Top

Bulletin of Engineering Geology and the Environment

Published in:

01-06-2022 | Original Paper

Automatic identification of rock discontinuity sets using modified agglomerative nesting algorithm

Authors: Jianhua Yan, Jianping Chen, Jiewei Zhan, Shengyuan Song, Yansong Zhang, Mingyu Zhao, Yongqiang Liu, Wanglai Xu

Published in: Bulletin of Engineering Geology and the Environment | Issue 6/2022

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Identification of rock discontinuity sets is essential for each studied jointed rock slope, and is also an initial step in many existing methods for rock slope stability analysis. This paper presents a new hierarchical agglomerative clustering method using modified agglomerative nesting (MAGNES) algorithm for automatically partitioning discontinuity sets. It is an orientation-based clustering method, and different linkage criteria (single, complete, and average) are incorporated for merging two closest clusters. The performance of MAGNES is tested using a complicate artificial data set, Shanley and Mahtab’s data set, and a real data set from unmanned aerial vehicle (UAV) survey. In addition, the clustering results of four other well-recognized clustering methods are also chosen as comparisons. It shows that the single linkage criterion is inapposite for partitioning orientations and the complete linkage criterion is not robust. Only MAGNES using average linkage criterion (MAGNES_AVG) shows good performance for detecting discontinuity sets. Generally, the main discrepancies among the clustering results lie mainly in the poles at the boundary of two adjacent joint sets. Considering the real data sets are characterized by “ground truth,” the artificial data set with known classification labels is used to further test which method performs better. The number of misclassification points is adopted as an evaluation index, and MAGNES_AVG performs best in partitioning the poles at the boundary of adjacent joint sets. Another advantage of the proposed algorithm is that it is independent of initial parameters, which is user-friendly.

previous article Probabilistic assessment of effects of heterogeneity on the stability of coal mine overburden dump slopes through discrete element framework

next article Multimethod geophysical investigation in karst areas: case studies from Silesia, Poland

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Abellán A, Oppikofer T, Jaboyedoff M, Rosser NJ, Lim M, Lato MJ (2014) Terrestrial laser scanning of rock slope instabilities. Earth Surf Process Landf 39:80–97. https://doi.org/10.1002/esp.3493CrossRef

Assali P, Grussenmeyer P, Villemin T, Pollet N, Viguier F (2014) Surveying and modeling of rock discontinuities by terrestrial laser scanning and photogrammetry: semi-automatic approaches for linear outcrop inspection. J Struct Geol 66:102–114. https://doi.org/10.1016/j.jsg.2014.05.014CrossRef

Battulwar R, Zare-Naghadehi M, Emami E, Sattarvand J (2021) A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models. J Rock Mech Geotech Eng 13:920–936. https://doi.org/10.1016/j.jrmge.2021.01.008CrossRef

Bemis SP, Micklethwaite S, Turner D, James MR, Akciz S, Thiele ST, Bangash HA (2014) Ground-based and UAV-based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology. J Struct Geol 69:163–178. https://doi.org/10.1016/j.jsg.2014.10.007CrossRef

Cai M, Wang P, Zhao K, Zhang D (2005) Fuzzy C-means cluster analysis based on genetic algorithm for automatic identification of joint sets. Chin J Rock Mech Eng 24:371–376. https://doi.org/10.3321/j.issn:1000-6915.2005.03.002 (In Chinese with English abstract)CrossRef

Chen J (2001) 3-D network numerical modeling technique for random discontinuities of rock mass. Chin J Geotech Eng 23:397–402. https://doi.org/10.3321/j.issn:1000-4548.2001.04.003 (In Chinese with English abstract)CrossRef

Chen J, Zhu H, Li X (2016) Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud. Comput Geosci 95:18–31. https://doi.org/10.1016/j.cageo.2016.06.015CrossRef

Day WHE, Edelsbrunner H (1984) Efficient algorithms for agglomerative hierarchical clustering methods. J Classif 1:7–24. https://doi.org/10.1007/BF01890115CrossRef

Ding Q, Huang R, Wang F, Chen JP, Wang C, Zhang X (2018) Multi-parameter dominant grouping of discontinuities in rock mass using improved ISODATA algorithm. Math Probl Eng 5619404:1–10. https://doi.org/10.1155/2018/5619404CrossRef

Emmendorfer RL, Canuto AMP (2021) A generalized average linkage criterion for Hierarchical Agglomerative Clustering. Appl Soft Comput J 100:106990. https://doi.org/10.1016/j.asoc.2020.106990CrossRef

