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Investigating the length, area and volume measurement accuracy of UAV-Based oblique photogrammetry models produced with and without ground control points

Yıl 2023, Cilt: 8 Sayı: 1, 32 - 51, 15.02.2023
https://doi.org/10.26833/ijeg.1017176

Öz

This study aimed to investigate the performance and sensitivity of 3D photogrammetric models generated without GCPs (ground control points). To determine whether the models with no GCPs retained accuracy in all terrain types as well as under varying climate or meteorological conditions, two separate studies were conducted in two areas with different characteristics (elevation, slope, topography, and meteorological differences). The study areas were initially modelled with GCPs and were later modelled without GCPs. Furthermore, some of the dimensions and areas within the modelled regions were measured using terrestrial techniques (with GPS/GNSS) for accuracy analyses. After regional modelling was conducted with and without GCPs, different territories with different slopes and geometric shapes were selected. Various length, area and volume measurements were carried out over the selected territories using both models (generated with and without GCPs). The datasets obtained from the measurement results were compared, and the measurements obtained using the models produced with GCPs were accepted as the true values. The length measurement results provided various levels of success. The first study area exhibited very promising length measurement results, with a relative error less than 1% and an RMSE (root mean square error) of 0.139 m. In the case of the area measurements, in the first study area (Sivas), a minimum relative error of 0.04% and a maximum relative error of 1.05% with an RMSE of 1.264 m² were obtained. In the second study areas (Artvin), a minimum relative error of 0.56% and a maximum relative error of 5.27% with an RMSE of 1.76 m² were achieved. Finally, in the case of the volume measurements, for the first study area (Sivas), a minimum relative error of 0.8% and a maximum relative error of 6.8% as well as an RMSE of 2.301 m³ were calculated. For the second study area (Artvin), the minimum relative error of the volume measurements was 0.502%, and the maximum relative error was 2.01%, with an RMSE of 7.061 m³.

