UAS Point Cloud Accuracy Assessment Using Structure from Motion–Based Photogrammetry and PPK Georeferencing Technique for Building Surveying Applications

Abstract

Construction researchers and professionals have shown increased interest and need to enhance the accuracy of unmanned aerial system (UAS)-generated point cloud data (PCD) and ideally improve this technology's integration within construction practices. High-accuracy PCD are required for a variety of construction practices, including building surveying applications. This study aims to investigate the effect of single- and dual-frequency types of global navigation satellite systems (GNSSs) together with postprocessing kinematic (PPK) technique on the accuracy of the UAS-generated PCD in a building surveying application. The paper first discusses the customization of an open-source UAS platform equipped with a dual-frequency GNSS that is capable of georeferencing captured data using PPK technology. Then a comparative PCD accuracy assessment is conducted through a building surveying experiment with three UAS configurations and conditions: (1) UAS with dual-frequency GNSS and PPK, (2) UAS with dual-frequency GNSS without PPK, and (3) UAS with single-frequency GNSS without PPK. Ground sampling distance (GSD) and camera angle parameters were also considered in the experimental assessment to better understand their effects on the generated PCD accuracies. The outcomes of this experiment led to the development of a PCD accuracy matrix that illustrates the effect of those UAS technical configurations and flight parameters on the level of PCD accuracy.