Automated rockmass discontinuity mapping from 3-dimensional surface data

Remote sensing technologies, specifically terrestrial-based static LiDAR and photogrammetry, are transforming from state-of-the-art to state-of-practice tools for engineering geologists. The complexity of available software packages to perform standard geomechanical analyses is slowing the widesprea...

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Vydané v:	Engineering geology Ročník 164; s. 155 - 162
Hlavní autori:	Vöge, Malte, Lato, Matthew J., Diederichs, Mark S.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Kidlington Elsevier B.V 17.09.2013 Elsevier
Predmet:	algorithms Applied sciences Automated algorithms Buildings. Public works computer software engineering Exact sciences and technology Feature extraction Geologic structure geology Geotechnics LiDAR Measurements. Technique of testing Photogrammetry PlaneDetect remote sensing Soil investigations. Testing PlaneDetect Feature extraction Automated algorithms Geologic structure Photogrammetry LiDAR Cartography Discontinuity Geology Site analysis Rock mass Algorithm Remote sensing Lidar Automatic system Pattern extraction Method study
ISSN:	0013-7952, 1872-6917
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Abstract	Remote sensing technologies, specifically terrestrial-based static LiDAR and photogrammetry, are transforming from state-of-the-art to state-of-practice tools for engineering geologists. The complexity of available software packages to perform standard geomechanical analyses is slowing the widespread adoption of these technologies within the geotechnical community. The development of automated processing tools for feature extraction and data interpretation is aimed at eliminating the need for complex software and manual analysis. This paper presents the development of the algorithms used in the software program PlaneDetect for the automated identification and mapping of planar discontinuities within a 3-dimensional surface model of a jointed rockmass. The software employs a five stage procedure of: surface smoothing, edge detection and masking, blast damaged detection and masking, discontinuity identification, and discontinuity set clustering. The software outputs a stereonet of discontinuity orientations colored by joint set family, an image of the 3-dimensional model with each mapped discontinuity colored by the set family, and a text file of discontinuity orientations. The results of the geomechanical analyses computed by PlaneDetect in comparison to the manual mapping results are more statistically reliable based on less user bias. The time saving realized through using PlaneDetect for mapping discontinuities is approximately ten times compared to the manual mapping approaches. •Development of a new algorithm for automated fracture mapping•Mathematics of the algorithm is explained in detail.•Example liDAR data processed within 2degrees of manual methods•Algorithms developed are 10× more efficient than manual methods.
AbstractList	Remote sensing technologies, specifically terrestrial-based static LiDAR and photogrammetry, are transforming from state-of-the-art to state-of-practice tools for engineering geologists. The complexity of available software packages to perform standard geomechanical analyses is slowing the widespread adoption of these technologies within the geotechnical community. The development of automated processing tools for feature extraction and data interpretation is aimed at eliminating the need for complex software and manual analysis. This paper presents the development of the algorithms used in the software program PlaneDetect for the automated identification and mapping of planar discontinuities within a 3-dimensional surface model of a jointed rockmass. The software employs a five stage procedure of: surface smoothing, edge detection and masking, blast damaged detection and masking, discontinuity identification, and discontinuity set clustering. The software outputs a stereonet of discontinuity orientations colored by joint set family, an image of the 3-dimensional model with each mapped discontinuity colored by the set family, and a text file of discontinuity orientations. The results of the geomechanical analyses computed by PlaneDetect in comparison to the manual mapping results are more statistically reliable based on less user bias. The time saving realized through using PlaneDetect for mapping discontinuities is approximately ten times compared to the manual mapping approaches. •Development of a new algorithm for automated fracture mapping•Mathematics of the algorithm is explained in detail.•Example liDAR data processed within 2degrees of manual methods•Algorithms developed are 10× more efficient than manual methods. Remote sensing technologies, specifically terrestrial-based static LiDAR and photogrammetry, are transforming from state-of-the-art to state-of-practice tools for engineering geologists. The complexity of available software packages to perform standard geomechanical analyses is slowing the widespread adoption of these technologies within the geotechnical community. The development of automated processing tools for feature extraction and data interpretation is aimed at eliminating the need for complex software and manual analysis. This paper presents the development of the algorithms used in the software program PlaneDetect for the automated identification and mapping of planar discontinuities within a 3-dimensional surface model of a jointed rockmass. The software employs a five stage procedure of: surface smoothing, edge detection and masking, blast damaged detection and masking, discontinuity identification, and discontinuity set clustering. The software outputs a stereonet of discontinuity orientations colored by joint set family, an image of the 3-dimensional model with each mapped discontinuity colored by the set family, and a text file of discontinuity orientations. The results of the geomechanical analyses computed by PlaneDetect in comparison to the manual mapping results are more statistically reliable based on less user bias. The time saving realized through using PlaneDetect for mapping discontinuities is approximately ten times compared to the manual mapping approaches.
Author	Diederichs, Mark S. Vöge, Malte Lato, Matthew J.
Author_xml	– sequence: 1 givenname: Malte surname: Vöge fullname: Vöge, Malte organization: Norwegian Geotechnical Institute, Sognsveien 72, 0806 Oslo, Norway – sequence: 2 givenname: Matthew J. surname: Lato fullname: Lato, Matthew J. email: mjlato@rocksense.ca organization: Norwegian Geotechnical Institute, Sognsveien 72, 0806 Oslo, Norway – sequence: 3 givenname: Mark S. surname: Diederichs fullname: Diederichs, Mark S. organization: Queen's University, Dept of Geol Sci. and Geol. Eng, Kingston, Canada
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Cites_doi	10.1680/geot.1965.15.3.287 10.1111/j.1477-9730.2008.00516.x 10.1016/S0924-2716(99)00008-8 10.1016/j.tust.2010.04.008 10.1130/GES00139.1 10.1016/j.compgeo.2010.09.003 10.1007/3DRes.02(2011)3 10.1016/j.ijrmms.2010.11.009 10.1007/s10064-008-0157-y 10.3141/1913-18 10.1016/j.ijrmms.2004.03.032 10.1130/GES00104.1 10.1016/j.ijrmms.2012.08.003 10.1016/j.ijrmms.2008.04.007 10.5194/nhess-9-267-2009 10.1007/BF01039902 10.3390/s90705241 10.1007/s00603-010-0086-5 10.1016/j.ijrmms.2012.06.003 10.1016/S0148-9062(98)00011-4 10.1016/S0013-7952(97)00069-0 10.1007/BF01036074 10.1016/S0019-9958(69)90591-9
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Keywords	PlaneDetect Feature extraction Automated algorithms Geologic structure Photogrammetry LiDAR Cartography Discontinuity Geology Site analysis Rock mass Algorithm Remote sensing Lidar Automatic system Pattern extraction Method study
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Snippet	Remote sensing technologies, specifically terrestrial-based static LiDAR and photogrammetry, are transforming from state-of-the-art to state-of-practice tools...
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SubjectTerms	algorithms Applied sciences Automated algorithms Buildings. Public works computer software engineering Exact sciences and technology Feature extraction Geologic structure geology Geotechnics LiDAR Measurements. Technique of testing Photogrammetry PlaneDetect remote sensing Soil investigations. Testing
Title	Automated rockmass discontinuity mapping from 3-dimensional surface data
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