Feng QH, Röshoff K (2004) In-situ mapping and documentation of rock faces using a full-coverage 3-D laser scanning technique. Int J Rock Mech Min Sci 41:139–144. https://doi.org/10.1016/j.ijrmms.2004.03.032CrossRef

Ferrero AM, Forlani G, Roncella R, Voyat HI (2009) Advanced geostructural survey methods applied to rock mass characterization. Rock Mech Rock Eng 42:631–665. https://doi.org/10.1007/s00603-008-0010-4CrossRef

Fisher N (1987) Statistical analysis of spherical data. Cambridge University Press, LondonCrossRef

Gao F, Chen D, Zhou K, Niu W, Liu H (2018) A fast clustering method for identifying rock discontinuity sets. KSCE J Civ Eng 23:556–566. https://doi.org/10.1007/s12205-018-1244-7CrossRef

Ge Y, Tang H, Xia D, Wang L, Zhao B, Teaway JW, Chen H, Zhou T (2018) Automated measurements of discontinuity geometric properties from a 3D-point cloud based on a modified region growing algorithm. Eng Geol 242:44–54. https://doi.org/10.1016/j.enggeo.2018.05.007CrossRef

Gigli G, Casagli N (2011) Semi-automatic extraction of rock mass structural data from high resolution LIDAR point clouds. Int J Rock Mech Min Sci 48:187–198. https://doi.org/10.1016/j.ijrmms.2010.11.009CrossRef

Gomes RK, Oliveira LPL, Gonzaga LJ, Tognoli FMW, Veronez MR, Souza MK (2016) An algorithm for automatic detection and orientation estimation of planar structures in LiDAR-scanned outcrops. Comput Geosci 90:170–178. https://doi.org/10.1016/j.cageo.2016.02.011CrossRef

Goodman RE, Shi GH (1985) Block theory and its application to rock engineering. Prentice-Hall, New Jersey

Hammah RE, Curran JH (1998) Fuzzy cluster algorithm for the automatic identification of joint sets. Int J Rock Mech Min Sci 35:889–905. https://doi.org/10.1016/S0148-9062(98)00011-4CrossRef

Hammah RE, Curran JH (1999) On distance measures for the Fuzzy K-means algorithm for joint data. Rock Mech Rock Eng 32:1–27. https://doi.org/10.1007/s006030050041CrossRef

Han X, Chen J, Wang Q, Li Y, Zhang W, Yu T (2016) A 3D fracture network model for the undisturbed rock mass at the Songta dam site based on small samples. Rock Mech Rock Eng 49:611–619. https://doi.org/10.1007/s00603-015-0747-5CrossRef

Haneberg WC (2008) Using close range terrestrial digital photogrammetry for 3-D rock slope modeling and discontinuity mapping in the United States. Bull Eng Geol Environ 67:457–469. https://doi.org/10.1007/s10064-008-0157-yCrossRef

Harrison JP (1992) Fuzzy objective functions applied to the analysis of discontinuity orientation data. In: Hudson JA (ed) Rock characterization. Thomas Telford, British Geotechnical Society, London, pp 25–30

Hassani M, Seidl T (2016) Using internal evaluation measures to validate the quality of diverse stream clustering algorithms. Vietnam J Comput Sci 4:171–183. https://doi.org/10.1007/s40595-016-0086-9CrossRef

Hoek E, Bray J (1981) Rock slope engineering. The Institution of Mining and Metallurgy, LondonCrossRef

ISRM (1978) Suggested methods for the quantitative description of discontinuities in rock masses. Int J Rock Mech Min Sci 15(6):319–368. https://doi.org/10.1016/0148-9062(79)91476-1CrossRef

Jain AK (2010) Data clustering: 50 years beyond K-means. Pattern Recognit Lett 31:651–666. https://doi.org/10.1016/j.patrec.2009.09.011CrossRef

Jain AK, Murty MN, Flynn PJ (1999) Data clustering: a review. ACM Comput Surv 31:264–323. https://doi.org/10.1145/331499.331504CrossRef

Jimenez R (2007) Fuzzy spectral clustering for identification of rock discontinuity sets. Rock Mech Rock Eng 41:929–939. https://doi.org/10.1007/s00603-007-0155-6CrossRef

Jimenez-Rodriguez R, Sitar N (2006) A spectral method for clustering of rock discontinuity sets. Int J Rock Mech Min Sci 43:1052–1061. https://doi.org/10.1016/j.ijrmms.2006.02.003CrossRef

Klose CD, Seo S, Obermayer K (2005) A new clustering approach for partitioning directional data. Int J Rock Mech Min Sci 42:315–321. https://doi.org/10.1016/j.ijrmms.2004.08.011CrossRef

