Ground control points and their influences on the precision of generating a digital surface model using an unmanned aerial vehicle
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- Category: Content №6 2025
- Last Updated on 25 December 2025
- Published on 30 November -0001
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Authors:
Anh Tuan Luu*, orcid.org/0009-0001-7738-9718, Hanoi University of Mining and Geology, Faculty of Geomatics and Land Administration, Hanoi, Socialist Republic of Vietnam, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.
Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2025, (6): 179 - 188
https://doi.org/10.33271/nvngu/2025-6/179
Abstract:
Purpose. To determine the optimal number and spatial distribution of Ground Control Points (GCPs) required to achieve high-precision georeferencing in unmanned aerial vehicle (UAV) imagery, particularly for applications requiring 1:1,000 scale mapping.
Methodology. Seven experimental scenarios were conducted, varying the number of GCPs from 4 to 30. For each scenario, GCPs were arranged in seven different spatial configurations, including central, corner, edge, and evenly distributed placements. The Root Mean Squared Error (RMSE) was calculated for each configuration to assess georeferencing accuracy.
Findings. The results showed that using only 4 GCPs produced the highest RMSE, indicating the lowest accuracy. RMSE values decreased as the number of GCPs increased, with minimal improvement beyond 20 GCPs. Among all distribution patterns, placing GCPs at the corners consistently resulted in the highest RMSE. The most accurate results were achieved with 20 evenly distributed GCPs.
Originality. This study provides a systematic evaluation of both the quantity and spatial arrangement of GCPs in UAV photogrammetry, offering empirical evidence to support optimal GCP deployment strategies.
Practical value. The findings offer practical guidance for UAV mapping professionals, suggesting that 20 evenly distributed GCPs are sufficient to meet the accuracy standards for 1:1,000 scale maps. This helps optimize fieldwork efficiency while ensuring data quality.
Keywords: ground control points, Digital Surface Model, unmanned aerial vehicle
References.
1. Minh, D. T., & Dung, N. B. (2023). Applications of UAVs in mine industry: A scoping review. Journal of Sustainable Mining, 22(2), 128-145. https://doi.org/10.46873/2300-3960.1384
2. Kaushal, H., & Bhatnagar, H. (2022). Application of Drones in Mining industry-rules, guidelines and case study. Journal of emerging technologies and innovative research, 12, 459-470.
3. Bhandari, B., Oli, U., Pudasaini, U., & Panta, N. (2015). Generation of high resolution DSM using UAV images. FIG working week, 17-21. Retrieved from https://www.researchgate.net/publication/311650666
4. Puniach, E., Gruszczyński, W., Ćwiąkała, P., & Matwij, W. (2021). Application of UAV-based orthomosaics for determination of horizontal displacement caused by underground mining. ISPRS Journal of Photogrammetry and Remote Sensing, 174, 282-303. https://doi.org/10.1016/j.isprsjprs.2021.02.006
5. Vemulapalli, S. C., & Mesapam, S. (2021). Slope stability analysis for mine hazard assessment using uav. Journal of the Indian Society of Remote Sensing, 49, 1483-1491. https://doi.org/10.1007/s12524-020-01239-9
6. Carabassa, V., Montero, P., Alcañiz, J. M., & Padró, J.-C. (2021). Soil erosion monitoring in quarry restoration using drones. Minerals, 11(9), 949. https://doi.org/10.3390/min11090949
7. Nguyen, B. D. (2023). Identifying the Potential Application of Unmanned Aerial Vehicle Technology in Mine Waste Dumps. Inżynieria Mineralna, 52(2). http://doi.org/10.2922/IM-2023-02-2
8. Baltiyeva, A., Orynbassarova, E., Zharaspaev, M., & Akhmetov, R. (2023). Studying sinkholes of the earth’s surface involving radar satellite interferometry in terms of Zhezkazgan field, Kazakhstan. Mining of Mineral Deposits, 17(4), 61-74. https://doi.org/10.33271/mining17.04.061
9. Gehrke, S., Morin, K., Downey, M., Boehrer, N., & Fuchs, T. (2010). Semi-global matching: An alternative to LIDAR for DSM generation. Proceedings of the 2010 Canadian Geomatics Conference and Symposium of Commission I, 2(6), 1-6. Retrieved from https://www.isprs.org/proceedings/XXXVIII/part1/11/11_01_Paper_121.pdf
