Masahiro Ohkawa
Mitsubishi Materials Techno Corporation, Tokyo 110-0016, Japan
Kota Osawa
Mitsubishi Materials Techno Corporation, Tokyo 110-0016, Japan
Ryo Okino
Mitsubishi Materials Techno Corporation, Tokyo 110-0016, Japan
Shigeaki Matsuo
Mitsubishi Materials Techno Corporation, Tokyo 110-0016, Japan
Evaluating rock mass quality using three-dimensional (3D) point clouds is crucial for discontinuity extraction and is widely applied in various industrial sectors. However, the utilization of this method in geological surveys remains limited. Notable limitations of current research include the scarcity of validation using simple geometric shapes for discontinuity extraction methods, and the lack of studies that target both planar and linear discontinuity. To address these gaps, this study proposes a workflow for identifying discontinuity planes and traces in rock outcrops from photogrammetric 3D modeling, employing the Compass and Facets plugins in the open-source CloudCompare software. Prior to field application, the efficacy of the extraction methods was first evaluated using experimental datasets of a cube and an isosceles triangular prism generated under laboratory-controlled conditions. This validation demonstrated exceptional accuracy, with the dip and dip direction (DDD) of extracted structures consistently within ±2° of the actual values. Following this rigorous laboratory validation, this methodology was applied to a more complex natural rock outcrop (Miocene–Pliocene deposits in Japan), demonstrating its applicability in realistic geological settings for identifying structures. The results showed that the dip and dip direction trends of the extracted bedding planes and faults were consistent with field measurements, achieving a time reduction of approximately 40% compared to traditional methods. In conclusion, through strictly controlled initial verification and subsequent successful application to a complex natural setting, this study confirmed that the proposed workflow can effectively and efficiently extract discontinuous geological structures from point clouds.
[1] Bieniawski, Z.T., 1989. Engineering Rock Mass Classifications: A Complete Manual for Engineers and Geologists in Mining, Civil, and Petroleum Engineering. John Wiley & Sons: New York, NY, USA. pp. 1–251.
[2] Jaboyedoff, M., Couture, R., Locat, P., 2009. Structural analysis of Turtle Mountain (Alberta) using digital elevation model: Toward a progressive failure. Geomorphology. 103(1), 5–16.
[3] Nagendran, S.K., Ismail, M.A.M., Wen, Y.T., 2019. Photogrammetry approach on geological plane extraction using CloudCompare FACET plugin and scanline survey. Bulletin of the Geological Society of Malaysia. 68, 151–158.
[4] Kong, D., Wu, F., Saroglou, C., 2020. Automatic identification and characterization of discontinuities in rock masses from 3D point clouds. Engineering Geology. 265, 105442. DOI: https://doi.org/10.1016/j.enggeo.2019.105442
[5] Singh, S.K., Banerjee, B.P., Lato, M.J., et al., 2022. Automated rock mass discontinuity set characterisation using amplitude and phase decomposition of point cloud data. International Journal of Rock Mechanics and Mining Sciences. 152, 105072.
[6] Viero, A., Teza, G., Massironi, M., et al., 2010. Laser scanning-based recognition of rotational movements on a deep seated gravitational instability: The Cinque Torri case (North-Eastern Italian Alps). Geomorphology. 122, 191–204.
[7] Bellian, J.A., Kerans, C., Jennette, D.C., 2005. Digital outcrop models: Applications of terrestrial scanning lidar technology in stratigraphic modeling. Journal of Sedimentary Research. 75(2), 166–176. DOI: https://doi.org/10.2110/jsr.2005.013
[8] Riquelme, A.J., Abellán, A., Tomás, R., 2015. Discontinuity spacing analysis in rock masses using 3D point clouds. Engineering Geology. 195, 185–195.
[9] Chen, J., Zhu, H., Li, X., 2016. Automatic extraction of discontinuity orientation from rock mass surface 3D point cloud. Computers & Geosciences. 95, 18–31.