Kaynakça

  • Yastikli, N. (2007). Documentation of cultural heritage using digital photogrammetry and laser scanning. Journal of Cultural heritage, 8(4), 423-427.
  • McCarthy, J. (2014). Multi-image photogrammetry as a practical tool for cultural heritage survey and community engagement. Journal of Archaeological Science, 43, 175-185.
  • Berni, J. A., Zarco-Tejada, P. J., Suárez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on geoscience and Remote Sensing, 47(3), 722-738.
  • Xiang, H., & Tian, L. (2011). Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV). Biosystems engineering, 108(2), 174-190.
  • Jauregui, L. M., & Jauregui, M. (2000). Terrestrial photogrammetry applied to architectural restoration and archaeological surveys. International Archives of Photogrammetry and Remote Sensing, 33(B5/1; PART 5), 401-405.
  • Bianchi, G., Bruno, N., Dall'Asta, E., Forlani, G., Re, C., Roncella, R., ... & Zerbi, A. (2016). Integrated survey for archıtectural restoratıon: A methodologıcal comparıson of two case studıes. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 41, 175-182.
  • Kucukkaya, A. G. (2004). Photogrammetry and remote sensing in archeology. Journal of Quantitative Spectroscopy and Radiative Transfer, 88(1-3), 83-88.
  • Guidi, G., Russo, M., Ercoli, S., Remondino, F., Rizzi, A., & Menna, F. (2009). A multi-resolution methodology for the 3D modeling of large and complex archeological areas. International Journal of Architectural Computing, 7(1), 39-55.
  • Patikova, A. (2004) Digital photogrammetry in the practice of open pit mining. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 34, 1-4.
  • Sheng, Y. H., Yan, Z. G., & Song, J. L. (2003). Monitoring technique for mining subsidence with digital terrestrial photogrammetry. Journal of China University of Mining & Technology, 32(4), 411-415.
  • Murfitt, S. L., Allan, B. M., Bellgrove, A., Rattray, A., Young, M. A., & Ierodiaconou, D. (2017). Applications of unmanned aerial vehicles in intertidal reef monitoring. Scientific reports, 7(1), 1-11.
  • Yalcin, G., & Selcuk, O. (2015). 3D city modelling with Oblique Photogrammetry Method. Procedia Technology, 19, 424-431.
  • Danahy, J. (1997). A set of visualization data needs in urban environmental planning & design for photogrammetric data. In Automatic extraction of man-made objects from aerial and space images (II) (pp. 357-366). Birkhäuser, Basel.
  • Döner, F. & Bıyık, C. Management of three dimensional objects in spatial database. Chamb. Surv. Cadastre Eng. Geod. Geoinf. Mag. 100, 27 (2009).
  • Yılmaz, H. M., Mutluoglu, O., Ulvi, A., Yaman, A., & Bilgilioglu, S. S. (2018). Created Tree Dimensional Model of Aksaray University Campus with Unmanned Aerial Vehicle. Journal of Geomatics, 3(2), 103-107.
  • Choudhury, M. A. M., Costanzini, S., Despini, F., Rossi, P., Galli, A., Marcheggiani, E., & Teggi, S. (2019, May). Photogrammetry and Remote Sensing for the identification and characterization of trees in urban areas. In Journal of Physics: Conference Series (Vol. 1249, No. 1, p. 012008). IOP Publishing.
  • Wu, B., Xie, L., Hu, H., Zhu, Q., & Yau, E. (2018). Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas. ISPRS journal of photogrammetry and remote sensing, 139, 119-132.
  • Goetz, J., & Brenning, A. (2019). Quantifying uncertainties in snow depth mapping from structure from motion photogrammetry in an alpine area. Water Resources Research, 55(9), 7772-7783.
  • Chudley, T. R., Christoffersen, P., Doyle, S. H., Abellan, A., & Snooke, N. (2019). High-accuracy UAV photogrammetry of ice sheet dynamics with no ground control. The Cryosphere, 13(3), 955-968.
  • Casella, V. and Franzini, M. (2016) Modelling steep surfaces by various configurations of nadir and oblique photogrammetry. ISPRS Annals of the Photogrammetry. Remote Sensing and Spatial Information Sciences, III-1, 175-182.
  • Tomaštík, J., Mokroš, M., Surový, P., Grznárová, A., & Merganič, J. (2019). UAV RTK/PPK method—An optimal solution for mapping inaccessible forested areas?. Remote sensing, 11(6), 721.
  • He, F., Zhou, T., Xiong, W., Hasheminnasab, S. M., & Habib, A. (2018). Automated aerial triangulation for UAV-based mapping. Remote Sensing, 10(12), 1952.
  • 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 (PFG), (1), 17-30.
  • Turk, T. & Ocalan, T. (2020). Examining the Accuracy of Photogrammetric Products Obtained by Unmanned Aerial Vehicles with PPK GNSS System with Different Approaches. Turkish Journal of Photogrammetry, 2 (1), 22-28.
  • Eling, C., Klingbeil, L., & Kuhlmann, H. (2014). Development of an RTK-GPS system for precise real-time positioning of lightweight UAVs.
  • Takasu, T. (2021) RTKLIB, Open-Source Program Package for RTK-GPS. https://github.com/tomojitakasu/RTKLIB
Yıl 2023, Cilt: 8 Sayı: 1, 32 - 51, 15.02.2023
https://doi.org/10.26833/ijeg.1017176

