TY - CPAPER T1 - Structural recognition and rock mass characterization in underground mines: A UAV and LiDAR map ping bas ed appr oach T2 - MassMin 2020: Eighth International Conference & Exhibition on Mass Mining AU - Canales, CC AU - Sellers, ES ED - Castro, R A2 - Castro, R ED - Báez, F A2 - Báez, F ED - Suzuki, K A2 - Suzuki, K DA - 2020/12/09 PY - 2020 PB - University of Chile PP - Santiago CY - Santiago C1 - Santiago SP - 1302 EP - 1312 AB - The current geotechnical challenges in underground mines create the necessity for tools that can make safe and quick geological and geotechnical assessments, especially in hazard zones such as open stopes, in environments that are increasingly deep and confined. The purpose of this work was to test and validate the use of a new technology called Hovermap (HM). This tool combines the autonomous management of a drone (UAV) with the ability to generate 3D surface representations using LiDAR. This research shows the results of two case studies. The first case study is a comparison of data collected with Hovermap of a medium-quality scan with traditional methods such as Cavity Monitoring Surveys (CMS) and Core Logging to assess surface quality representation for geotechnical purposes. The results showed discordance between the RQD calculated with HM data and RQD calculated with traditional methods. Nevertheless, the origin of the problem is clear, and the solutions are also displayed. Once these results were validated, a second case study was performed with a higher quality scan and easier structural visualization for structural identification. The results were analysed to estimate the potential for use in underground mines for stability analysis. Furthermore, a series of drone flight parameters were estimated to perform scans depending on different purposes, such as velocity and wall distance and Sample Effort Variable (SEV). UR - https://papers.acg.uwa.edu.au/p/2063_97_Canales/ ER - DO - 10.36487/ACG_repo/2063_97