed by 3853
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue 3D Point Clouds in Rock Mechanics Applications)
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23 pages, 12322 KiB  
Article
A New Method for Automatic Extraction and Analysis of Discontinuities Based on TIN on Rock Mass Surfaces
by Xiang Wu, Fengyan Wang, Mingchang Wang, Xuqing Zhang, Qing Wang and Shuo Zhang
Remote Sens. 2021, 13(15), 2894; https://doi.org/10.3390/rs13152894 - 23 Jul 2021
Cited by 15 | Viewed by 3276
Abstract
Light detection and ranging (LiDAR) can quickly and accurately obtain 3D point clouds on the surface of rock masses, and on the basis of this, discontinuity information can be extracted automatically. This paper proposes a new method to automatically extract discontinuity information from [...] Read more.
Light detection and ranging (LiDAR) can quickly and accurately obtain 3D point clouds on the surface of rock masses, and on the basis of this, discontinuity information can be extracted automatically. This paper proposes a new method to automatically extract discontinuity information from 3D point clouds on the surface of rock masses. This method first applies the improved K-means algorithm based on the clustering algorithm by fast search and find of density peaks (DPCA) and the silhouette coefficient in the cluster validity index to identify the discontinuity sets of rock masses, and then uses the hierarchical density-based spatial clustering of applications with noise (HDBSCAN) algorithm to segment the discontinuity sets and to extract each discontinuity from a discontinuity set. Finally, the random sampling consistency (RANSAC) method is used to fit the discontinuities and to calculate their parameters. The 3D point clouds of the typical rock slope in the Rockbench repository is used to extract the discontinuity orientations using the new method, and these are compared with the results obtained from the classical approach and the previous automatic methods. The results show that, compared to the results obtained by Riquelme et al. in 2014, the average deviation of the dip direction and dip angle is reduced by 26% and 8%, respectively; compared to the results obtained by Chen et al. in 2016, the average deviation of the dip direction and dip angle is reduced by 39% and 40%, respectively. The method is also applied to an artificial quarry slope, and the average deviation of the dip direction and dip angle is 5.3° and 4.8°, respectively, as compared to the manual method. Furthermore, the related parameters are analyzed. The study shows that the new method is reliable, has a higher precision when identifying rock mass discontinuities, and can be applied to practical engineering. Full article
(This article belongs to the Special Issue 3D Point Clouds in Rock Mechanics Applications)
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30 pages, 4330 KiB  
Article
Photogrammetric Digital Surface Model Reconstruction in Extreme Low-Light Environments
by Riccardo Roncella, Nazarena Bruno, Fabrizio Diotri, Klaus Thoeni and Anna Giacomini
Remote Sens. 2021, 13(7), 1261; https://doi.org/10.3390/rs13071261 - 26 Mar 2021
Cited by 11 | Viewed by 3370
Abstract
Digital surface models (DSM) have become one of the main sources of geometrical information for a broad range of applications. Image-based systems typically rely on passive sensors which can represent a strong limitation in several survey activities (e.g., night-time monitoring, underground survey and [...] Read more.
Digital surface models (DSM) have become one of the main sources of geometrical information for a broad range of applications. Image-based systems typically rely on passive sensors which can represent a strong limitation in several survey activities (e.g., night-time monitoring, underground survey and night surveillance). However, recent progresses in sensor technology allow very high sensitivity which drastically improves low-light image quality by applying innovative noise reduction techniques. This work focuses on the performances of night-time photogrammetric systems devoted to the monitoring of rock slopes. The study investigates the application of different camera settings and their reliability to produce accurate DSM. A total of 672 stereo-pairs acquired with high-sensitivity cameras (Nikon D800 and D810) at three different testing sites were considered. The dataset includes different camera configurations (ISO speed, shutter speed, aperture and image under-/over-exposure). The use of image quality assessment (IQA) methods to evaluate the quality of the images prior to the 3D reconstruction is investigated. The results show that modern high-sensitivity cameras allow the reconstruction of accurate DSM in an extreme low-light environment and, exploiting the correct camera setup, achieving comparable results to daylight acquisitions. This makes imaging sensors extremely versatile for monitoring applications at generally low costs. Full article
(This article belongs to the Special Issue 3D Point Clouds in Rock Mechanics Applications)
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20 pages, 8543 KiB  
Article
A Practical Methodology for Generating High-Resolution 3D Models of Open-Pit Slopes Using UAVs: Flight Path Planning and Optimization
by Rushikesh Battulwar, Garrett Winkelmaier, Jorge Valencia, Masoud Zare Naghadehi, Bijan Peik, Behrooz Abbasi, Bahram Parvin and Javad Sattarvand
Remote Sens. 2020, 12(14), 2283; https://doi.org/10.3390/rs12142283 - 16 Jul 2020
Cited by 35 | Viewed by 5003
Abstract
High-resolution terrain models of open-pit mine highwalls and benches are essential in developing new automated slope monitoring systems for operational optimization. This paper presents several contributions to the field of remote sensing in surface mines providing a practical framework for generating high-resolution images [...] Read more.
