Investigation of the effect of GCP number and distribution on photogrammetric product accuracy in UAV photogrammetry

Year 2025, Volume: 12 Issue: 1, 77 - 88, 30.04.2025

Tarık Türk , Berkay Bahadur , Yasin Demirel , Cemali Altuntaş , Taylan Öcalan

https://doi.org/10.9733/JGG.2025R0006.E

Abstract

Recently, photogrammetric products produced using Unmanned Aerial Vehicles (UAVs) are frequently preferred for disaster management, geological, and meteorological studies, urban studies and military purposes. Obtaining products with UAV photogrammetry provides a significant advantage over ground-based methods in terms of speed and cost. At the same time, the accuracy of the products produced is of particular importance. In this study, the effects of the number of Ground Control Points (GCPs) and GCP network design on accuracy were investigated. In this direction, 12 GCPs with homogeneous distribution in the study area were established and their locations were determined by GNSS measurements. Then, scenarios with different number of GCPs and different network designs were created, and the accuracy of these points were evaluated. As a result, it has been concluded that 5 GCPs homogeneously distributed in the field is sufficient for the products at high accuracy (≤ 10 cm) required in geomatics applications, increasing the number of the GCPs will not benefit the accuracy of the project and this process is disadvantageous in terms of increasing the cost along with the speed.

Keywords

UAV Photogrammetry , GCP , Network design

Project Number

TÜBİTAK 122Y125 ve CÜBAP M855

İHA fotogrametrisinde YKN sayısı ve dağılımının fotogrametrik ürün doğruluğuna etkisinin araştırılması

Abstract

Son zamanlarda İnsansız Hava Araçları (İHA) kullanılarak üretilen fotogrametrik ürünler afet yönetimi, jeolojik ve meteorolojik araştırmalar, şehircilik çalışmaları ve askeri amaçlar için sıklıkla tercih edilmektedir. İHA fotogrametrisi ile ürün elde etmek hız ve maliyet açısından yersel yöntemlere göre önemli bir avantaj sağlamaktadır. Aynı zamanda üretilen ürünlerin doğruluğu da ayrı bir önem arz etmektedir. Bu çalışmada, Yer Kontrol Noktası (YKN) sayısının ve YKN ağ tasarımının doğruluk üzerindeki etkileri araştırılmıştır. Bu doğrultuda çalışma alanında homojen dağılım gösteren 12 nokta tesis edilerek GNSS ölçümleri ile konumları belirlenmiştir. Ardından, farklı YKN sayısına ve farklı ağ tasarımına sahip senaryolar oluşturularak bu noktaların doğrulukları değerlendirilmiştir. Sonuç olarak, arazide homojen dağılım gösteren 5 YKN’nin geomatik uygulamalarında gereksinim duyulan yüksek doğruluklu (≤ 10 cm) ürünler için yeterli olduğu, YKN sayısını artırmanın projenin doğruluğuna fayda sağlamayacağı ve bu işlemin hız ile birlikte maliyeti artırması bakımından dezavantajlı olduğu sonucuna varılmıştır.

Keywords

İHA fotogrametrisi , YKN , Ağ tasarımı

Ethical Statement

Bu çalışmada etik kurallara uyulmuştur.

Project Number

TÜBİTAK 122Y125 ve CÜBAP M855

Thanks

Yazarlar çalışmayı destekleyen TÜBİTAK'a ve Sİvas Cumhuriyet Üniversitesine teşekkür ederler.