Kong D, Wu F, Saroglou C (2020) Automatic identification and characterization of discontinuities in rock masses from 3D point clouds. Eng Geol 265:105442. https://doi.org/10.1016/j.enggeo.2019.105442CrossRef

Kulatilake PHSW, Wang L, Tang H, Liang Y (2011) Evaluation of rock slope stability for Yujian River dam site by kinematic and block theory analyses. Comput Geotech 38:846–860. https://doi.org/10.1016/j.compgeo.2011.05.004CrossRef

Li X, Chen Z, Chen J, Zhu H (2019) Automatic characterization of rock mass discontinuities using 3D point clouds. Eng Geol 259:105131. https://doi.org/10.1016/j.enggeo.2019.05.008CrossRef

Li Y, Wang Q, Chen J, Xu L, Song S (2015) K-means algorithm based on particle swarm optimization for the identification of rock discontinuity sets. Rock Mech Rock Eng 48:375–385. https://doi.org/10.1007/s00603-014-0569-xCrossRef

Liu J, Zhao XD, Xu ZH (2017a) Identification of rock discontinuity sets based on a modified affinity propagation algorithm. Int J Rock Mech Min Sci 94:32–42. https://doi.org/10.1016/j.ijrmms.2017.02.012CrossRef

Liu T, Deng J, Zheng J, Zheng L, Zhang Z, Zheng H (2017b) A new semi-deterministic block theory method with digital photogrammetry for stability analysis of a high rock slope in China. Eng Geol 216:76–89. https://doi.org/10.1016/j.enggeo.2016.11.012CrossRef

Lu C, Cai C (2019) Challenges and countermeasures for construction safety during the Sichuan-Tibet railway project. Eng 5:833–838. https://doi.org/10.1016/j.eng.2019.06.007CrossRef

Ma GW, Xu ZH, Zhang W, Li SC (2014) An enriched K-means clustering method for grouping fractures with meliorated initial centers. Arab J Geosci 8:1881–1893. https://doi.org/10.1007/s12517-014-1379-xCrossRef

Mah J, Samson C, McKinnon SD (2011) 3D laser imaging for joint orientation analysis. Int J Rock Mech Min Sci 48:932–941. https://doi.org/10.1016/j.ijrmms.2011.04.010CrossRef

Mahtab MA, Yegulalp TM (1982) A rejection criterion for definition of clusters in orientation data. In: Goodman RE, Heuze FE (eds) Proceedings of the 22nd US Symposium Rock Mechanics, Berkeley, California, August 1982. American Institute of Mining Metallurgy and Petroleum Engineers, New York, pp 116–123. https://doi.org/10.1016/0148-9062(83)91604-2

Maulik U, Bandyopadhyay S (2002) Performance evaluation of some clustering algorithms and validity indices. IEEE Trans Pattern Anal Mach Intell 24:1650–1654. https://doi.org/10.1109/TPAMI.2002.1114856CrossRef

Obregon C, Mitri H (2019) Probabilistic approach for open pit bench slope stability analysis - a mine case study. Int J Min Sci Technol 29:629–640. https://doi.org/10.1016/j.ijmst.2019.06.017CrossRef

Omran MGH, Engelbrecht AP, Salman A (2007) An overview of clustering methods. Intell Data Anal 11:583–605. https://doi.org/10.3233/ida-2007-11602CrossRef

Park HJ, Lee JH, Kim KM, Um JG (2016) Assessment of rock slope stability using gis-based probabilistic kinematic analysis. Eng Geol 203:56–69. https://doi.org/10.1016/j.enggeo.2015.08.021CrossRef

Priest SD (1993) Discontinuity Analysis for Rock Engineering. Chapman & Hall. https://doi.org/10.1016/0926-9851(93)90044-YCrossRef

Riquelme AJ, Abellán A, Tomás R, Jaboyedoff M (2014) A new approach for semi-automatic rock mass joints recognition from 3D point clouds. Comput Geosci 68:38–52. https://doi.org/10.1016/j.cageo.2014.03.014CrossRef

Roncella R, Forlani G (2005) Extraction of planar patches from point clouds to retrieve dip and dip direction of rock discontinuities. ISPRS WG III/3, III/4, V/3 Workshop “Laser Scanning 2005.” Enschede, the Netherlands, pp 162–167

Shanley RJ, Mahtab MA (1976) Delineation and analysis of clusters in orientation data. Math Geol 8:9–23. https://doi.org/10.1007/BF01039681CrossRef

