Application of Low-cost Unmanned Aerial Vehicle for Accurate Mapping: Case Study at  King Mongkut's University of Technology Thonburi, Ratchaburi Residential College

Theera Laphitchayangkul; Abhisit Bhatsada; Komsilp Wangyao

Authors

Theera Laphitchayangkul Department of Civil Engineering, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, Thailand
Abhisit Bhatsada The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology Thonburi, Bangkok, Thailand; Center of Excellence on Energy Technology and Environment (CEE), PERDO, King Mongkut's University of Technology Thonburi, Bangkok, Thailand
Komsilp Wangyao The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology Thonburi, Bangkok, Thailand; Center of Excellence on Energy Technology and Environment (CEE), PERDO, King Mongkut's University of Technology Thonburi, Bangkok, Thailand

Keywords:

UAV photogrammetry, Topographic map, Drone

Abstract

In this study, photogrammetric potential of low-cost UAVs for accurate mapping was tested at King Mongkut's University of Technology Thonburi, Ratchaburi Residential College by analyzing the accuracy of a digital elevation model (DEM) from low-cost UAV photogrammetry. Ground control points (GCPs) and check points (CPs) were established using a technique based on global navigation satellite system. Sixteen points were placed as GCPs for geo-referencing and twenty-one points were placed as CPs for accuracy evaluation. A flight plan was set at the ground sampling distance (GSD) of 5 cm/pixel with 80% frontal overlap and 75% side overlap. The collected photos and positions were processed via the Pix4Dmapper software (version 4.5) for generating densified point cloud, DEM, orthomosaic and contour lines. The outputs were evaluated for planimetric and vertical accuracies using root mean square error (RMSE). The results showed that RMSE_X, RMSE_Y, RMSE_Z, and RMSE_T of GCPs were 1.24, 1.86, 0.42, and 1.17 cm, respectively. At the CPs, RMSE_X, RMSE_Y, RMSE_Z, and RMSE_T were 4.75, 4.76, 6.95, and 5.48 cm, respectively. In accordance with the ASPRS 2014 standard, the orthomosaic obtained in this study can be used for the highest accuracy work because both RMSE_X and RMSE_Y values were less than 1-pixel. As per the former ASPRS 1990 standard, the map scale was noted to be 1:400 or smaller in Class 1. In the case of the vertical accuracy evaluation, the result was in “the 10 cm of vertical accuracy class” that meets the ASPRS 2014 standard. Therefore, UAV photogrammetry from low-cost UAV could be regarded as an advanced technology, which can potentially change conventional mapping; it also leads to the savings in terms of cost, time and labor in the field.

References

Rakha, T. and Gorodetsky, A., 2018, “Review of Unmanned Aerial System (UAS) Applications in the Built Environment: Towards Automated Building Inspection Procedures using Drones,” Automation in Construction, 93, pp. 252-264.

Crouch, C.C., 2005, “ Integration of Mini-Uavs At The Tactical Operations Level: Implications Of Operations, Implementation, And Information Sharing,” Naval Postgraduate School Monterey CA.

Hassanalian, M. and Abdelkefi, A., 2017, “Classifications, applications, and design challenges of drones: A review,” Progress in Aerospace Sciences, 91, pp. 99-131.

Fornace, K.M., Drakeley, C.J., William, T., Espino, F. and Cox, J., 2014, “Mapping Infectious Disease Landscapes: Unmanned Aerial Vehicles and Epidemiology,” Trends in Parasitology, 30 (11), pp. 514-519.

Ajayi, O.G., Salubi, A.A., Angbas, A.F. and Odigure, M.G., 2017, “ Generation of Accurate Digital Elevation Models from UAV Acquired Low Percentage Overlapping Images,” International Journal of Remote Sensing, 38 (8-10), pp. 3113-3134.

Hamilton, S., 2017, UAV (drone) aerial photography and photogrammetry and its utility for archaeological site documentation, Lakehead University [Online], Available: http://www. apaontario.ca/resources/Documents/APA_OccasionalPaper2_DroneTesting_2017. pdf.[day]

Martínez-Carricondo, P., Agüera-Vega, F., Carvajal-Ramírez, F., Mesas-Carrascosa, F.J., García-Ferrer, A. and 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, pp. 1-10.

American Society for Photogrammetric Engineering and Remote Sensing (ASPRS), 2015, “ASPRS Positional Accuracy Standards for Digital Geospatial Data (Edition 1, Version 1.0., November, 2014),” Photogrammetric Engineering and Remote Sensing, 81 (3), pp. A1-A26.

Singhal, G., Bansod, B. and Mathew, L., 2018, Unmanned Aerial Vehicle Classification, Applications and Challenges: A Review.

Day, D., Weaver, W. and Wilsing, L., 2016, “ Accuracy of UAS Photogrammetry: A Comparative Evaluation”, Photogrammetric Engineering and Remote Sensing, 82 (12), pp. 909-914.

Torres-Sánchez, J., López-Granados, F., Borra-Serrano, I. and Peña, J.M., 2018, “Assessing UAV-collected Image Overlap Influence on Computation Time and Digital Surface Model Accuracy in Olive Orchards,” Precision Agriculture, 19 (1), pp. 115-133.

Sadeq, H.A., 2019, “ Accuracy Assessment Using Different UAV Image Overlaps,” Journal of Unmanned Vehicle Systems, 7 (3), pp. 175-193.

Akturk, E. and Altunel, A.O., 2019, “ Accuracy Assesment of a Low-cost UAV Derived Digital Elevation Model (DEM) in a Highly Broken and Vegetated Terrain,” Measurement, 136, pp. 382-386.

American Society for Photogrammetry and Remote Sensing (ASPRS), 1990, “ASPRS Accuracy Standards for Large-scale Maps,” Photogrammetric Engineering and Remote Sensing, 56 (7), pp. 1068-1070.