ASSESSING THE ACCURACY OF GEOREFERENCED POINT CLOUDS FROM UAS IMAGERY
- 1Civil Engineering Department, California State Polytechnic University, Pomona, USA
- 2Department of Computer Science, California State Polytechnic University, Pomona, USA
Keywords: Unmanned Aircraft System (UAS), Ground Control Point (GCP), Photogrammetry, Accuracy, Root Mean Square Error (RMSE), Point Clouds
Abstract. Unmanned Aircraft System (UAS) mapping methods determine the three-dimensional (3D) position of surface features. UAS mapping is often used, compared to traditional mapping techniques, such as the total station (TS), Global Navigation Satellite System (GNSS) and terrestrial laser scanning (TLS). Traditional mapping methods have become less favourable due to efficiency and cost, especially for medium to large areas. As UAS mapping increases in popularity, the need to verify its accuracy for topographic mapping is evident. In this study, an assessment of the accuracy of UAS mapping is performed. Our results suggest that there are many factors that affect the accuracy of UAS photogrammetry products. In specific, the distribution and density of ground control points (GCPs) are particularly significant for a study area of 2.861 km2 in size. The best results were obtained by strategizing the distribution and density of GCPs; where, the root mean square error (RMSE) for the X, Y, Z, and 3D was minimized to 0.012, 0.021, 0.038, and 0.045 meters, respectively, by applying a total of 15 GCPs in the aerotriangulation. Therefore, it may be concluded that UAS photogrammetric mapping can meet sub-decimeter accuracy for topographic mapping, if proper planning, data collection and processing procedures are followed.