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.
Get full access to this article
View all available purchase options and get full access to this article.
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.
References
Agisoft. 2018. Agisoft PhotoScan User Manual, Professional Edition, Version 1.4. Accessed June 10, 2018. https://www.agisoft.com/pdf/photoscan-pro_1_4_en.pdf.
Agüera-Vega, F., F. Carvajal-Ramírez, and P. Martínez-Carricondo. 2017a. “Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry.” J. Surv. Eng. 143 (2): 04016025. https://doi.org/10.1061/(ASCE)SU.1943-5428.0000206.
Agüera-Vega, F., F. Carvajal-Ramírez, and P. Martínez-Carricondo. 2017b. “Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle.” Measurement 98 (Feb): 221–227. https://doi.org/10.1016/j.measurement.2016.12.002.
Besl, P. J., and N. D. McKay. 1992. “A method for registration of 3-D shapes.” IEEE Trans. Pattern Anal. Mach. Intell. 14 (2): 239–256. https://doi.org/10.1109/34.121791.
Bolkas, D., Sichler T. J., and McMarlin W. 2019. “A case study on the accuracy assessment of a small UAS photogrammetric survey using terrestrial laser scanning.” Surv. Land Inf. Sci. 78 (1): 31–44.
Brown, D. C. 1966. “Decentering distortion of lenses.” Photogram. Eng. Remote Sens. 32 (3): 444–462.
Carrivick, J. L., M. W. Smith, and D. J. Quincey. 2016. Structure from motion in the geosciences. Oxford, UK: Wiley.
Clapuyt, F., V. Vanacker, and K. Van Oost. 2016. “Reproducibility of UAV-based earth topography reconstructions based on structure-from-motion algorithms.” Geomorphology 260 (May): 4–15. https://doi.org/10.1016/j.geomorph.2015.05.011.
Colomina, I., and P. Molina. 2014. “Unmanned aerial systems for photogrammetry and remote sensing: a review.” ISPRS J. Photogramm. Remote Sens. 92 (Jun): 79–97. https://doi.org/10.1016/j.isprsjprs.2014.02.013.
Deakin, R. E., and D. G. Kildea. 1999. “A note on standard deviation and RMS.” Aust. Surv. 44 (1): 74–79. https://doi.org/10.1080/00050351.1999.10558776.
Eltner, A., A. Kaiser, C. Castillo, G. Rock, F. Neugirg, and A. Abellán. 2016. “Image-based surface reconstruction in geomorphometry—Merits, limits and developments.” Earth Surf. Dynam. 4 (2): 359–389. https://doi.org/10.5194/esurf-4-359-2016.
Forlani, G., E. Dall'Asta, F. Diotri, U. Md Cella, R. Roncella, and M. Santise. 2018. “Quality assessment of DSMs produced from UAV flights georeferenced with on-board RTK positioning.” Remote Sens. 10 (2): 311. https://doi.org/10.3390/rs10020311.
Gabrlik, P., Al Cour-Harbo, P. Kalvodova, L. Zalud, and P. Janata. 2018. “Calibration and accuracy assessment in a direct georeferencing system for UAS photogrammetry.” Int. J. Remote Sens. 39 (15–16): 4931–4959. https://doi.org/10.1080/01431161.2018.1434331.
Galarreta, J. F., N. Kerle, and M. Gerke. 2015. “UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning.” Nat. Hazards Earth Syst. 15 (6): 1087–1101. https://doi.org/10.5194/nhess-15-1087-2015.
Gindraux, S., R. Boesch, and D. Farinotti. 2017. “Accuracy assessment of digital surface models from unmanned aerial vehicles’ imagery on glaciers.” Remote Sens. 9 (2): 186. https://doi.org/10.3390/rs9020186.
Gneeniss, A. S., J. P. Mills, and P. E. Miller. 2015. “In-flight photogrammetric camera calibration and validation via complementary lidar.” ISPRS J. Photogramm. Remote Sens. 100 (Feb): 3–13. https://doi.org/10.1016/j.isprsjprs.2014.04.019.
Harwin, S., and A. Lucieer. 2012. “Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (UAV) imagery.” Remote Sens. 4 (6): 1573–1599. https://doi.org/10.3390/rs4061573.
Harwin, S., A. Lucieer, and J. Osborn. 2015. “The impact of the calibration method on the accuracy of point clouds derived using unmanned aerial vehicle multi-view stereopsis.” Remote Sens. 7 (9): 11933–11953. https://doi.org/10.3390/rs70911933.
Hugenholtz, C., O. Brown, J. Walker, T. Barchyn, P. Nesbit, M. Kucharczyk, and S. Myshak. 2016. “Spatial accuracy of UAV-derived orthoimagery and topography: Comparing photogrammetric models processed with direct geo-referencing and ground control points.” Geomatica 70 (1): 21–30. https://doi.org/10.5623/cig2016-102.
