During the last decades photogrammetric computer vision systems have been well established in scientific and commercial applications. Recent developments in image-based 3D reconstruction systems, affordable high quality digital consumer grade cameras and especially the increasing availability of unmanned aerial vehicles (UAVs) in conjunction with automated multi-view processing pipelines have resulted in an easy way of acquiring mid- to large-scale spatial data and creating realistic, visually appealing and accurate 3D models. Multi-copter UAVs are bridging the gap between terrestrial and traditional aerial image acquisition and are therefore ideally suited to enable easy and safe data collection and inspection tasks in complex or hazardous environments like mining. The presented research deals with studies on the identification and quantification of relevant influencing parameters regarding the desired or achievable accuracy in the UAV -based photogrammetric mine surveying. Based on different case studies for applications in mining in particular, the redundancy (overlap) and the ground resolution of the images, as well as the camera network configuration, the calibration of the camera and the type and quality of the scaling or georegistration are investigated.