Öz

Kaynakça

  • Yastikli, N. (2007). Documentation of cultural heritage using digital photogrammetry and laser scanning. Journal of Cultural heritage, 8(4), 423-427.
  • McCarthy, J. (2014). Multi-image photogrammetry as a practical tool for cultural heritage survey and community engagement. Journal of Archaeological Science, 43, 175-185.
  • Berni, J. A., Zarco-Tejada, P. J., Suárez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on geoscience and Remote Sensing, 47(3), 722-738.
  • Xiang, H., & Tian, L. (2011). Development of a low-cost agricultural remote sensing system based on an autonomous unmanned aerial vehicle (UAV). Biosystems engineering, 108(2), 174-190.
  • Jauregui, L. M., & Jauregui, M. (2000). Terrestrial photogrammetry applied to architectural restoration and archaeological surveys. International Archives of Photogrammetry and Remote Sensing, 33(B5/1; PART 5), 401-405.
  • Bianchi, G., Bruno, N., Dall'Asta, E., Forlani, G., Re, C., Roncella, R., ... & Zerbi, A. (2016). Integrated survey for archıtectural restoratıon: A methodologıcal comparıson of two case studıes. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 41, 175-182.
  • Kucukkaya, A. G. (2004). Photogrammetry and remote sensing in archeology. Journal of Quantitative Spectroscopy and Radiative Transfer, 88(1-3), 83-88.
  • Guidi, G., Russo, M., Ercoli, S., Remondino, F., Rizzi, A., & Menna, F. (2009). A multi-resolution methodology for the 3D modeling of large and complex archeological areas. International Journal of Architectural Computing, 7(1), 39-55.
  • Patikova, A. (2004) Digital photogrammetry in the practice of open pit mining. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 34, 1-4.
  • Sheng, Y. H., Yan, Z. G., & Song, J. L. (2003). Monitoring technique for mining subsidence with digital terrestrial photogrammetry. Journal of China University of Mining & Technology, 32(4), 411-415.
  • Murfitt, S. L., Allan, B. M., Bellgrove, A., Rattray, A., Young, M. A., & Ierodiaconou, D. (2017). Applications of unmanned aerial vehicles in intertidal reef monitoring. Scientific reports, 7(1), 1-11.
  • Yalcin, G., & Selcuk, O. (2015). 3D city modelling with Oblique Photogrammetry Method. Procedia Technology, 19, 424-431.
  • Danahy, J. (1997). A set of visualization data needs in urban environmental planning & design for photogrammetric data. In Automatic extraction of man-made objects from aerial and space images (II) (pp. 357-366). Birkhäuser, Basel.
  • Döner, F. & Bıyık, C. Management of three dimensional objects in spatial database. Chamb. Surv. Cadastre Eng. Geod. Geoinf. Mag. 100, 27 (2009).
  • Yılmaz, H. M., Mutluoglu, O., Ulvi, A., Yaman, A., & Bilgilioglu, S. S. (2018). Created Tree Dimensional Model of Aksaray University Campus with Unmanned Aerial Vehicle. Journal of Geomatics, 3(2), 103-107.
  • Choudhury, M. A. M., Costanzini, S., Despini, F., Rossi, P., Galli, A., Marcheggiani, E., & Teggi, S. (2019, May). Photogrammetry and Remote Sensing for the identification and characterization of trees in urban areas. In Journal of Physics: Conference Series (Vol. 1249, No. 1, p. 012008). IOP Publishing.
  • Wu, B., Xie, L., Hu, H., Zhu, Q., & Yau, E. (2018). Integration of aerial oblique imagery and terrestrial imagery for optimized 3D modeling in urban areas. ISPRS journal of photogrammetry and remote sensing, 139, 119-132.
  • Goetz, J., & Brenning, A. (2019). Quantifying uncertainties in snow depth mapping from structure from motion photogrammetry in an alpine area. Water Resources Research, 55(9), 7772-7783.
  • Chudley, T. R., Christoffersen, P., Doyle, S. H., Abellan, A., & Snooke, N. (2019). High-accuracy UAV photogrammetry of ice sheet dynamics with no ground control. The Cryosphere, 13(3), 955-968.
  • Casella, V. and Franzini, M. (2016) Modelling steep surfaces by various configurations of nadir and oblique photogrammetry. ISPRS Annals of the Photogrammetry. Remote Sensing and Spatial Information Sciences, III-1, 175-182.
  • Tomaštík, J., Mokroš, M., Surový, P., Grznárová, A., & Merganič, J. (2019). UAV RTK/PPK method—An optimal solution for mapping inaccessible forested areas?. Remote sensing, 11(6), 721.
  • He, F., Zhou, T., Xiong, W., Hasheminnasab, S. M., & Habib, A. (2018). Automated aerial triangulation for UAV-based mapping. Remote Sensing, 10(12), 1952.
  • 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 (PFG), (1), 17-30.
  • Turk, T. & Ocalan, T. (2020). Examining the Accuracy of Photogrammetric Products Obtained by Unmanned Aerial Vehicles with PPK GNSS System with Different Approaches. Turkish Journal of Photogrammetry, 2 (1), 22-28.
  • Eling, C., Klingbeil, L., & Kuhlmann, H. (2014). Development of an RTK-GPS system for precise real-time positioning of lightweight UAVs.
  • Takasu, T. (2021) RTKLIB, Open-Source Program Package for RTK-GPS. https://github.com/tomojitakasu/RTKLIB
Toplam 26 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Erdem Emin Maraş 0000-0002-5205-1622

