Using unmanned aerial systems for observations of water wave characteristics

Dominant wave components within a wavefield play key hydrodynamic and morphodynamic processes. Herein, we present a method to detect and measure the parameters of these waves, such as their wavelength, propagation angle and period. Image sequences of the free surface are captured with the use of a commercial unmanned aerial system. A snapshot proper orthogonal decomposition analysis is then applied to the image sequence, and a 2D autocorrelation is performed on the resulting modes. By extracting the mode that is representative of the dominant wave signal, it is then possible to infer the wave properties of the dominant wave. The outlined procedure is applied to ocean swells, wind waves, free surface undulations along a river and propagating ship wakes. Our results demonstrate an improvement in the signal-to-noise ratio of the peak wave signal to ambient noise over the more widely used fast Fourier transform approach.

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Publication Details

Journal
Experiments in Fluids
Published
2024-12-04
DOI
https://doi.org/10.1007/s00348-024-03922-w
Citations
1
Primary Topic
Ocean Waves and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.48

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Using unmanned aerial systems for observations of water wave characteristics

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article

Using unmanned aerial systems for observations of water wave characteristics

Mu-Jung Lee, Scott A. Socolofsky, Vivek Bheeroo, Kuang‐An Chang, Soo Bum Bae
article en
1 citations

Abstract

Dominant wave components within a wavefield play key hydrodynamic and morphodynamic processes. Herein, we present a method to detect and measure the parameters of these waves, such as their wavelength, propagation angle and period. Image sequences of the free surface are captured with the use of a commercial unmanned aerial system. A snapshot proper orthogonal decomposition analysis is then applied to the image sequence, and a 2D autocorrelation is performed on the resulting modes. By extracting the mode that is representative of the dominant wave signal, it is then possible to infer the wave properties of the dominant wave. The outlined procedure is applied to ocean swells, wind waves, free surface undulations along a river and propagating ship wakes. Our results demonstrate an improvement in the signal-to-noise ratio of the peak wave signal to ambient noise over the more widely used fast Fourier transform approach.

Experiments in FluidsVol. 66(1)
Texas A&M University (US)
National Oceanic and Atmospheric Administration
Clean water and sanitation
Openalex Percentile: Top 31%
Ocean Waves and Remote Sensing
0.48
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