SavedAdd your journal

Journals / International Journal of Engineering and Geosciences / 2026 / Volume: 10 Issue: 2

The Effect of Ground Control Points Located on Roofs on Building Facade Accuracy

Hasan Dilmaç(ONDOKUZ MAYIS UNIVERSITY)0000-0001-6877-8730
Veli İlçi(ONDOKUZ MAYIS ÜNİVERSİTESİ)0000-0002-9485-874X
Nazime Tilbe Şaşmaz(ONDOKUZ MAYIS UNIVERSITY)0009-0002-5042-2837
İbrahim Murat Ozulu(HITIT UNIVERSITY)0000-0002-0963-3600
Pages
—
Publication Date
2025-07-15
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Average std. dev. values of the models fluctuate within a range of 7 to 11 cm

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The popularity of Unmanned Aerial Vehicle (UAV) photogrammetry is growing worldwide due to its low-cost advantage in collecting high-resolution 3D topographic models.
📊
Key Findings & Data:A UAV survey covering 10.37 hectares was conducted to achieve this goal.
💡
Conclusion & Impact:Average std. dev. values of the models fluctuate within a range of 7 to 11 cm
🔬Design:Survey & Empirical Study
📍Scope:Comprehensive Sample
⚙️Variables:UAV · Photogrammetry · GCP

Abstract

The popularity of Unmanned Aerial Vehicle (UAV) photogrammetry is growing worldwide due to its low-cost advantage in collecting high-resolution 3D topographic models. This research aims to ascertain the impact of Ground Control Points (GCPs) located on building roofs on facade accuracy. A UAV survey covering 10.37 hectares was conducted to achieve this goal. The research utilised 91 GCPs for geo-referencing, with 38 on the ground and 53 on the roofs of the buildings in the area. Images were obtained with three different flight patterns: single (S), double (D), and circular (C), which represent flight routes. The images acquired from the flights have been subjected to two distinct GCP configurations, and two models were obtained for each flight pattern. The point cloud produced by a robotic total station was used to ensure the accuracy of the facades of the buildings in the models. The standard deviation (std. dev.) of the distances between the points on the facade and the reference planes (RPs) were used as a measure of accuracy. The std. dev. values of the model facades were compared by each other while considering the number of points of the surfaces. Average std. dev. values of the models fluctuate within a range of 7 to 11 cm

🔖

Cite This Article

Dilmaç, H., İlçi, V., Şaşmaz, N. T., Ozulu, İ. M. (2025). The Effect of Ground Control Points Located on Roofs on Building Facade Accuracy. International Journal of Engineering and Geosciences, Volume: 10 Issue: 2. https://doi.org/10.26833/ijeg.1535675

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (45)

