Lightweight Unmanned Aerial Vehicle (UAV) for 3D topographic mapping in mining industry has been raised significantly in recent years. Especially, in complex terrains such as in open-pit mines in which the elevation is rapidly undulating, UAV-based mapping has proven its economical efficiency and higher safety compared to the conventional methods. However, one of the most important factors in UAV mapping of complex terrain is the flight altitude, which needs to be considered seriously because of the safety and accuracy of generated DEMs. This paper aims to evaluate the influence of the flight height on the accuracy of DEMs generated in open-pit mines. To this end, the study area is selected in a quarry with a complex terrain, which is located in northern Vietnam. The investigation was conducted with five flight heights of 50 m, 100 m, 150 m, 200 m, and 250 m. To assess the accuracy of resulting DEMs, ten ground control points (GCPs), and 385 checkpoints measured by both GNSS/RTK and total station methods were used. The accuracy of DEM was assessed by root-mean-square error (RMSE) in X, Y, Z, XY, and XYZ components. The results show that DEM models generated at the flight heights of less than 150 m have high accuracy. RMSEs of the 10 GCPs increase from 1.8 cm to 6.2 cm for the vertical (Z), and from 2.6 cm to 6.3 cm for the horizontal (XY), whereas RMSE of 385 checkpoints increase gradually from 0.05 m to 0.15 m for the vertical (Z) when the flight height increases from 50 m to 250 m.

Image data from Drones/Unmanned Aerial Vehicles (UAVs) has been studied and used extensively for establishing maps. The process of UAV data provides three main products including (Digital Surface Model) DSM, Point cloud and Ortho-photos, in which point cloud is a valuable data source in building 3D models and topographic surfaces as well. However, processing point cloud separately to achieve secondary products has not been received much attention from researchers. This study determines parameters to develop a method for classifying point cloud data constructed from UAV images. Consequently, A 3D surface of the ground is built by applying a developed algorithm for the point cloud data for an open-pit mine. The temporal or non-ground objects such as trees, houses, vehicles are automatically subtracted from the point cloud by the algorithms.  According to this line, it is possible to calculate and analyze the amount of reserves, the exploited volume to evaluate the efficiency for each mine during operation with the support of UAV integrated camera.