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<p>Characterisation of rock mass discontinuities is crucial in underground excavations and design. Recent advancement in Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry (drone technology) has permitted geotechnical characterization of underground excavation faces to be executed efficiently and in real-time. This study focuses on extraction of discontinuity parameter semi-automatically from a 3D Point Cloud obtained from drone imagery in an underground mine at southwestern Ghana. Captured images from the underground stope were imported and processed using Agisoft metashape and CloudCompare software to generate a 3D Point Cloud. A MATLAB Extension tool called Discontinuity set Extractor (DSE) was subsequently used to process and semi-automatically extract discontinuity sets from the generated 3-D dense point cloud data. A total of six discontinuity sets were identified in the first section of the 3D point cloud, whereas seven discontinuity sets were delineated in the second section. The maximum percentage error between the direct field measurement and semi-automatically obtained discontinuity orientations was 2.3% which reveals the effectiveness of the unmanned aerial vehicle (UAV) and 3D point cloud for discontinuity characterisation in underground mines. Therefore, the use of UAV and 3D point cloud as tools in underground rock characterisation is trustworthy since it can offer insightful initial data about rock mass discontinuities.</p>

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Automatic Discontinuity Characterisation Using Structure-from-Motion Multi-View Stereo (SfM-MVS) Photogrammetry in an Underground Mine in Southwestern Ghana

  • 期刊论文

  • 发表日期：

    2026年1月12日

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  • Sylvanus Sebbeh-Newton,
  • Ebenezer Atuahene,
  • Jamel Seidu,
  • Yakubu Issaka,
  • Ezekiel Sackitey Nanor

摘要

Characterisation of rock mass discontinuities is crucial in underground excavations and design. Recent advancement in Structure-from-Motion Multi-View Stereo (SfM-MVS) photogrammetry (drone technology) has permitted geotechnical characterization of underground excavation faces to be executed efficiently and in real-time. This study focuses on extraction of discontinuity parameter semi-automatically from a 3D Point Cloud obtained from drone imagery in an underground mine at southwestern Ghana. Captured images from the underground stope were imported and processed using Agisoft metashape and CloudCompare software to generate a 3D Point Cloud. A MATLAB Extension tool called Discontinuity set Extractor (DSE) was subsequently used to process and semi-automatically extract discontinuity sets from the generated 3-D dense point cloud data. A total of six discontinuity sets were identified in the first section of the 3D point cloud, whereas seven discontinuity sets were delineated in the second section. The maximum percentage error between the direct field measurement and semi-automatically obtained discontinuity orientations was 2.3% which reveals the effectiveness of the unmanned aerial vehicle (UAV) and 3D point cloud for discontinuity characterisation in underground mines. Therefore, the use of UAV and 3D point cloud as tools in underground rock characterisation is trustworthy since it can offer insightful initial data about rock mass discontinuities.