  1. Ajayi, O. G., Palmer, M., & Salubi, A. A. (2018). Modelling farmland topography for suitable site selection of dam construction using unmanned aerial vehicle (UAV) photogrammetry. Remote Sensing Applications: Society and Environment, 11, 220-230. https://doi.org/10.1016/j.rsase.2018.07.007
  2. Szypuła, B. (2024). Accuracy of UAV-based DEMs without ground control points. Geoinformatica, 28(1), 1-28. https://doi.org/10.1007/s10707-023-00498-1
  3. Sefercik, U. G., Kavzoglu, T., Colkesen, İ., Nazar, M., Ozturk, M. Y., Adalı, S., & Din, S. (2023). 3D positioning accuracy and land cover classification performance of multispectral RTK UAVs. International Journal of Engineering and Geosciences. 8(2), 119-128. https://doi.org/10.26833/ijeg.1074791
  4. Karataş, L., Alptekin, A. & Yakar, M. (2022). Creating Architectural Surveys of Traditional Buildings with the Help of Terrestrial Laser Scanning Method (TLS) and Orthophotos: Historical Diyarbakır Sur Mansion. Advanced LiDAR, 2(2), 54-63.
  5. Murtiyoso, A., Grussenmeyer, P., Börlin, N., Vandermeerschen, J., & Freville, T. (2018). Open source and independent methods for bundle adjustment assessment in close-range UAV photogrammetry. Drones. 2(1), 1–18. https://doi.org/10.3390/drones2010003
  6. Colica, E., D’Amico, S., Lannuci, R., Martino, S., Gauci, A., Galone, L., Galea, P., & Paciello, A. (2021). Using unmanned aerial vehicle photogrammetry for digital geological surveys: case study of Selmun promontory, northern of Malta. Environmental Earth Sciences, 80(17), 1–14. https://doi.org/10.1007/s12665-021-09846-6
  7. Maraş, E. E., & Nasery, M. 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
  8. Đurić, I., Vasiljević, I., Obradović, M., Stojaković, V., Kićanović, J., & Obradović, R. (2021). Comparative analysis of open-source and commercial photogrammetry software for cultural heritage. eCAADe 2021 Towards a New, Configurable Architecture, 2, 8-10, Novi Sad, Serbia.
  9. Jarahizadeh, S., & Salehi, B. (2024). A Comparative Analysis of UAV Photogrammetric Software Performance for Forest 3D Modeling: A Case Study Using Agisoft Photoscan, PIX4DMapper, and DJI Terra. Sensors, 24(286), 1–15. https://doi.org/10.3390/s24010286
  10. Janoušek, J., Jambor, V., Marcoň, P., Dohnal, P., Synková, P., & Fiala, P. (2021). Using UAV-based photogrammetry to obtain correlation between the vegetation indices and chemical analysis of agricultural crops. Remote Sensing, 13(10), 1878. doi: 10.3390/rs13101878.
  11. Frey, J., Kovach, K., Stemmler, S., & Koch, B. (2018). UAV photogrammetry of forests as a vulnerable process. A sensitivity analysis for a structure from motion RGB-image pipeline. Remote Sensing, 10(912),1–12. https://doi.org/10.3390/rs10060912
  12. İlci, V., & Ozulu, İ. M. (2016). The Utility of PPP Technique in Archaeological Surveying Applications: A Case Study in Sapinuva Excavation. Harita Teknolojileri Elektronik Dergisi, 8(3), 1-9. doi: 10.15659/hartek.16.09.303.
  13. Kanun, E., Alptekin, A., & Yakar, M. (2021). Cultural heritage modelling using UAV photogrammetric methods: a case study of Kanlıdivane archeological site. Advanced UAV, 1(1), 24–33.
  14. Yakar, M., Yılmaz, H. M. & Mutluoǧlu, Ö. (2010). Comparative evaluation of excavation volume by TLS and total topographic station-based methods. Lasers in Eng, 19, 331-345
  15. Özdemir, İ., & Güngör, A. (2024). Documentation of Archaeological Excavation Sites with Terrestrial Laser Scanning and UAV Photogrammetry Methods. Advanced LiDAR, 4(1), 28-32.
