A new approach for semi-automatic rock mass joints recognition from 3D point clouds

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Títol: A new approach for semi-automatic rock mass joints recognition from 3D point clouds
Autors: Riquelme, Adrián | Abellán Fernández, Antonio | Tomás, Roberto | Jaboyedoff, Michel
Grups d'investigació o GITE: Ingeniería del Terreno y sus Estructuras (InTerEs)
Centre, Departament o Servei: Universidad de Alicante. Departamento de Ingeniería Civil
Paraules clau: LiDAR | Rock mass | Discontinuities | Semi-automatic detection | 3D point cloud | Sensitivity analysis
Àrees de coneixement: Ingeniería del Terreno
Data de publicació: 4-d’abril-2014
Editor: Elsevier
Citació bibliogràfica: Computers & Geosciences. 2014, Accepted Manuscript, Available online 4 April 2014. doi:10.1016/j.cageo.2014.03.014
Resum: Rock mass characterization requires a deep geometric understanding of the discontinuity sets affecting rock exposures. Recent advances in Light Detection and Ranging (LiDAR) instrumentation currently allow quick and accurate 3D data acquisition, yielding on the development of new methodologies for the automatic characterization of rock mass discontinuities. This paper presents a methodology for the identification and analysis of flat surfaces outcropping in a rocky slope using the 3D data obtained with LiDAR. This method identifies and defines the algebraic equations of the different planes of the rock slope surface by applying an analysis based on a neighbouring points coplanarity test, finding principal orientations by Kernel Density Estimation and identifying clusters by the Density-Based Scan Algorithm with Noise. Different sources of information —synthetic and 3D scanned data— were employed, performing a complete sensitivity analysis of the parameters in order to identify the optimal value of the variables of the proposed method. In addition, raw source files and obtained results are freely provided in order to allow to a more straightforward method comparison aiming to a more reproducible research.
Patrocinadors: This work was partially funded by the University of Alicante (vigrob-157, uausti11–11, and gre09–40 projects), the Swiss National Science Foundation (FNS-138015 and FNS-144040 projects) and by the Generalitat Valenciana (project GV/2011/044).
URI: http://hdl.handle.net/10045/36557
ISSN: 0098-3004 (Print) | 1873-7803 (Online)
DOI: 10.1016/j.cageo.2014.03.014
Idioma: eng
Tipus: info:eu-repo/semantics/article
Revisió científica: si
Versió de l'editor: http://dx.doi.org/10.1016/j.cageo.2014.03.014
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