Article

Use of Unmanned Aerial Vehicle Photogrammetry to Obtain Topographical Information to Improve Bridge Risk Assessment

Hackl, J., Adey, B. T., Woźniak, M., and Schümperlin, O. (2018). Use of Unmanned Aerial Vehicle Photogrammetry to Obtain Topographical Information to Improve Bridge Risk Assessment. Journal of Infrastructure Systems, 24(1). doi: 10.1061/(ASCE)IS.1943-555X.0000393

Abstract

Bridges, as all objects in road networks, are built to provide a specified level of service over a specified time period. This level of service ensures that acceptable levels of health, safety, and prosperity of society are guaranteed. The level of service, required from the transportation infrastructure, changes over time, as does the ability of infrastructure to provide it. The extent of maintenance is influenced by gradual deterioration, such as that caused by chloride-induced corrosion of concrete, and sudden deterioration such as that caused by the occurrence of scour resulting from extreme floods. To ensure that infrastructure provides the required service levels, its performance needs to be monitored. Determining how monitoring is to be done is a trade-off between accuracy and cost. Ideally, one will have access to accurate but inexpensive monitoring techniques. This paper contains the results of an investigation into the use of an unmanned aerial vehicle and modern photogrammetric technology to obtain topographical information to apply in bridge risk assessment. The unmanned aerial vehicle was used to take georeferenced images. With the images and photogrammetric technology, a three-dimensional (3D) mesh of the terrain was generated. This mesh was then converted to a computational mesh, which could be used to run computational fluid dynamic simulations during a bridge risk assessment. The investigated bridge was a single span concrete bridge in the Canton of Grisons, Switzerland. The hydraulic events, predicted by the developed model, correspond with historical observations, indicating that the topographical information collected is sufficiently accurate to be used to simulate complex flow situations, which can be used in bridge risk assessments.