Nearshore Bathymetry Estimation from Drone Video Using PIV Technique
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This research introduces a novel method to estimate nearshore bottom topography using an unmanned aerial vehicle (UAV), or drone. The UAV was manipulated over the area of interest to film video, and the Particle image velocimetry (PIV) technique was then applied to analyze the video frames in order to retrieve the wave speeds. Under the shallow water conditions, the wave dispersion relation can be simplified in a manner such that when the wave speed is known, the water depth can be inferred. In other words, when wave speed is known, water depth can be inferred. After combining the inferred water depths at multiple points from within the area of interest, the bathymetry was constructed. To validate the method, individual waves were recorded in the nearshore breaking zone during two trials at Freeport, Texas, USA. We measured the significant difference in intensity across the recorded images, as the intensity had a larger signal-to-noise ratio, and this improved the implementation of the PIV algorithm. We then compared the PIVestimated water depth with field measurement and observations, finding that the water depth was overestimated by 13.5%, which was primarily explained by non-linear wave breaking effects. We then introduced a correction factor, reducing the estimation error to within 6% of the true observed water depth. Though there are limitations, this new approach can lower the cost of developing bathymetric maps in the nearshore and result in greater flexibility across space and time. Further improvements in equipment and work on developing better correction factors may result in still greater precision.
Sun, Shih-Heng (2017). Nearshore Bathymetry Estimation from Drone Video Using PIV Technique. Master's thesis, Texas A & M University. Available electronically from