Measurement Accuracy Assessment in 3D Models Derived from Drone Surveys

Engineering Surveying & Deformation Monitoring

Authors

First and Last Name Academic degree E-mail Affiliation
Sonia Calluso No sonia.calluso [at] outlook.it Freelance External Collaborator DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy)
Reggio Calabria, Italy
Giuseppe Maria Meduri No ing.giuseppemariameduri [at] gmail.com DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy)
Reggio Calabria, Italy
Vincenzo Gullace No gllvcn77a15h558w [at] studenti.unirc.it DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy)
Reggio Calabria, Italy
Maurizio Manti No ing.manti5 [at] gmail.com Freelance External Collaborator DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy)
Reggio Calabria, Italy
Emanuela Genovese No emanuela.genovese [at] unirc.it DICEAM - Department of Civil, Energy, Environment and Materials Engineering - Mediterranea University of Reggio Calabria (Italy)
Reggio Calabria, Italy

I and my co-authors (if any) authorize the use of the Paper in accordance with the Creative Commons CC BY license

First published on this website: 27.08.2023 - 12:30
Abstract 

Unmanned Aerial Vehicle (UAV) systems, or drones, have gained prominence in surveying due to their efficiency and accessibility advantages. Employed with computer vision algorithms, they reconstruct accurate 3D models, transforming data acquisition. Although commonplace for inspections, monitoring, and controls, their use in infrastructure measurements remains limited. This study addresses this gap, focusing on accuracy assessment. Assessing accuracy requires considering parameters during both survey and processing phases. This research aims to predict the accuracy of 3D reconstruction from UAV surveys using commercial software (Agisoft Metashape). By analyzing key parameters, we establish a relationship to anticipate survey accuracy based on predefined choices. This study advances UAV-based infrastructure measurement accuracy, offering insights for better decision-making and precision in the field.

References 

Barrile, V., Bernardo, E., Candela, G., Bilotta , G., Modafferi, A., & Fotia, A. (2020a). Road infrastructure heritage: From scan to infrabim. WSEAS Transaction on Environment and Development, 16, 633-642.

 

Barrile, V., Bilotta, G., & Nunnari, A. (2017). 3D modeling with photogrammetry by UAVs and model quality verification. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 4, 129-134.

 

Barrile, V., Bilotta, G., Fotia , A., & Bernardo, E. (2020b). Road extraction for emergencies from satellite imagery. Computational Science and Its Applications - ICCSA 2020: 20th International Conference (p. 767-781). Cagliari, Italy: Springer International Publishing .

 

Barrile, V., Fotia, A., Bernardo, E., Bilotta, G., & Modafferi, A. (2020c). Road infrastructure monitoring: an experimental geomatic integrated system. Computational Science and Its Applications - ICCSA 2020: 20th Intenrational Conference (p. 634-648). Cagliari, Italy: Springer International Publishing.

 

Barrile, V., Fotia, A., Leonardi, G., & Pucinotti, R. (2020d). Geomatics and soft computing techniques for infrastructural monitoring. Sustainability, 12(4), 1606.

 

Barrile, V., Gelsomino, V., & Bilotta, G. (2017). UAV and computer vision in 3D modeling of cultural heritage in southern Italy. IOP Conference Series: Materials science and engineering. 225, No. 1, p. 012196. IOP Publishing.

 

Goncalves, J. A., & Henriques, R. (2015). UAV photogrammetry for topographic monitoring of coastal areas. ISPRS Journal of Photogrammetry and Remote Sensing , 104, 101-111.

 

Lan, J. K., & Lee, F. K. (2022). Drone Forensics: A Case Study on Dji Mavic Air 2. 2022 24th International Conference on Advanced Communication Technology (ICACT) (p. 291-296). IEEE.

 

Leonardi, G., Barrile, V., Palamara, R., Suraci, F., & Candela, G. (2019). 3D mapping of pavement distresses using an Unamanned Aerial Vehicle (UAV) system. New Metropolitan Perspectives: Local Knowledge and Innovation Dynamics Towards Territory Attractiveness Through the Implementation of Horizon/E2020/Agenda2030. 2, p. 164-171. Springer International Publishing.

 

Pricope, N. G., Mapes, K. L., Woodward, K. D., Olsen, S. F., & Baxley, J. B. (2019). Multi-sensor assessment of the effects of varying processing parameters on UAS product accuracy and quality. Drones, 3(3), 63.

 

Sankarasrinivasan, S., Balasubramanian, E., Karthik, K., Chandrasekar, U., & Gupta, R. (2015). Health monitoring of civil structures with integrated UAV and image processing system. Procedia Computer Science, 54, 508-515.