  16. Mandirola, M., Casarotti, C., Peloso, S., Lanese, I., Brunesi, E., Senaldi, I., Monti, A., & Facchetti, C. (2021). Guidelines for the use of Unmanned Aerial Systems for fast photogrammetry-oriented mapping in emergency response scenarios. International Journal of Disaster Risk Reduction, 58(102207), 1-15. https://doi.org/10.1016/j.ijdrr.2021.102207.
  17. Erdoğan, A., Görken, M., & Kabadayı, A. (2022). Study on the use of unmanned aerial vehicles in open mine sites: A case study of Ordu Province Mine Site. Advanced UAV, 2(2), 35-40.
  18. Douglas, A., Langenderfer, A. M., & Johnson, C. (2024). Road Condition Monitoring Utilizing UAV Photogrammetry Aligned to Principal Curve of Mine Haul Truck Path. Mining, Metallurgy & Exploration, 41, 61-72. https://doi.org/10.1007/s42461-023-00877-0
  19. Polat, N., & Akça, Ş. (2023). Assessing road roughness using UAV-derived dense point clouds. Mersin Photogrammetry Journal, 5(2), 75-81. https://doi.org/10.53093/mephoj.1358902
  20. Aykut, N. O. (2019). İnsansız hava araçlarının kıyı çizgisinin belirlenmesinde kullanılabilirliğinin araştırılması. Geomatik, 4(2), 141-146. https://doi.org/10.29128/geomatik.503055
  21. Budiharto, W., Irwansyah, E., Suroso, J. S., Chowanda, A., Ngarianto, H., & Gunawan, A. A. S. (2021). Mapping and 3D modelling using quadrotor drone and GIS software. Journal of Big Data, 8(1), 1-12. https://doi.org/10.1186/s40537-021-00436-8
  22. Sona, G., Pinto, L., Pagliari, D., Passoni, D., & Gini, R. (2014). Experimental analysis of different software packages for orientation and digital surface modelling from UAV images. Earth Science Informatics, 7(2), 97–107.https://doi.org/10.1007/s12145-013-0142-2
  23. Lovitt, J., Rahman, M. M., & McDermid, G. J. (2017). Assessing the value of UAV photogrammetry for characterizing terrain in complex peatlands. Remote Sensing, 9(7), 715. https://doi.org/10.3390/rs9070715
  24. Pathak, S., Acharya, S., Bk, S., Karn, G., Thapa, U. (2024). UAV-based topographical mapping and accuracy assessment of orthophoto using GCP. Mersin Photogrammetry Journal, 6(1), 1-8. https://doi.org/10.53093/mephoj.1350426
  25. Yakar, M., Yilmaz, H. M. & Mutluoglu, O. (2010). Close range photogrammetry and robotic total station in volume calculation. International Journal of the Physical Sciences. 5(2), 086-096
  26. Türk, T., Tunalioglu, N., Erdogan, B., Ocalan, T., & Gurturk, M. (2022). Accuracy assessment of UAV-post-processing kinematic (PPK) and UAV-traditional (with ground control points) georeferencing methods. Environmental Monitoring and Assessment, 194, 476. https://doi.org/10.1007/s10661-022-10170-0
  27. Jiménez-Jiménez, S. I., Ojeda-Bustamante, W., Marcial-Pablo, M. D. J., & Enciso, J. (2021). Digital terrain models generated with low-cost UAV photogrammetry: Methodology and accuracy. ISPRS International Journal of Geo-Information, 10(5), 285. https://doi.org/10.3390/ijgi10050285
  28. Mesas-Carrascosa, F. J., García, M. D. N., De Larriva, J. E. M., & 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), 1-12. https://doi.org/10.3390/s16111838
  29. Sanz-Ablanedo, E., Chandler, J. H., Rodríguez-Pérez, J. R., & 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), 1-19. https://doi.org/10.3390/rs10101606
  30. Akay, S. S., Ozcan, O., Şanlı, F. B., Bayram, B., & Gorum, T. (2021). Assessing the spatial accuracy of UAV-derived products based on variation of flight altitudes. Turkish Journal of Engineering, 5(1), 35-40.
  31. Deliry, S. I., & Avdan, U. (2024). Accuracy assessment of UAS photogrammetry and structure from motion in surveying and mapping. International Journal of Engineering and Geosciences, 9(2), 165-190. https://doi.org/10.26833/ijeg.1366146