Song S, Wang Q, Chen J, Li Y, Zhang W, Ruan Y (2017) Fuzzy C-means clustering analysis based on quantum particle swarm optimization algorithm for the grouping of rock discontinuity sets. KSCE J Civ Eng 21:1115–1122. https://doi.org/10.1007/s12205-016-1223-9CrossRef

Sturzenegger M, Stead D (2009) Close-range terrestrial digital photogrammetry and terrestrial laser scanning for discontinuity characterization on rock cuts. Eng Geol 106:163–182. https://doi.org/10.1016/j.enggeo.2009.03.004CrossRef

Vasuki Y, Holden EJ, Kovesi P, Micklethwaite S (2014) Semi-automatic mapping of geological Structures using UAV-based photogrammetric data: an image analysis approach. Comput Geosci 69:22–32. https://doi.org/10.1016/j.cageo.2014.04.012CrossRef

Wang X, Zou L, Shen X, Ren Y, Qin Y (2017) A region-growing approach for automatic outcrop fracture extraction from a three-dimensional point cloud. Comput Geosci 99:100–106. https://doi.org/10.1016/j.cageo.2016.11.002CrossRef

Watson GS, Williams EJ (1956) On the construction of significance tests on the circle and the sphere. Biom 43:344–352. https://doi.org/10.2307/2332913CrossRef

Xu LM, Chen JP, Wang Q, Zhou FJ (2013) Fuzzy C-means cluster analysis based on mutative scale chaos optimization algorithm for the grouping of discontinuity sets. Rock Mech Rock Eng 46:189–198. https://doi.org/10.1007/s00603-012-0244-zCrossRef

Xu R, Wunsch D (2005) Survey of clustering algorithms. IEEE Trans Neural Netw 16:645–678. https://doi.org/10.1109/TNN.2005.845141CrossRef

Yan J, Chen J, Li Y, Li Z, Zhang Y, Zhou X, Qaiser M, Liu J, Wang Z (2021) Kinematic-based failure angle analysis for discontinuity-controlled rock slope instabilities: a case study of Ren Yi Peak Cluster in Fusong County, China. Nat Hazards 111:2281–2296. https://doi.org/10.1007/s11069-021-05137-2CrossRef

Zhan J, Chen J, Xu P, Zhang W, Han X, Zhou X (2017a) Automatic identification of rock fracture sets using finite mixture models. Math Geosci 49:1021–1056. https://doi.org/10.1007/s11004-017-9702-1CrossRef

Zhan J, Xu P, Chen J, Wang Q, Zhang W, Han X (2017b) Comprehensive characterization and clustering of orientation data: a case study from the Songta dam site, China. Eng Geol 225:3–18. https://doi.org/10.1016/j.enggeo.2017.01.010CrossRef

Zhang W, Chen JP, Liu C, Huang R, Li M, Zhang Y (2012) Determination of geometrical and structural representative volume elements at the Baihetan dam site. Rock Mech Rock Eng 45:409–419. https://doi.org/10.1007/s00603-011-0191-0CrossRef

Zhao M (2020) Rock structure information acquisition based on UAV photogrammetry. Jilin University (Master thesis, in Chinese with English abstract)

Zhou S, Xu Z, Liu F (2016) Method for determining the optimal number of clusters based on agglomerative hierarchical clustering. IEEE Trans Neural Netw Learn Syst 28:3007–3017. https://doi.org/10.1109/TNNLS.2016.2608001CrossRef

Title: Automatic identification of rock discontinuity sets using modified agglomerative nesting algorithm
Authors: Jianhua Yan
Jianping Chen
Jiewei Zhan
Shengyuan Song
Yansong Zhang
Mingyu Zhao
Yongqiang Liu
Wanglai Xu
Publication date: 01-06-2022
Publisher: Springer Berlin Heidelberg
Published in: Bulletin of Engineering Geology and the Environment / Issue 6/2022
Print ISSN: 1435-9529
Electronic ISSN: 1435-9537
DOI: https://doi.org/10.1007/s10064-022-02724-w

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Other articles of this Issue 6/2022

Failure mechanism of a high-locality colluvial landslide in Wanzhou County, Chongqing, China

Probabilistic assessment of effects of heterogeneity on the stability of coal mine overburden dump slopes through discrete element framework

Risk assessment on the stability of barrier dam induced by Caijiaba landslide, SW China

Large-scale model test for studying the water inrush during tunnel excavation in fault

A data-driven method for predicting debris-flow runout zones by integrating multivariate adaptive regression splines and Akaike information criterion

An improved nonlinear creep damage model of slates considering freeze–thaw damage and bedding damage