Assessment of Positional Accuracy in Maps Derived Using UAV_PPK, UAV Network RTK, RTKGNSS, and TUSAGA-Active Techniques

Abstract

Accurate spatial positioning is essential for many geospatial applications, particularly those requiring high precision. This study evaluates the positional accuracy of maps derived from Unmanned Aerial Vehicle (UAV) data by comparing them with Ground Control Points (GCPs) established using a high-precision electronic total station. Four positioning methods were assessed: Real-Time Kinematic (RTK), TUSAGA-Active (Turkish National Permanent GNSS Network – Active), UAV Post-Processed Kinematic (UAV_PPK), and UAV Network RTK. Accuracy was evaluated regarding horizontal and vertical deviations using standard deviation (SD) and root mean square error (RMSE) metrics. Among the tested methods, RTK demonstrated the highest positional accuracy under the tested conditions, whereas UAV_PPK exhibited the lowest, particularly in vertical positioning. RTK consistently yielded horizontal and vertical RMSE values below 25 mm, while UAV_PPK produced errors exceeding 60 mm in horizontal and reaching up to 115 mm in vertical components. These findings indicate that although UAV-based techniques provide operational efficiency, integrating accurately surveyed GCPs remains critical for achieving reliable spatial accuracy. The study emphasizes the importance of selecting appropriate positioning methods based on project-specific accuracy requirements and supports further research to optimize UAV-based mapping workflows.