[10] Ge, Y., Tang, H., Xia, D., et al., 2018. Automated measurements of discontinuity geometric properties from a 3D-point cloud based on a modified region growing algorithm. Engineering Geology. 242, 44–54.
[11] Snavely, N., Seitz, S.M., Szeliski, R., 2008. Modeling the world from internet photo collections. International Journal of Computer Vision. 80, 189–210.
[12] Cawood, A.J., Bond, C.E., Howell, J.A., et al., 2017. LiDAR, UAV or compass-clinometer? Accuracy, coverage and the effects on structural models. Journal of Structural Geology. 98, 67–82.
[13] Nesbit, P.R., Durkin, P.R., Hugenholtz, C.H., et al., 2018. 3-D stratigraphic mapping using a digital outcrop model derived from UAV images and structure-from-motion photogrammetry. Geosphere. 14, 2469–2486.
[14] Cirillo, D., Cerritelli, F., Agostini, S., et al., 2022. Integrating post-processing kinematic (PPK)–structure-from-motion (SfM) with unmanned aerial vehicle (UAV) photogrammetry and digital field mapping for structural geological analysis. ISPRS International Journal of Geo-Information. 11, 437.
[15] Thiele, S.T., Grose, L., Samsu, A., et al., 2017. Rapid, semi-automatic fracture and contact mapping for point clouds, images and geophysical data. Solid Earth. 8, 1241–1253.
[16] Menegoni, N., Giordan, D., Perotti, C., et al., 2019. Detection and geometric characterization of rock mass discontinuities using a 3D high-resolution digital outcrop model generated from RPAS imagery–Ormea rock slope, Italy. Engineering Geology. 252, 145–163.
[17] Guo, J., Zhang, Z., Mao, Y., et al., 2022. Automatic extraction of discontinuity traces from 3D rock mass point clouds considering the influence of light shadows and color change. Remote Sensing. 14, 5314.
[18] Chen, J., Fang, Q., Zhang, D., et al., 2023. A critical review of automated extraction of rock mass parameters using 3D point cloud data. Intelligent Transportation Infrastructure. 2, liad005.
[19] Battulwar, R., Zare-Naghadehi, M., Emami, E., et al., 2021. A state-of-the-art review of automated extraction of rock mass discontinuity characteristics using three-dimensional surface models. Journal of Rock Mechanics and Geotechnical Engineering. 13(4), 920–936.
[20] Bazazian, D., Casas, J.R., Ruiz-Hidalgo, J., 2015. Fast and robust edge extraction in unorganized point clouds. In Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, Adelaide, Australia, 23–25 November 2015; pp. 1–8.
[21] Guo, J., Wu, L., Zhang, M., et al., 2018. Towards automatic discontinuity trace extraction from rock mass point cloud without triangulation. International Journal of Rock Mechanics and Mining Sciences. 112, 226–237.
[22] Pu, C., Zhan, J., Zhang, W., et al., 2025. Characterization and clustering of rock discontinuity sets: A review. Journal of Rock Mechanics and Geotechnical Engineering. 17(2), 1240–1262.
[23] Yi, X., Feng, W., Wang, D., et al., 2023. An efficient method for extracting and clustering rock mass discontinuities from 3D point clouds. Acta Geotechnica. 18(7), 3485–3503.
[24] Gu, Z., Xiong, X., Yang, C., et al., 2024. A method for identification rock mass discontinuities in underground drift with pre-separation of linear and planar point cloud features. Ain Shams Engineering Journal. 15(12), 103110.
[25] Liu, Y., Hua, W., Chen, Q., et al., 2024. Characterization of complex rock mass discontinuities from LiDAR point clouds. Remote Sensing. 16(17), 3291.
