Abstract

KGARUME, T.; VAN SCHOOR, M.; MPOFU, M.  and  GROBLER, H.. Light detection and ranging-based georeferencing of underground mining ground-penetrating radar data. J. S. Afr. Inst. Min. Metall. [online]. 2025, vol.125, n.7, pp.393-400. ISSN 2411-9717.  https://doi.org/10.17159/2411-9717/3166/2025.

The South African mining industry has committed to achieving a state of zero harm for its workforce, with a strong emphasis on worker health and safety. Among the major safety concerns are falls of ground, a leading cause of injuries and fatalities. Ground-penetrating radar, a non-destructive geophysical method, is recognised for its ability to image structures, fractures, and geological features within the rock mass. However, ground penetrating radar data is often acquired in local coordinates, posing challenges for visualisation in mine computer-aided design or three-dimensional visualisation software. This study explores the pivotal role of light detection and ranging data in transforming ground penetrating radar data from local survey coordinates to absolute mine coordinates. A comprehensive georeferencing methodology is presented, providing the stepwise progression from the initial georeferencing of ground penetrating radar data to the ultimate integration of ground penetrating radar and light detection and ranging datasets, resulting in the creation of a ground penetrating radar-light detection and ranging three-dimensional model. The proposed approach not only facilitates the integration of but also offers a practical means of visualising the integrated datasets within commonly used computer-aided design or three-dimensional visualisation software. An essential aspect of this integration is the adoption of non-proprietary data formats, specifically American Standard Code for Information Interchange text files, ensuring broader accessibility and compatibility. The potential for integrating diverse datasets to construct insightful models of the underground mining environment is illustrated. Integration of different datasets has the potential to offer a holistic understanding of the mining environment, providing essential information to decision-makers.

Keywords : georeferencing; light detection and ranging (LiDAR); ground penetrating radar (GPR); data integration; visualisation; health and safety.

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