One of the challenges faced by surveyors in acquisition of accurate spatial data for mining applications is the risk involved in acquiring data in rugged terrains and difficult or inaccessible areas. With the advent of modern technology, accurate geospatial data can now be safely obtained for proper mining documentation periodically. The use of Unmanned Aerial Vehicles (UAVs) for data acquisition in mine surveying has been a viable means of obtaining reliable geospatial data rapidly and efficiently. The main goal of this study is to develop a semi-automatic UAV-based system for the acquisition of spatial data required for the estimation of the volume of earthworks. A DJI Phantom 4 quadcopter was used for the acquisition of image data of the project site, while the images were processed into a Digital Elevation Model (DEM) using Pix4Dmapper v2.0.1, which was then imported into the MATLAB-based system developed for the automatic estimation of the volume of earthworks. The volume obtained from the automated system was thus compared with the volume obtained directly from the Pix4Dmapper software, having specified a contour interval of 1 and an allowable error rate of ±3% as the standard error. While ±1.02% error was observed in the volume estimated using the Pix4Dmapper, the developed automated system yielded an estimated precision of ±0.81% in its volume estimation, which proves to be more robust for automatic volume estimation in terms of accuracy and precision.
Dams are built to store the water flowing from upstream to downstream. Sedimentation and siltation are some of the major problems affecting the storage capacity of dams. For effective management, bathymetric and topographic data are used to assess this challenge. In the Mambila Plateau of Taraba, Nigeria, the Tunga Dam is a multifunctional reservoir that serves as a small hydropower, irrigation and domestic use dam. Nonetheless, it is not operating to its full potential, leading to issues such as frequent stoppage of the turbine, low irrigation activities and a shortage of water supply for domestic use. To determine the basin’s approximate present volume, a topographic and bathymetric survey was conducted using a differential global positioning system (DGPS)-Hi-Target V30 and a single beam echosounder to acquire the real-time data. The data were processed, and the digital elevation model (DEM) of the study area was modelled using a triangulation irregular network algorithm (TIN). The deepest point of the dam was found to be 21.25 m, and the volumetric capacity was assessed based on the elevations. The tessellation data format adequately represents the reservoir DEM for future purposes to better enhance the reservoir capacity. Hence, the research suggested that dredging should be carried out to boost the basin’s capacity. Likewise, an embankment can be constructed around the dam to enhance the basin’s storage capacity. The dredged material can be used to achieve the barrier’s building, which will reduce the overall cost.
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