[26] Yi, X., Wu, W., Feng, W., et al., 2025. Rock discontinuity extraction from 3D point clouds using pointwise clustering algorithm. Journal of Rock Mechanics and Geotechnical Engineering. 17(7), 4429–4444.
[27] Wang, S., Dong, F., Zhang, Z., et al., 2023. Multi-index dominant grouping of rock mass discontinuities based on the combined weighting method: A case study for the Huayang tunnel. Tunnelling and Underground Space Technology. 139, 105211.
[28] Liu, Y., Chen, J., Tan, C., et al., 2023. A novel system for multivariate analysis of discontinuities in fractured rock masses based on manifold learning and fractal models. International Journal of Rock Mechanics and Mining Sciences. 170, 105547.
[29] Dewez, T.J., Girardeau-Montaut, D., Allanic, C., et al., 2016. Facets: A CloudCompare plugin to extract geological planes from unstructured 3D point clouds. ISPRS International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 41, 799–804.
[30] Panigrahi, B., Srivastava, D.C., Tiwari, S., et al., 2023. Application of semi-automated methods for extraction of geological surface orientations: A case study from the outer Garhwal Himalaya. Journal of Earth System Science. 132, 171.
[31] Chandra, A.P., Setianto, A., Indrawan, I.G.B., 2024. Discontinuity measurement for slope failure analysis with structure from motion method using drone on a slope in Hargowilis, Kokap District, Kulon Progo Regency, DI Yogyakarta Province. IOP Conference Series: Earth and Environmental Science. 1378(1), 012014.
[32] Lukačić, H., Katić, J., Bernat Gazibara, S., et al., 2024. Rapid 3D rockfall susceptibility assessment of the Orašac rock slope, Croatia. In Proceedings of the 6th Regional Symposium on Landslides in the Adriatic-Balkan Region, Belgrade, Serbia, 15–18 May 2024; pp. 213–218.
[33] Sevil-Aguareles, J., Pisani, L., Chiarini, V., et al., 2025. Gypsum cave notches and their palaeoenvironmental significance: A combined morphometric study using terrestrial laser scanning, traditional cave mapping, and geomorphological observations. Geomorphology. 471, 109576.
[34] Lee, S., Suh, J., Park, H.D., 2013. Smart compass-clinometer: A smartphone application for easy and rapid geological site investigation. Computers & Geosciences. 61, 32–42.
[35] Yamamoto, Y., Mukoyoshi, H., Ogawa, Y., 2005. Structural characteristics of shallowly buried accretionary prism: Rapidly uplifted Neogene accreted sediments on the Miura–Boso Peninsula, central Japan. Tectonics. 24, TC5008.
[36] Ogawa, Y., 1978. Structural characteristics and tectonisms around the microcontinent in the outer margin of the Paleozoic–Mesozoic geosyncline of Japan. Tectonophysics. 47(3–4), 295–310.
[37] Ogawa, Y., 1982. Tectonics of some forearc fold belts in and around the arc–arc crossing area in central Japan. Geological Society, London, Special Publications. 10(1), 49–61.
[38] Kodama, K., Oka, S., Mitsunashi, T., 1980. Geology of the Misaki District, Quadrangle Series, Scale 1:50,000. Geological Survey of Japan (AIST): Tsukuba, Japan. Available from: https://www.gsj.jp/Map/EN/docs/5man_doc/08/08_093.htm
[39] Pickering, K.T., Agar, S.M., Prior, D.J., 1990. Vein structure and the role of pore fluids in early wet-sediment deformation, Late Miocene volcaniclastic rocks, Miura Group, SE Japan. Geological Society, London, Special Publications. 54(1), 417–430.
[40] Yamamoto, Y., Ohta, Y., Ogawa, Y., 2000. Implication for the two-stage layer-parallel faults in the context of the Izu forearc collision zone: Examples from the Miura accretionary prism, central Japan. Tectonophysics. 325, 133–144.
