Evaluation of UAS Flight Configuration Factors and Their Impacts on Photogrammetric Survey Accuracy
Publication: Construction Research Congress 2022
ABSTRACT
Recent advances in computer vision and camera-equipped unmanned aerial systems (UASs) for 3D modeling enabled UAS-based surveys with high spatial–temporal resolutions. Although there have been many studies on various factors that affect the accuracy of UAS-based photogrammetry-based geospatial data, there is little to no quantitative method that identifies the relationships between flight configuration factors and point cloud accuracy. This paper seeks to assess the degrees of influences that these factors affect accuracy. This study assesses five impact factors using the ANOVA method to understand which factors have higher or lower impacts on the accuracy. The influence factors include flight height, average image quality, image overlap, ground control point (GCP) quantities, and focal lengths of cameras. The results show that the number of GCPs has the largest impact on the vertical and horizontal accuracies than other impact factors. The findings of this study can help surveyors better design flight configurations given different site conditions and constraints.
Get full access to this article
View all available purchase options and get full access to this chapter.
REFERENCES
Agüera-Vega, F., Carvajal-Ramírez, F., and Martínez-Carricondo, P. 2017. Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement, 98, pp.221–227.
Agüera-Vega, F., Carvajal-Ramírez, F., and Martínez-Carricondo, P. 2017. Accuracy of digital surface models and orthophotos derived from unmanned aerial Vehicle photogrammetry. Journal of Surveying Engineering, 143(2), p.04016025.
Benjamin, A., O’Brien, D., Barnes, G., Wilkinson, B., and Volkmann, W. 2020. Improving data acquisition efficiency: systematic accuracy evaluation of GNSS-assisted aerial triangulation in UAS operations. Journal of Surveying Engineering, 146(1), p.05019006.
Casella, E., Rovere, A., Pedroncini, A., Stark, C., Casella, M., Ferrari, M., and Firpo, M. 2016. Drones as tools for monitoring beach topography changes in the Ligurian Sea (NW Mediterranean). Geo-Marine Letters, 36(2), pp.151–163.
Gabrlik, P., Cour-Harbo, A., Kalvodova, P., Zalud, L., and Janata, P. 2018. Calibration and accuracy assessment in a direct georeferencing system for UAS photogrammetry. International Journal of Remote Sensing, 39(15-16), pp.4931–4959.
Griffiths, D., and Burningham, H. 2018. Comparison of pre- and self-calibrated camera calibration models for UAS-derived nadir imagery for a SfM application. Progress in Physical Geography: Earth and Environment, 43(2), pp.215–235.
Harwin, S., and Lucieer, A. 2012. Assessing the accuracy of georeferenced point clouds produced via multi-view stereopsis from unmanned aerial vehicle (UAV) imagery. Remote Sensing, 4(6), pp.1573–1599.
Hubbard, B., and Hubbard, S. 2020. Unmanned aircraft systems (UAS) for bridge inspection safety. Drones, 4(3), p.40.
Khan, N., Jhanjhi, N., Brohi, S., Usmani, R., and Nayyar, A. 2020. Smart traffic monitoring system using Unmanned Aerial Vehicles (UAVs). Computer Communications, 157, pp.434–443.
Kielhauser, C., Renteria Manzano, R., Hoffman, J., and Adey, B. 2020. Automated construction progress and quality monitoring for commercial buildings with unmanned aerial systems: an application study from Switzerland. Infrastructures, 5(11), p.98.
Martínez-Carricondo, P., Agüera-Vega, F., Carvajal-Ramírez, F., Mesas-Carrascosa, F., García-Ferrer, A., and Pérez-Porras, F. 2018. Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points. International Journal of Applied Earth Observation and Geoinformation, 72, pp.1–10.
McEvoy, J., Hall, G., and McDonald, P. 2016. Evaluation of unmanned aerial vehicle shape, flight path and camera type for waterfowl surveys: disturbance effects and species recognition. PeerJ, 4, p.e1831.
Mesas-Carrascosa, F., Notario García, M., Meroño de Larriva, J., and García-Ferrer, A. 2016. An analysis of the influence of flight parameters in the generation of unmanned aerial vehicle (UAV) orthomosaicks to survey archaeological areas. Sensors, 16(11), p.1838.
Messinger, M., Asner, G., and Silman, M. 2016. Rapid assessments of amazon forest structure and biomass using small unmanned aerial systems. Remote Sensing, 8(8), p.615.
Photogrammetric Engineering & Remote Sensing. (2015). ASPRS positional accuracy standards for digital geospatial data. Photogrammetric Engineering & Remote Sensing, doi: https://doi.org/10.14358/PERS.81.3.A1-A26.
Sankaran, S., Khot, L., Espinoza, C., Jarolmasjed, S., Sathuvalli, V., Vandemark, G., Miklas, P., Carter, A., Pumphrey, M., Knowles, N., and Pavek, M. 2015. Low-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: A review. European Journal of Agronomy, 70, pp.112–123.
Sanz-Ablanedo, E., Chandler, J., Rodríguez-Pérez, J., and Ordóñez, C. 2018. Accuracy of unmanned aerial vehicle (UAV) and SfM photogrammetry survey as a function of the number and location of ground control points used. Remote Sensing, 10(10), p.1606.
Seifert, E., Seifert, S., Vogt, H., Drew, D., van Aardt, J., Kunneke, A., and Seifert, T. 2019. Influence of drone altitude, image overlap, and optical sensor resolution on multi-view reconstruction of forest images. Remote Sensing, 11(10), p.1252.
Wang, X., Chen, J., and Dadi, G. 2019. Factors influencing measurement accuracy of unmanned aerial systems (UAS) and photogrammetry in construction earthwork. In: ASCE International Conference on Computing in Civil Engineering 2019. ASCE, pp.408–414.
Zimmerman, T., Jansen, K., and Miller, J. 2020. Analysis of UAS flight altitude and ground control point parameters on DEM accuracy along a complex, developed coastline. Remote Sensing, 12(14), p.2305.
Information & Authors
Information
Published In
History
Published online: Mar 7, 2022
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.