Abstract
Ground control points (GCPs) are used in the process of indirectly georeferencing Unmanned Aerial Systems (UAS) images. A minimum of three ground control points (GCPs) is required but increasing the number of GCPs will lead to higher accuracy of the final results. The aim of this study is to provide the answer to the question of how many ground control points are necessary in order to derive high precision results. To obtain the results, an area of about 1 ha was photographed with a low-cost UAS, namely, the DJI Phantom 3 Standard at two different heights, 28 m and 35 m above ground, the camera being oriented in a nadiral position, and 50 ground control points were measured using a total station. In the first and the second scenario, the UAS images were processed using the Pix4D Mapper Pro software and 3DF Zephyr, respectively, by performing a full bundle adjustment process with the number being gradually increased from three GCPs to 40. The third test was made with 3DF Zephyr Pro software using a free-network approach in the bundle adjustment. Also, the point clouds and the mesh surfaces derived automatically after using the minimum and the optimum number of GCPs, respectively, were compared with a terrestrial laser scanner (TLS) point cloud. The results expressed a clear overview of the number of GCPs needed for the indirect georeferencing process with minimum influence on the final results.
Highlights
Multiple photogrammetry applications are based on Unmanned Aerial Systems (UAS) due to cost efficient data acquisition and high spatio-temporal resolution imagery
The main aim of this study is to determine the optimum number of ground control points in order to georeference a block of nadiral UAS images taken at two heights, in different scenarios and using two different software i.e., Pix4D Mapper software and 3DF Zephyr Pro software and to assess the accuracy of the final products i.e., dense point cloud and mesh surface by comparing the results with terrestrial laser scanner (TLS) point cloud and total station measurements, for three cases: using 3 GCPs and the determined optimum number of GCPs
As shown by the results presented in Appendix A, the sub-decimetre error is obtained with 14 GCPs, and the optimum number of GCPs for georeferencing the nadiral UAV images is 20, as from this point the error varies in the range of 1 cm until reaching 36 GCPs, where the root mean square error (RMSE) is 2.6 cm
Summary
Multiple photogrammetry applications are based on Unmanned Aerial Systems (UAS) due to cost efficient data acquisition and high spatio-temporal resolution imagery. Used in various fields like land surveying and construction, ground control points (GCPs) can greatly increase the accuracy of the 3D information and their measurement is an important aspect of georeferencing the UAS image blocks. Ground control points are used in the process of indirect georeferencing the UAS images, a minimum of three ground control points being required, increasing the number of GCPs will lead to higher accuracy of the final results i.e., point cloud, 3D mesh, orthomosaic or Proceedings 2018, 2, 352, doi:10.3390/ecrs-2-05165 www.mdpi.com/journal/proceedings. The accuracy of the final products derived from UAS images is influenced by different factors, such as: camera’s focal length, flight altitude, camera orientation, image quality, processing software, type of UAS system (fixed wind or rotary wind), and the precision with which targets can be measured and matched [1,8]. Each study contributes to the improvement in the product obtained by UAS technology
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