FACA v1 - Fully Automated Co-Alignment of UAV point clouds

Abstract

We introduce FACA - Fully Automated Co-Alignment, an open-source software program designed to fully automate the workflow for co-aligning point clouds derived from unoccupied aerial vehicle (UAV) images using photogrammetry. We developed FACA to efficiently evaluate fieldwork with UAVs on landslides and coastal dynamics. The software applies to any research requiring comparative, precise, and rapid multi-temporal point cloud generation from UAV imagery. Unoccupied aerial vehicles are an essential element in most contemporary applied geosciences research toolkits. Typical products of UAV flights are point clouds created with photogrammetry, which are used to measure objects and their change if multi-temporal data exists. Ground control points (GCPs) are considered the best method to increase the precision and accuracy of point clouds, but placing and measuring them is not always feasible during fieldwork. Co-alignment leads to the local precise alignment of multiple point clouds without GCPs. Fully Automated Co-Alignment uses Agisoft Metashape Pro and the Python standard library. The GPLv3 licensed FACA source code focuses on extendability, modifiability, and readability. Our software works interchangeably from the command line or a custom graphical user interface. We distribute the software with both usage and installation instructions. Three multi-temporal test datasets are available. We demonstrate the utility and versatility of FACA v1 with a multi-year and -region dataset acquired along Germany's Baltic Sea coast. FACA is in continuous open development.