High-resolution terrain models of open-pit mine highwalls and benches are essential in developing new automated slope monitoring systems for operational optimization. This paper presents several contributions to the field of remote sensing in surface mines providing a practical framework for generating high-resolution images using low-trim Unmanned Aerial Vehicles (UAVs). First, a novel mobile application was developed for autonomous drone flights to follow mine terrain and capture high-resolution images of the mine surface. In this article, case study is presented showcasing the ability of developed software to import area terrain, plan the flight accordingly, and finally execute the area mapping mission autonomously. Next, to model the drone’s battery performance, empirical studies were conducted considering various flight scenarios. A multivariate linear regression model for drone power consumption was derived from experimental data. The model has also been validated using data from a test flight. Finally, a genetic algorithm for solving the problem of flight planning and optimization has been employed. The developed power consumption model was used as the fitness function in the genetic algorithm. The designed algorithm was then validated using simulation studies. It is shown that the offered path optimization can reduce the time and energy of high-resolution imagery missions by over 50%. The current work provides a practical framework for stability monitoring of open-pit highwalls while achieving required energy optimization and imagery performance. Full article
(This article belongs to the Special Issue 3D Point Clouds in Rock Mechanics Applications)
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27 pages, 16483 KiB  
Technical Note
An Integration of UAV-Based Photogrammetry and 3D Modelling for Rockfall Hazard Assessment: The Cárcavos Case in 2018 (Spain)
by Ilenia G. Gallo, Mónica Martínez-Corbella, Roberto Sarro, Giulio Iovine, Juan López-Vinielles, Mario Hérnandez, Gaetano Robustelli, Rosa María Mateos and Juan Carlos García-Davalillo
Remote Sens. 2021, 13(17), 3450; https://doi.org/10.3390/rs13173450 - 31 Aug 2021
Cited by 28 | Viewed by 4543
Abstract
An example of the combined use of UAV photogrammetry and rockfall numerical simulation is described. A case of fragmental rockfall occurred on 17 November 2018 in Cárcavos, a site located in the Spanish municipality of Ayna (Albacete). The event caused a great social [...] Read more.
An example of the combined use of UAV photogrammetry and rockfall numerical simulation is described. A case of fragmental rockfall occurred on 17 November 2018 in Cárcavos, a site located in the Spanish municipality of Ayna (Albacete). The event caused a great social alarm as some infrastructure was affected. By using Unmanned Aerial Vehicle (UAV) photogrammetry, a high-resolution 3D model has been generated from point cloud data, and distribution and size of the fragmented rocks (more than 600 boulders) determined. The analysis has been performed through numerical simulations to: (1) reproduce the paths followed by the real blocks; and (2) estimate the speed and energy of the blocks, together with their heights, impacts and stopping points. Accordingly, source areas have been identified, including the potential source areas and unstable blocks on the slope. In addition, the exposed elements at risk (buildings, facilities, infrastructures, etc.) have been identified, and the effectiveness of mitigation measures against future events evaluated. Full article
(This article belongs to the Special Issue 3D Point Clouds in Rock Mechanics Applications)
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