Evaluating the accuracy of Digital Surface Models generated from imagery acquired with Unmanned Aerial Vehicles
- Authors: Minh Tuyet Dang
Affiliations:
Thuyloi University, Ha Noi, Vietnam
- *Corresponding:This email address is being protected from spambots. You need JavaScript enabled to view it.
- Received: 23rd-Apr-2024
- Revised: 28th-May-2024
- Accepted: 2nd-June-2024
- Online: 31st-Aug-2024
Abstract:
This paper assesses the accuracy of the UAV-based Digital Surface Model (DSM) in a small area with complicated terrain based on the number of ground control points determined by GNSS technology. Experimental results obtained at the mineral exploitation and processing area of Tan Tien Co., Ltd., Yen Bai province show that 5 ground control points are the minimum number needed for image correction to generate DSM with a mean square error of 14.744 cm. In addition, the optimal number of ground control points provides the highest accuracy for DSM models while also meeting the required accuracy for creating a 1:1000 scale map of 20 points. The results of the paper can be used as a reference when choosing ground control points to establish DSM for areas with areas and topographical characteristics similar to the research area of the paper.
1. Phạm Hà Thái, T. T. A., Lê Thu Trang & Nguyễn Thị Ánh (2018). Khảo sát một số yếu tố ảnh hưởng đến độ chính xác xây dựng mô hình số bề mặt từ dữ liệu ảnh chụp bởi thiết bị bay không người lái. Tạp chí Khoa học Kỹ thuật Mỏ - Địa chất. Số 59, kỳ 5. 21-30.
2. Agüera-Vega, F., F. Carvajal-Ramírez and P. Martínez-Carricondo (2017). Assessment of photogrammetric mapping accuracy based on variation ground control points number using unmanned aerial vehicle. Measurement 98: 221-227.
3. Awasthi, B., S. Karki, P. Regmi, D. S. Dhami, S. Thapa and U. S. Panday (2020). Analyzing the effect of distribution pattern and number of GCPs on overall accuracy of UAV photogrammetric results. Proceedings of UASG 2019: Unmanned Aerial System in Geomatics 1, Springer.
4. Clapuyt, F., V. Vanacker and K. Van Oost (2016). Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms. Geomorphology 260: 4-15.
5. Coveney, S. and K. Roberts (2017). Lightweight UAV digital elevation models and orthoimagery for environmental applications: data accuracy evaluation and potential for river flood risk modelling. International journal of remote sensing 38(8-10): 3159-3180.
6. Kääb, A., L. Girod and I. Berthling (2014). Surface kinematics of periglacial sorted circles using structure-from-motion technology. The Cryosphere 8(3): 1041-1056.
7. Leitão, J. P., M. Moy de Vitry, A. Scheidegger and J. Rieckermann (2016). Assessing the quality of digital elevation models obtained from mini unmanned aerial vehicles for overland flow modelling in urban areas. Hydrology and Earth System Sciences 20(4): 1637-1653.
8. Lim, S. (2016). Geospatial Information Data Generation Using Unmanned Aerial Photogrammetry and Accuracy Assessment. Department of Civil Engineering, Graduate School Chungnam National University, Daejeon, Korea.
9. Liu, X., X. Lian, W. Yang, F. Wang, Y. Han and Y. Zhang (2022). Accuracy assessment of a UAV direct georeferencing method and impact of the configuration of ground control points. Drones 6(2): 30.
10. Long, N. Q., R. Goyal, L. K. Bui, C. X. Cuong, L. V. Canh, N. Q. Minh and X. N. Bui (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).
11. Minh, D. T. and N. B. Dung (2023). Applications of UAVs in mine industry: A scoping review. Journal of Sustainable Mining 22(2): 128-145.
12. Nguyen, B. D. (2023). Identifying the Potential Application of Unmanned Aerial Vehicle Technology in Mine Waste Dumps. Inzynieria Mineralna 52(2).
13. Nguyen, L. Q., M. T. Dang, L. K. Bui, Q. B. Ngoc and T. X. Tran (2022). Application of Unmanned Aerial Vehicles for Surveying and Mapping in Mines: A Review. International Conference on Geo- Spatial Technologies and Earth Resources, Springer.
14. Sanz-Ablanedo, E., J. H. Chandler, J. R. Rodríguez-Pérez and C. Ordóñez (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.
15. Smith, M. W., J. L. Carrivick and D. J. Quincey (2016). Structure from motion photogrammetry in physical geography. Progress in physical geography 40(2): 247-275.
16. Son, S. W., J. H. Yoon, H. J. Jeon, D. W. Kim and J. J. Yu (2019). Optimal flight parameters for unmanned aerial vehicles collecting spatial information for estimating large-scale waste generation. International Journal of Remote Sensing 40(20): 8010-8030.
17. 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.
18. Van Le, C., C. X. Cao, V. H. Le and T. Dinh (2020). Volume computation of quarries in Vietnam based on Unmanned Aerial Vehicle (UAV) data. Journal of Mining and Earth Sciences Vol 61(1): 21-30.
19. Yu, J. J., D. W. Kim, E. J. Lee and S. W. Son (2020). Determining the optimal number of ground control points for varying study sites through accuracy evaluation of unmanned aerial system-based 3D point clouds and digital surface models. Drones 4(3): 49.
20. YUN, B.-Y. and S.-M. SUNG (2018). Location accuracy of unmanned aerial photogrammetry results according to change of number of ground control points. Journal of the Korean Association of Geographic Information Studies 21(2): 24-33.
Other articles
Mining Industry Journal
No. 226 Le Duan Street, Dong Da District, Hanoi City
Tel:(+84-24) 36649158 Fax: (+84-24) 366159
Email:tccongnghiepmo@gmail.com