Qualitative assessment reveals improved spatial data collection for Digital Twin in quarries, indicating laser scanning enhances accuracy and efficiency.
Quarries represent critical sites for raw material extraction, for which regular monitoring and mine surveying documentation, along with its updating, is essential to ensuring safety, environmental protection, and effective management of the mining process. This article aims to evaluate the modern approach to quarry surveying and the creation of a base mining map using advanced laser scanning methods, such as terrestrial laser scanning (TLS) and simultaneous localization and mapping (SLAM)-based mobile laser scanning (MLS). Particular attention is given to the analysis of noise generated using TLS and SLAM-based MLS methods. An analysis of mutual differences between point clouds is presented to compare the spatial accuracy of the point clouds obtained using MLS technology against those from the reference TLS method on both horizontally and vertically oriented test areas. To assess the quality and usability of data obtained using the TLS and MLS methods, a selected section of the mining wall was analyzed based on the distance between points (Cloud-to-Cloud analysis), cross-section analysis, and volume calculations based on 3D mesh models generated from stage edges and point clouds. The findings offer valuable insights into the effective use of each method in quarry surveying, contributing to the development of innovative approaches to spatial data collection as a base for creating Digital Twins of quarries. The article also evaluates the efficiency of both measurement approaches in terms of accuracy, measurement speed, and practical applicability in mining practices. The results show that the point cloud obtained by the TLS Leica RTC360 device, compared to that by the MLS method using the FARO Orbis device (FARO Technologies, Inc., Lakemary, FL, USA), achieves better values in terms of average noise level, standard deviation, interval of highest point density, and RMSD (Root Mean Square Deviation) in test areas. Our conclusions highlight the high potential of laser scanning for the modernization of mining documentation and the improvement of surveying processes in the smart mining industry, particularly for updating Digital Elevation Models (DEMs), Digital Terrain Models (DTMs), Digital Surface Models (DSMs), and other 3D models of quarries for the creation of their Digital Twins.
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Kovanič et al. (2025) studied this question.
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