Abstract
Georeferencing of aerial images from small unmanned aerial systems (sUASs) is often achieved using (1) an abundant number of ground control points (GCPs), or (2) global navigation satellite system (GNSS) postprocessed kinematic (PPK) georeferencing, which utilizes accurate positioning for captured images and waives the requirement of having GCPs. In addition, GCPs allow for camera self-calibration when accurate camera calibration is not available in advance. This study assesses the impact of GCP number (and their separation distance) on elevation accuracy of sUAS surveys and examines their impact on georeferencing and camera self-calibration. In addition, this study assesses how GNSS-kinematic positioning can enhance georeferencing and camera self-calibration, and reduce the number of required GCPs. sUAS data were collected at the Pennsylvania State University Wilkes-Barre campus and were compared with reference elevation information derived from terrestrial laser scanning and checkpoints collected using total station observations. Two flights with GNSS-kinematic capability at different altitudes were used, namely, flying altitudes of 90 and 50 m (3.8- and 2.2-cm average point spacing, respectively). Scenarios with varying number of GCPs were tested to identify the cases that yield poor elevation accuracy. Based on the scenarios and data of this study, in the GCP-only case, at least 12 GCPs (65-m distance separation) are needed to achieve reliable georeferencing and camera self-calibration for this study area and data. This leads to an elevation accuracy at the centimeter level (1–2 cm). However, in the GNSS-assisted case, the required number of GCPs drops to six (105-m separation distance) in order to achieve the same accuracy level as the GCP-only case. Results and conclusions of this study can aid practitioners in sUAS survey planning.
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Acknowledgments
Purchase of the Aibotix sUAS was funded by the Academic Affairs Office of the Pennsylvania State University, Wilkes-Barre Campus, and a Research Development Grant from the Office of Engineering Technology and Commonwealth Engineering (ETCE) of Pennsylvania State University. Agisoft PhotoScan Professional was purchased with a research allocation from Research in Undergraduate Education of the Office of Undergraduate Education of Pennsylvania State University. Purchase of the Aibotix sUAS and computer hardware was funded by the Academic Affairs Office of Pennsylvania State University, Wilkes-Barre Campus. The author would like to thank Mr. Frank Lenik and Mr. Bruce Marquis from Leica Geosystems for providing the laser scanner ScanStation P40. Thanks go to students Matthew Boyes, Wyatt McMarlin, and Aaron Martinez for participating in the TLS and sUAS data acquisition. In addition, Mr. Timothy Sichler is acknowledged for his aid in flying the sUAS. Furthermore, the author would like to acknowledge the three anonymous reviewers who contributed in improving this manuscript with their valuable comments and suggestions.
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© 2019 American Society of Civil Engineers.
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Received: Jun 11, 2018
Accepted: Jan 17, 2019
Published online: Jun 12, 2019
Published in print: Aug 1, 2019
Discussion open until: Nov 12, 2019
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