[41] Stow, D.A., Taira, A., Ogawa, Y., et al., 1998. Volcaniclastic sediments, process interaction and depositional setting of the Mio–Pliocene Miura Group, SE Japan. Sedimentary Geology. 115, 351–381.
[42] Mazumder, R., van Loon, A.T., Malviya, V.P., et al., 2016. Soft-sediment deformation structures in the Mio–Pliocene Misaki Formation within alternating deep-sea clays and volcanic ashes (Miura Peninsula, Japan). Sedimentary Geology. 344, 323–335.
[43] Geospatial Information Authority of Japan. Map and aerial photograph service. Available from: https://service.gsi.go.jp/map-photos/app/map (cited 15 July 2021). (in Japanese)
[44] Suzuki, T., Takahashi, K.I., Sunamura, T., et al., 1970. Rock mechanics on the formation of washboard-like relief on wave-cut benches at Arasaki, Miura Peninsula, Japan. Geographical Review of Japan. 43(4), 211–222. (in Japanese)
[45] Gonçalves, G., Gonçalves, D., Gómez-Gutiérrez, Á., et al., 2021. 3D reconstruction of coastal cliffs from fixed-wing and multi-rotor UAS: Impact of SfM–MVS processing parameters, image redundancy and acquisition geometry. Remote Sensing. 13(6), 1222.
[46] Lin, J., Wang, R., Li, L., et al., 2019. A workflow of SfM-based digital outcrop reconstruction using Agisoft PhotoScan. In Proceedings of the 2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC), Xiamen, China, 5–7 July 2019; pp. 711–715.
[47] Han, S., Han, D., 2024. Enhancing direct georeferencing using real-time kinematic UAVs and structure-from-motion-based photogrammetry for large-scale infrastructure. Drones. 8(12), 736.
[48] Daghigh, H., Tannant, D.D., Daghigh, V., et al., 2022. A critical review of discontinuity plane extraction from 3D point cloud data of rock mass surfaces. Computers & Geosciences. 169, 105241.
[49] Cardozo, N., Allmendinger, R.W., 2013. Spherical projections with OSXStereonet. Computers & Geosciences. 51, 193–205.
[50] Monsalve, A., Yager, E.M., Tonina, D., 2023. Evaluating Apple iPhone LiDAR measurements of topography and roughness elements in coarse bedded streams. Journal of Ecohydraulics. 10(2), 181–191.
[51] Ivelja, T., Bechor, B., Hasan, O., et al., 2020. Improving vertical accuracy of UAV digital surface models by introducing terrestrial laser scans on a point-cloud level. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XLIII-B1-2020, 457–463.
[52] Bemis, S.P., Micklethwaite, S., Turner, D., et al., 2014. Ground-based and UAV-based photogrammetry: A multi-scale, high-resolution mapping tool for structural geology and paleoseismology. Journal of Structural Geology. 69, 163–178.
[53] Riquelme, A., Cano, M., Tomás, R., et al., 2017. Identification of rock slope discontinuity sets from laser scanner and photogrammetric point clouds: A comparative analysis. Procedia Engineering. 191, 838–845.
[54] Novakova, L., Pavlis, T.L., 2017. Assessment of the precision of smart phones and tablets for measurement of planar orientations: A case study. Journal of Structural Geology. 97, 93–103.
[55] Benrabah, A., Senent Domínguez, S., Carrera-Ramírez, F., et al., 2023. Structural and geomechanical analysis of natural caves and rock shelters: Comparison between manual and remote sensing discontinuity data gathering. Remote Sensing. 16(1), 72.
[56] Wong, D., Chan, K., Millis, S., 2019. Digital mapping of discontinuities. In Proceedings of the 39th HKIE Geotechnical Division Annual Seminar, Hong Kong, China, 11 April 2019; p. 13.
Copyright © 2026 Masahiro Ohkawa, Kota Osawa, Ryo Okino, Shigeaki Matsuo
This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.