James, M. R., S. Robson, S. d'Oleire-Oltmanns, and U. Niethammer. 2017. “Optimising UAV topographic surveys processed with structure-from-motion: Ground control quality, quantity and bundle adjustment.” Geomorphology 280 (Mar): 51–66. https://doi.org/10.1016/j.geomorph.2016.11.021.
Klingbeil, L., C. Eling, E. Heinz, M. Wieland, and H. Kuhlmann. 2017. “Direct georeferencing for portable mapping systems: In the air and on the ground.” J. Surv. Eng. 143 (4): 04017010. https://doi.org/10.1061/(ASCE)SU.1943-5428.0000229.
Lato, M. J., G. Bevan, and M. Fergusson. 2012. “Gigapixel imaging and photogrammetry: Development of a new long range remote imaging technique.” Remote Sens. 4 (10): 3006–3021. https://doi.org/10.3390/rs4103006.
Lato, M. J., D. J. Hutchinson, D. Gauthier, T. Edwards, and M. Ondercin. 2014. “Comparison of airborne laser scanning, terrestrial laser scanning, and terrestrial photogrammetry for mapping differential slope change in mountainous terrain.” Can. Geotech. J. 52 (2): 129–140. https://doi.org/10.1139/cgj-2014-0051.
Liu, P., A. Y. Chen, Y. N. Huang, J. Y. Han, J. S. Lai, S. C. Kang, T. Wu, M. Wen, and M. Tsai. 2014. “A review of rotorcraft unmanned aerial vehicle (UAV) developments and applications in civil engineering.” Smart Struct. Syst. 13 (6): 1065–1094. https://doi.org/10.12989/sss.2014.13.6.1065.
Nex, F., and F. Remondino. 2014. “UAV for 3D mapping applications: a review.” Appl. Geom. 6 (1): 1–15. https://doi.org/10.1007/s12518-013-0120-x.
NGS (National Geodetic Survey). 2012. “GEOID12B.” Accessed June 10, 2018. https://www.ngs.noaa.gov/GEOID/GEOID12B/.
Niethammer, U., M. R. James, S. Rothmund, J. Travelletti, and M. Joswig. 2012. “UAV-based remote sensing of the Super-Sauze landslide: Evaluation and results.” Eng. Geol. 128 (Mar): 2–11. https://doi.org/10.1016/j.enggeo.2011.03.012.
Rusnák, M., J. Sládek, J. Buša, and V. Greif. 2016. “Suitability of digital elevation models generated by UAV photogrammetry for slope stability assessment (Case study of landslide in Svätý Anton, Slovakia).” Acta Sci. Pol. Formatio Circumiectus 15 (4): 439–450.
Shahbazi, M., G. Sohn, J. Théau, and P. Menard. 2015. “Development and evaluation of a UAV-photogrammetry system for precise 3D environmental modeling.” Sensors 15 (11): 27493–27524. https://doi.org/10.3390/s151127493.
Siebert, S., and J. Teizer. 2014. “Mobile 3D mapping for surveying earthwork projects using an unmanned aerial vehicle (UAV) system.” Autom. Constr. 41 (May): 1–14. https://doi.org/10.1016/j.autcon.2014.01.004.
Tang, R., and D. Fritsch. 2013. “Correlation analysis of camera self-calibration in close range photogrammetry.” Photogramm. Rec. 28 (141): 86–95. https://doi.org/10.1111/phor.12009.
Tonkin, T. N., and N. G. Midgley. 2016. “Ground-control networks for image based surface reconstruction: An investigation of optimum survey designs using UAV derived imagery and structure-from-motion photogrammetry.” Remote Sens. 8 (9): 786. https://doi.org/10.3390/rs8090786.
Toth, C., G. Jozkow, and D. Grejner-Brzezinska. 2015. “Mapping with small UAS: A point cloud accuracy assessment.” J. Appl. Geod. 9 (4): 213–226. https://doi.org/10.1515/jag-2015-0017.
Turner, D., A. Lucieer, and L. Wallace. 2014. “Direct georeferencing of ultrahigh-resolution UAV imagery.” IEEE Trans. Geosci. Remote Sens. 52 (5): 2738–2745. https://doi.org/10.1109/TGRS.2013.2265295.
Vautherin, J., S. Rutishauser,K. Schneider-Zapp, H. F. Choi, V. Chovancova, A. Glass, and C. Strecha. 2016. “Photogrammetric accuracy and modeling of rolling shutter cameras.” In Proc., ISPRS Ann. Photogramm. Remote Sens. Spat. Inform. Sci., 139–146. Göttingen, Germany: Copernicus.
Information & Authors
Information
Published In
Journal of Surveying Engineering
Volume 145 • Issue 3 • August 2019
Copyright
© 2019 American Society of Civil Engineers.
History
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
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.