Meta-analysis and systematic review of drone technology in mining and geotechnical engineering
DOI:
https://doi.org/10.51301/ejsu.2026.i3.05Keywords:
drones, UAVs, UAS, photogrammetry, mine waste, volumetrics, accuracy, subsidence, landslide, mappingAbstract
Unmanned Aerial Vehicles (UAVs) have revolutionized geotechnical and mining operations by enabling fast, high-resolution, and inexpensive spatial data acquisition, terrain modeling, and monitoring. The current review and meta-analysis integrate observations from over 133 peer-reviewed articles to present a comparison of the accuracy of UAV-based surveying methods, i.e., photogrammetry and LiDAR, and traditional methods such as total stations and terrestrial LiDAR. This study focuses on application of UAVs and drone use in mining and geotechnical engineering in terms of finding stockpile volumes, mining subsidence, mine tailings and dump site, and rock mass identification. UAVs are capable of achieving decent accuracy on a regular basis, as indicated by meta-analysis, if optimized flight parameters, RTK/PPK positioning, and GCPs are utilized. Improved accuracy in UAV LiDAR surveys and balance between visual accuracy and cost-recovery in UAV photogrammetry are feasible. However, error magnitude is dependent on complexity of terrain, flight planning, and meteorology, emphasizing methodical accuracy. Bibliometric analysis indicates exponential publication development per year since 2017 for UAVs, and China once more emerges as the leading contributor with funding, authorship, and research. Keyword and co-authorship network visualization demonstrates increasing adherence to machine learning, 3D reconstruction, and digital twin technologies. SWOT analysis determines UAVs' efficiency of operations, safety benefit, and visual outcome as its major strengths but bottlenecks to data processing, inconsistent accuracy, and difficulties in unfavorable terrain conditions as its weaknesses. Shortages of skills are listed as major weaknesses to extensive deployment. The findings are reinforced by an industry validation survey in which 100% of respondents testified to UAV-improved efficiency and 71% to significant cost savings. There are some concerns regarding the amount of data processing and UAV response in slopes or complex environments. UAVs are transitioning from test equipment to geotechnical equipment of choice, providing real-time actionable information for monitoring, site planning, and hazard analysis. Sensor fusion, artificial intelligence-driven analytics, and normalization of workflow destinies are UAVs to be a major driver of mining digitalization. Future research will focus on underground mapping, automation, and standardization of the regulation to open up the full potential of UAVs across the mining value chain.
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