Regular surveying provides a great amount of information about a mine. Having mine maps and models and regularly monitoring stockpile volumes and slope stability is a considerable perk for a mine operation, allowing for improved short-term and long-term planning. This thesis aimed to collect, evaluate, present and discuss UAV-based LiDAR and photogrammetry data. A DJI system consisting of the M300 RTK aircraft and two payloads: Zenmuse L1 and Zenmuse P1 cameras was used. DJI D-RTK 2 GNSS RTK was included as a base station, with an additional set of 8 GCPs for georeferencing. In this research, two surveying methods were applied: photogrammetry and LiDAR data acquisition. The two methods were evaluated and compared internally. Several criteria were used for the evaluation, such as precision, data size and versatility. Different software was used for LiDAR point clouds and photogrammetric model processing. Also, various computer programs are discussed for further monitoring activities. The goal was to assess the accuracy of the different sensor systems as well as the onboard RTK system in collecting point cloud data. Photogrammetric models are evaluated according to georeferencing deviations. One set is georeferenced with GCPs, and the other only with the onboard RTK system. Those two methods were compared. All the comparison was done with raw data. Usually, the way to go is refining and simplifying the data for further use, because the data from open pits consumes a lot of computer memory. This puts less strain on the computer and boosts processing times. Based on this evaluation, potential improvements are identified. The conclusions are to be implemented into research and industry and assist in the constant advancement of surveying practices in open pit mines.