10. Lastilla, L., Belloni, V., Ravanelli, R., & Crespi, M. J. R. S. (2021). DSM generation from single and cross-sensor multi-view satellite images using the new agisoft metashape: The case studies of Trento and Matera (Italy). Remote Sensing, 13(4), 593. https://doi.org/10.3390/rs13040593
11. Hwang, J. T., Chen, Y. W., Lian, W. Y., Yang, Y. Y., & Chu, T. C. (2015). DSM generation on the shade of tree area of aerial photogrammetry. 2015 23 rd International Conference on Geoinformatics, 1-4. https://doi.org/10.1109/GEOINFORMATICS.2015.7378601
12. Ulvi, A. (2021). The effect of the distribution and numbers of ground control points on the precision of producing orthophoto maps with an unmanned aerial vehicle. Journal of Asian Architecture and Building Engineering, 20(6), 806-817. https://doi.org/10.1080/13467581.2021.1973479
13. Ulvi, A. (2018). Analysis of the utility of the unmanned aerial vehicle (UAV) in volume calculation by using photogrammetric techniques. International journal of engineering and geosciences, 3(2), 43-49. https://doi.org/10.26833/ijeg.377080
14. Nguyen, L. Q. (2021). Accuracy assessment of open-pit mine’s digital surface models generated using photos captured by Unmanned Aerial Vehicles in the post-processing kinematic mode. Journal of Mining and Earth Sciences, 62(4), 38-47. https://doi.org/10.46326/JMES.2021.62(4).05
15. Clapuyt, F., Vanacker, V., & Van Oost, K. (2016). Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms. Geomorphology, 260, 4-15. https://doi.org/10.1016/j.geomorph.2015.05.011
16. Rock, G., Ries, J., & Udelhoven, T. (2012). Sensitivity analysis of UAV-photogrammetry for creating digital elevation models (DEM). The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 38, 69-73. https://doi.org/10.5194/isprsarchives-XXXVIII-1-C22-69-2011
17. Nouwakpo, S. K., Weltz, M. A., & McGwire, K. (2016). Assessing the performance of structure-from-motion photogrammetry and terrestrial LiDAR for reconstructing soil surface microtopography of naturally vegetated plots. Earth Surface Processes and Landforms, 41(3), 308-322. https://doi.org/10.1002/esp.3787
18. 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. https://doi.org/10.3390/rs12050876
19. 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
20. 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. https://doi.org/10.3390/rs10101606
21. Gomes Pessoa, G., Caceres Carrilho, A., Takahashi Miyoshi, G., Amorim, A., & Galo, M. (2021). Assessment of UAV-based digital surface model and the effects of quantity and distribution of ground control points. International Journal of Remote Sensing, 42(1), 65-83. https://doi.org/10.1080/01431161.2020.1800122
22. 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
23. Long, N. Q., Goyal, R., Bui, L. K., Cuong, C. X., Canh, L. V., Minh, N. Q., & Bui, X. N. (2021). Optimal choice of the number of ground control points for developing precise DSM using light-weight UAV in small and medium-sized open-pit mine. Archives of Mining Sciences, 66(3), 369-384. https://doi.org/10.24425/ams.2021.138594
24. 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/10.13140/RG.2.2.29670.52807
25. 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. https://doi.org/10.5194/isprs-archives-XLII-4-W12-167-2019
26. Shahbazi, M., Sohn, G., Théau, J., & Menard, P. (2015). Development and evaluation of a UAV-photogrammetry system for precise 3D environmental modeling. Sensors, 15(11), 27493-27524.
https://doi.org/10.3390/s151127493
27. Nguyen, Q. L., Bui, X. N., Cao, X. C., & Le, V. C. (2019). An approach of mapping quarries in Vietnam using low-cost Unmanned Aerial Vehicles. Inżynieria Mineralna, 21. https://doi.org/10.29227/IM2025-n1-v1
28. Tonkin, T. N., & Midgley, N. G. (2016). Ground-control networks for image based surface reconstruction: An investigation of optimum survey designs using UAV derived imagery and structure-from-motion photogrammetry. Remote Sensing, 8(9), 786. https://doi.org/10.3390/rs8090786
29. Long, N. Q. (2021). Research proposes a process of establishing large scale topographic maps 1:2,000, 1:1,000 and 1:500 for the topographic of open pit mine area in vietnam using low-cost uavs and common cameras. Ministerial-level scientific research project.
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