Uas-Based Airport Maintenance Inspections: Lessons Learned From Pilot Study Implementation

Unmanned aircraft systems (UAS) can be used to collect visual assets such as 2D geo-referenced and infrared images. These 2D images can be converted into 3D point clouds through the UAS photogrammetry process. Such point clouds can then be utilized to detect obstructions around airports. This research describes the process of data collection, using UAS at airports to analyze point cloud data and document the potential implications of UAS-based airport inspections. Two field tests were conducted and three different UAS platforms were deployed. The Point Cloud Library (PCL) was employed to detect and measure trees around runways. The main contribution of this study is the provision of an overview of how UAS and visual assets can be used for airport inspections, in order to improve work efficiency and reduce human error.