Determining the limits of unmanned aerial photogrammetry for the evaluation of road runoff

Abstract

The accuracy of point cloud data in runoff evaluation is a non-resolved question. The increasingly use of unmanned aerial photogrammetric systems shows great opportunities, although they provide less accuracy data than traditional survey systems. This manuscript presents a new method to check the usage limits of point clouds obtained from unmanned aerial photogrammetry in runoff evaluation. The methodology uses D8 algorithm for the runoff estimation. The quality of photogrammetric data is evaluated by comparison with a light detection and ranging scanning dataset that acts as ground truth. The methodology includes point cloud rasterization, with pixel cells ranging from 0.25m to 5m. Five test zones are selected from the road pavement and five from the road slopes. Results show that the runoff evaluation from the unmanned aerial photogrammetric data diverges from the mobile light detection and ranging data as cell size decreases and resolution increases. Studies that require cell sizes below 1m are very influenced by the lower accuracy of the photogrammetric point clouds. However, the unmanned aerial surveys in larger areas with cell sizes above 2m are perfectly affordable for this type of technology, without implication in the quality of runoff results.