PERFORMANCE EVALUATION OF BUILDING FAÇADE RECONSTRUCTION FROM UAS IMAGERY
Keywords: Unmanned Aircraft System (UAS), Ground Control Point (GCP), Photogrammetry, Point Cloud, Cloud-to-Cloud (C2C), Accuracy, Reconstruction
Abstract. Unmanned Aircraft Systems (UASs) coupled with low-cost cameras are rapidly becoming a cost-effective alternative for surveying and mapping, particularly for civil, construction, and environmental engineering applications. The proliferation of UASs provide unique opportunities to map and model surfaces at unprecedented spatial and temporal resolutions. Although, UASs have been extensively evaluated for mapping and modeling, limited research has been performed on assessing the accuracy of UAS imagery for building façade reconstruction. In this study, a performance evaluation of UAS mapping for building façade reconstruction is performed. Our results suggest that there are many aspects that impact the accuracy of UAS photogrammetry for building façade reconstruction. In specific, the texture, contrast, and subtle details influence the generated point cloud, thus complicating the building façade reconstruction. The best results were obtained by strategizing the flying height and camera angle; where, the mean, median, and standard deviation for the cloud-to-cloud (C2C) absolute distances were 0.023, 0.014, and 0.023 meters, respectively, by applying a flying height of 150’ with an orbit at 80’. Therefore, it may be concluded that UAS photogrammetric mapping can meet sub-decimeter accuracy for building façade reconstruction, if proper planning, data collection and processing procedures are followed.