DIGITAL SURFACE MODEL DERIVED FROM UAS IMAGERY ASSESSMENT USING HIGH-PRECISION AERIAL LIDAR AS REFERENCE SURFACE

Abstract. Imagery captured from aerial unmanned systems (UAS) has found significant utility in the field of surveying and mapping as the efforts of the computer vision field combined the principles of photogrammetry. Its respectability in the remote sensing community as increased as the miniaturization of on-board survey-grade global navigation satellite system (GNSS) signal receivers has made it possible to produce high network accuracy contributing to effective aerotriangulation. UAS photogrammetry has gained much popularity because of its effectiveness, efficiency, economy, and especially its availability and ease of use. Although photogrammetry has proven to meet and exceed planimetric precision and accuracy, variables tend to cause deficiencies in the achievement of accuracy in the vertical plane. This research aims to demonstrate achievable overall accuracy of surface modelling through minimization of systematic errors at a significant level using a fixed-wing platform designed for high-accuracy surveying with the eBee Plus and X models by SenseFly equipped with survey-grade GNSS signal-receiving capabilities and 20MP integrated, fixed-focal length camera. The UAS campaign was flown over a site 320 m by 320 m with 81 surveyed 3D ground control points, where horizontal positions were surveyed to 1.0 cm horizontal accuracy and 0.5 cm vertical accuracy using static GNSS methods and digital leveling respectively. All AT accuracy was based on 75 independent checkpoints. The digital surface model (DSM) was compared to a reference DSM generated from high-precision manned aerial LiDAR using the Optech Galaxy scanner. Overall accuracy was in the sub-decimeter level vertically in both commercial software used, including Pix4Dmapper and Agisoft Metashape.