Noman Nasery Bu kişi benim

Yayımlanma Tarihi 15 Şubat 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 8 Sayı: 1

Kaynak Göster

APA Maraş, E. E., & Nasery, N. (2023). Investigating the length, area and volume measurement accuracy of UAV-Based oblique photogrammetry models produced with and without ground control points. International Journal of Engineering and Geosciences, 8(1), 32-51. https://doi.org/10.26833/ijeg.1017176
AMA Maraş EE, Nasery N. Investigating the length, area and volume measurement accuracy of UAV-Based oblique photogrammetry models produced with and without ground control points. IJEG. Şubat 2023;8(1):32-51. doi:10.26833/ijeg.1017176
Chicago Maraş, Erdem Emin, ve Noman Nasery. “Investigating the Length, Area and Volume Measurement Accuracy of UAV-Based Oblique Photogrammetry Models Produced With and Without Ground Control Points”. International Journal of Engineering and Geosciences 8, sy. 1 (Şubat 2023): 32-51. https://doi.org/10.26833/ijeg.1017176.
EndNote Maraş EE, Nasery N (01 Şubat 2023) Investigating the length, area and volume measurement accuracy of UAV-Based oblique photogrammetry models produced with and without ground control points. International Journal of Engineering and Geosciences 8 1 32–51.
IEEE E. E. Maraş ve N. Nasery, “Investigating the length, area and volume measurement accuracy of UAV-Based oblique photogrammetry models produced with and without ground control points”, IJEG, c. 8, sy. 1, ss. 32–51, 2023, doi: 10.26833/ijeg.1017176.
ISNAD Maraş, Erdem Emin - Nasery, Noman. “Investigating the Length, Area and Volume Measurement Accuracy of UAV-Based Oblique Photogrammetry Models Produced With and Without Ground Control Points”. International Journal of Engineering and Geosciences 8/1 (Şubat 2023), 32-51. https://doi.org/10.26833/ijeg.1017176.
JAMA Maraş EE, Nasery N. Investigating the length, area and volume measurement accuracy of UAV-Based oblique photogrammetry models produced with and without ground control points. IJEG. 2023;8:32–51.
MLA Maraş, Erdem Emin ve Noman Nasery. “Investigating the Length, Area and Volume Measurement Accuracy of UAV-Based Oblique Photogrammetry Models Produced With and Without Ground Control Points”. International Journal of Engineering and Geosciences, c. 8, sy. 1, 2023, ss. 32-51, doi:10.26833/ijeg.1017176.
Vancouver Maraş EE, Nasery N. Investigating the length, area and volume measurement accuracy of UAV-Based oblique photogrammetry models produced with and without ground control points. IJEG. 2023;8(1):32-51.