Combining UAV-LiDAR and UAV-Photogrammetry for Bridge Assessment and Infrastructure Monitoring

Abstract

Abstract Maintaining the health of strategic infrastructures and bridges is crucial for effective maintenance operations. However, traditional periodical monitoring using elevating platforms is expensive and complex, leading to a search for more efficient and flexible methods. In recent years, there has been a growing adoption of non-invasive approaches such as the use of Unmanned Aerial Vehicles (UAVs) equipped with optical sensors and LiDAR technologies for rapid mapping of the territory. This study presents two methodologies for bridge inspection. The first approach integrates traditional topographic and GNSS techniques with TLS and photogrammetry using cameras mounted on UAV. The second approach involves using a DJI Matrice 300 equipped with a LiDAR DJI Zenmuse L1 sensor for both manual and automatic flights. While the first approach resulted in a centimeter-accurate but time-consuming model, the UAV-LiDAR point cloud's georeferencing accuracy was less accurate in the case of manual flight under the bridge due to GNSS signal obstruction. However, a photogrammetric model reconstruction phase using Ground Control Points and photos taken by the L1-embedded camera improved the overall accuracy of the workflow. This workflow can be used for flexible, low-cost mapping of bridges when medium level accuracy (5–10 cm) is acceptable. Finally, the article presents a solution for integrating the final 3D products interactively into a Bridge Management System environment.