Analysis of the residual distortion and forward motion influence on the accuracy of spatial coordinates determination based on UAV survey

Lviv Polytechnic National University
Lviv Polytechnic National University
Engineering geodesy department of Lviv Polytechnic National University

The purpose of this work is to study the operation of a non-metric digital camera Canon EOS 5D Mark III installed on a DJI S1000 octocopter, regarding the accuracy of spatial coordinates determination on images, and perform the identification and analysis of errors affecting the accuracy of stereophotogrammetry survey. During the experimental part, we conducted the stereophotogrammetric and aerial surveys of the areas including marked points. This served as a source of data for creating stereo models with their subsequent processing with the use of the Delta 2 software. The catalogs of spatial coordinates of the marked points were formed according to measurements taken by the Trimble M3 DR Total Station and from stereo models. We calculated the differences and defined root-mean-square error of determining the spatial coordinates of the points on images. Considering the specifics of the marked points placement on the studied sites, we also calculated the errors of image displacements caused by terrain. Additionally, the research studied the influence of camera`s forward motion on the accuracy of survey data of unmanned aerial vehicle (UAV). The obtained results confirm the presence of residual distortion in the optical system of the Canon EOS 5D Mark III digital camera. This leads to the need to calibrate the camera for improving the accuracy of the obtained images for their further use in mapping, monitoring geomorphological processes and phenomena, creating a Digital Elevation Model, etc. Also, the study revealed the influence of forward motion of the survey camera and image displacements caused by the height difference of the survey sites on the accuracy of created stereo models. The authors proposed a configuration and created an experimental site of marked control points on the ground for calibrating a digital non-metric camera in conditions as close as possible to the real survey conditions. Considering the analyzed literary sources, it is more effective than calibration in a laboratory.

  1. Ai, M., Hu, Q., Li, J., Wang, M., Yuan, H., & Wang, S. (2015). A Robust Photogrammetric Processing Method of Low-Altitude UAV Images. Remote Sensing. 2015. 7(3), 2302–2333.
  2. Burshtynska, Kh. (1999). Aerophotography. LAHT. (in Ukranian)
  3. Hlotov, V., Tserklevych, A., Zbruckij, O., Kolisnichenko, V., Prokhorchuk, A., Karnaushenko, R., & Galecky, V. (2014). Analysis and perspectives aeroshooting process with unpiloted aircraft. Modern Achievements of a Geodetic Science and Industry, 1(27), 131-136. (in Ukranian).
  4. Hlotov, V., Hunina, A., & Protsyk M. (2020). A complex method of determining the elements of internal orientation of digital cameras. Modern Achievements of a Geodetic Science and Industry. 2020. 1, 110-117. (in Ukranian)
  5. Ivanov, V. L., Ruhain, O. V., & Cheked, I. V. (2004). Aviatsiine obladnannia viiskovykh litalnykh aparativ. NAU. file:///C:/Users/%D0%93%D0%B0%D0%BB%D0%B8%D0%BD%D0%B0/Downloads/%D0%90%D0%9E%D0%92%D0%9B%D0%90-%D1%87-1.pdf (in Ukranian)
  6. Cramer, M., Przybilla, H. J., & Zurhorst, A. (2017). UAV cameras: Overview and geometric calibration benchmark. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives. 2017. 42(2W6), 85–92.
  7. Gerke, M., & Przybilla, H. J. (2016). Accuracy analysis of photogrammetric UAV image blocks: Influence of onboard RTK-GNSS and cross flight patterns. Photogrammetrie, Fernerkundung, Geoinformation. 2016. (1), 17–30.
  8. Griffiths, D., & Burningham, H. (2019). Comparison of pre-and self-calibrated camera calibration models for UAS-derived nadir imagery for a SfM application. Progress in Physical Geography, 43(2), 215–235.
  9. Mohsan, S. A. H., Khan, M. A., Noor, F., Ullah, I., & Alsharif, M. H. (2022). Towards the Unmanned Aerial Vehicles (UAVs): A Comprehensive Review. Drones. 2022. 6(6),147.
  10. Niemeyer, F. (2015). Konzept und prototypische Umsetzung eines „Four Vision“-Kamerasystems mit Anwendungen in kommunalen und landwirtschaftlichen Bereichen für den Einsatz auf UAVs (Unmanned Aerial Vehicle) [Doctoral thesis]. The university of Rostock.
  11. ResearchGate. (n.d.). ResearchGate. Retrieved May 9, 2023, from
  12. Schultz, R., Voytenko, S., Krelshteinn, P., & Malina, I. (2015). The issue of calculating points positioning accuracy for aerial photographs from unmanned aerial vehicles. KNUBA. 2015. (62). 124-136. (in Ukranian)
  13. Vovk, A., Hlotov, V., Gunina, A., Malitskyy, A., Tretyak, K., & Tserklevych, A. (2015). Analysis of the results of the use UAV TRIMBLE UX-5 for creation of orthophotomaps and digital model of relief. Geodesy, Cartography and Aerial Photography. 2015. (81), 90-103. (in Ukranian)