References

• 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.
• Agüera-Vega, F., Carvajal-Ramírez, F., & Martínez-Carricondo, P. (2017). Accuracy of digital surface models and orthophotos derived from unmanned aerial vehicle photogrammetry. Journal of Surveying Engineering, 143(2), 04016025.
• Cerreta, J., Thirtyacre, D., Miller, P., Burgess, S. S., & Austin, W. J. (2023). Accuracy Assessment of the eBee Using RTK and PPK Corrections Methods as a Function of Distance to a GNSS Base Station. International Journal of Aviation, Aeronautics, and Aerospace, 10(3), 4.
• 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.
• 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), 2447.
• Gencerk, E Y. (2016). An analysis of the production state of a construction project with the unmanned aerial vehicle photogrammetry application (Master Thesis). Graduate School of Natural and Applied Sciences, Istanbul Technical University, Istanbul, Türkiye.
• Harwin, S., & 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), 1573-1599.
• Hastaoglu, K. O., Kapicioglu, H. S., Gül, Y., & Poyraz, F. (2023). Investigation of the effect of height difference and geometry of GCP on position accuracy of point cloud in UAV photogrammetry. Survey Review, 55(391), 325-337.
• Hugenholtz, C. H., Whitehead, K., Brown, O. W., Barchyn, T. E., Moorman, B. J., LeClair, A., Riddell, K., & Hamilton, T. (2013). Geomorphological mapping with a small unmanned aircraft system (sUAS): Feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model. Geomorphology, 194, 16-24.
• 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), 30.
• 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.
• Mozas-Calvache, A. T., Pérez-García, J. L., Cardenal-Escarcena, F. J., Mata-Castro, E., & Delgado-García, J. (2012). Method for photogrammetric surveying of archaeological sites with light aerial platforms. Journal of Archaeological Science, 39(2), 521-530.
• Niethammer, U., James, M. R., Rothmund, S., Travelletti, J., & Joswig, M. (2012). UAV-based remote sensing of the Super-Sauze landslide: Evaluation and results. Engineering Geology, 128, 2-11.
• Okuyama, S., Torii, T., Nawa, Y., Kinoshita, I., Suzuki, A., Shibuya, M., & Miyazaki, N. (2005). Development of a remote radiation monitoring system using unmanned helicopter. International congress series, 1276, 422-423.
• Ollero, A., & Merino, L. (2006). Unmanned aerial vehicles as tools for forest-fire fighting. Forest Ecology and Management, 234(1), S263.
• Oniga, V. E., Breaban, A. I., Pfeifer, N., & Chirila, C. (2020). Determining the suitable number of ground control points for UAS images georeferencing by varying number and spatial distribution. Remote Sensing, 12(5), 876.
• Ozdas, N., Kocak, M. G., & Karakis, S. (2024). Examining the accuracy of DEM of difference and 3D point cloud comparison methods: Open pit mine case study. Journal of Geodesy and Geoinformation, 11(1), 41-50.
• 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), 1606.
• Štroner, M., Urban, R., Reindl, T., Seidl, J., & Brouček, J. (2020). Evaluation of the georeferencing accuracy of a photogrammetric model using a quadrocopter with onboard GNSS RTK. Sensors, 20(8), 2318.
• Tomaštík, J., Mokroš, M., Saloň, Š., Chudý, F., & Tunák, D. (2017). Accuracy of photogrammetric UAV-based point clouds under conditions of partially-open forest canopy. Forests, 8(5), 151.
• 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.
• Turk, T., & Ocalan, T. (2020). PPK GNSS sistemine sahip insansız hava araçları ile elde edilen fotogrametrik ürünlerin doğruluğunun farklı yaklaşımlarla irdelenmesi. Türkiye Fotogrametri Dergisi, 2(1), 22-28 (in Turkish).
• Turk, 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(7), 476.
• Villanueva, J. K. S., & Blanco, A. C. (2019). Optimization of ground control point (GCP) configuration for unmanned aerial vehicle (UAV) survey using structure from motion (SFM). The international archives of the photogrammetry, remote sensing and spatial information sciences, 42, 167-174.
• Westoby, M. J., Brasington, J., Glasser, N. F., Hambrey, M. J., & Reynolds, J. M. (2012). ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications. Geomorphology, 179, 300-314.
• 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.
• Zhang, H., Aldana-Jague, E., Clapuyt, F., Wilken, F., Vanacker, V., & van Oost, K. (2019). Evaluating the potential of post-processing kinematic (PPK) georeferencing for UAV-based structure-from-motion (SfM) photogrammetry and surface change detection. Earth Surface Dynamics, 7(3), 807-827.