研究目的
To develop and validate an imaging-based method for estimating nearshore bathymetry in the surf zone using a consumer drone and particle image velocimetry (PIV) technique.
研究成果
The study successfully demonstrated a low-cost, imaging-based method for mapping nearshore bathymetry and surface velocity fields using a consumer drone and PIV technique, with an RMSE of 0.132 m. A correction factor of 1.02 was suggested to account for wave nonlinearity. This approach offers flexibility and cost-effectiveness for coastal surveys, particularly after extreme events, but further validation and improvements with high-end equipment are recommended.
研究不足
The method is limited to the surf zone where breaking waves provide clear texture for PIV analysis; it may not work well in deep water or areas without wave breaking. Accuracy is affected by camera quality, drone stability, and environmental conditions like wind and glare. Requires sufficient daylight and minimal glare for optimal imaging.
1：Experimental Design and Method Selection:
The methodology involves using a consumer drone to capture video imagery of the surf zone, applying PIV to analyze wave celerity, and using the shallow water approximation of the linear-wave dispersion relation to invert water depth.
2：Sample Selection and Data Sources:
Three field experiments were conducted at different beach sites in Freeport, Texas, on different dates, with video imagery collected by the drone.
3：List of Experimental Equipment and Materials:
DJI Phantom 3 Professional drone with integrated camera and GPS, total station for validation, yard stick for manual depth measurements, and software for PIV analysis (LaVision Inc. software and in-house MPIV software).
4：Experimental Procedures and Operational Workflow:
The drone was flown at heights of 47-56 m to record video for at least 5 minutes per experiment. Images were undistorted and processed with PIV to obtain velocity maps, from which wave celerity was extracted. Water depth was calculated using the dispersion relation, and results were validated against total station and manual measurements.
5：Data Analysis Methods:
PIV analysis with cross-correlation and minimum quadratic differences schemes, application of a correction factor for wave nonlinearity, and calculation of RMSE for accuracy assessment.
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