  32. Barba, S., Barbarella, M., Di Benedetto, A., Fiani, M., Gujski, L., & Limongiello, M. (2019). Accuracy assessment of 3d photogrammetric models from an unmanned aerial vehicle. Drones, 3(4), 1–19. https://doi.org/10.3390/drones3040079
  33. Chaudhry, M. H., Ahmad, A., & Gulzar, Q. (2020). Impact of uav surveying parameters on mixed urban landuse surface modelling. ISPRS International Journal of Geo-Information, 9(11), 1-17. https://doi.org/10.3390/ijgi9110656
  34. Rangel, J. M. G., Gonçalves, G. R., & Pérez, J. A. (2018). The impact of number and spatial distribution of GCPs on the positional accuracy of geospatial products derived from low-cost UASs. International Journal of Remote Sensing, 39(21), 7154–7171. https://doi.org/10.1080/01431161.2018.1515508
  35. Dharshan Shylesh, D. S., Manikandan, N., Sivasankar, S., Surendran, D., Jaganathan, R., & Mohan, G. (2023). Influence of quantity, quality, horizontal and vertical distribution of ground control points on the positional accuracy of UAV survey. Applied Geomatics, 15(4), 897–917. https://doi.org/10.1007/s12518-023-00531-w
  36. Yakar, M., & Dogan, Y. (2019). 3D Reconstruction of Residential Areas with SfM Photogrammetry. In Advances in Remote Sensing and Geo Informatics Applications: Proceedings of the 1st Springer Conference of the Arabian Journal of Geosciences (CAJG-1), Tunisia 2018 (pp. 73-75). Springer International Publishing.
  37. Agüera-Vega, F., Carvajal-Ramírez, F., & Martínez-Carricondo, P. (2017). Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement, 98, 221-227. https://doi.org/10.1016/j.measurement.2016.12.002.
  38. Taddia, Y., González-García, L., Zambello, E., & Pellegrinelli, A. (2020). Quality assessment of photogrammetric models for façade and building reconstruction using dji phantom 4 rtk. Remote Sensing, 12(19), 1–32. https://doi.org/10.3390/rs12193144
  39. Elkhrachy, I. (2021). Accuracy Assessment of Low-Cost Unmanned Aerial Vehicle (UAV) Photogrammetry. Alexandria Engineering Journal, 60(6), 5579–5590. https://doi.org/10.1016/j.aej.2021.04.011
  40. Ferrer-González, E., Agüera-Vega, F., Carvajal-Ramírez, F., & Martínez-Carricondo, P. (2020). UAV photogrammetry accuracy assessment for corridor mapping based on the number and distribution of ground control points. Remote Sensing, 12(15), 1-19. https://doi.org/10.3390/rs12152447
  41. Liu, X., Lian, X., Yang, W., Wang, F., Han, Y., & Zhang, Y. (2022). Accuracy Assessment of a UAV Direct Georeferencing Method and Impact of the Configuration of Ground Control Points. Drones, 6(2), 1-15. https://doi.org/10.3390/drones6020030
  42. Martínez-Carricondo, P., Agüera-Vega, F., Carvajal-Ramírez, F., Mesas-Carrascosa, F. J., García-Ferrer, A., & Pérez-Porras, F. J. (2018). Assessment of UAV-photogrammetric mapping accuracy based on variation of ground control points. International Journal of Applied Earth Observation and Geoinformation, 72, 1–10. https://doi.org/10.1016/j.jag.2018.05.015
  43. Zhang, Y., Zhang, C., Chen, S., & Chen, X. (2021). Automatic Reconstruction of Building Façade Model from Photogrammetric Mesh Model. Remote Sensing, 13(19), 3801. https://doi.org/10.3390/rs13193801
  44. Jeon, E. I., Yu, S. J., Seok, H. W., Kang, S. J., Lee, K. Y., & Kwon, O. S. (2017). Comparative evaluation of commercial softwares in UAV imagery for cultural heritage recording: case study for traditional building in South Korea. Spatial Information Research, 25(5), 701–712. https://doi.org/10.1007/s41324-017-0137-z
  45. Yilmaz, H. M. & Yakar, M. (2008). Computing Of Volume Of Excavation Areas By Digıtal Close Range Photogrammetry. Arabian J. Sci. Eng. 33(1A), 63-784