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Nearshore Bathymetry Retrieval from Wave-Based Inversion for Video Imagery
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A wavelet-based method for bathymetry retrieval using a sequence of static images of the surface wave field, as obtained from video imagery, is proposed. Synthetic images of the water surface are generated from a numerical Boussinesq type model simulating the propagation of irregular waves. The spectral analysis is used to retrieve both wave periods and wavelengths by evaluating the spectral peaks in the time and spatial domains, respectively. The water depths are estimated using the linear dispersion relation and the results are validated with the model’s bathymetry. To verify the proposed methodology, 2D and 3D simulations considering effects of wave shoaling and refraction were performed for different sea conditions over different seafloors. The method’s ability to reproduce the original bathymetry is shown to be robust in intermediate and shallow waters, being also validated with a real case with images obtained with a shore-based video station. The main improvements of the new method compared to the consideration of a single image, as often used in Satellite Derived Bathymetry, is that the use of successive images enables the consideration of different wave periods, improving depth estimations and not requiring the use of subdomains or filters. This image processing methodology shows very positive results to provide bathymetry maps for shallow marine environments and can be useful to monitor the nearshore with high time- and space-resolution at low cost.
Title: Nearshore Bathymetry Retrieval from Wave-Based Inversion for Video Imagery
Description:
A wavelet-based method for bathymetry retrieval using a sequence of static images of the surface wave field, as obtained from video imagery, is proposed.
Synthetic images of the water surface are generated from a numerical Boussinesq type model simulating the propagation of irregular waves.
The spectral analysis is used to retrieve both wave periods and wavelengths by evaluating the spectral peaks in the time and spatial domains, respectively.
The water depths are estimated using the linear dispersion relation and the results are validated with the model’s bathymetry.
To verify the proposed methodology, 2D and 3D simulations considering effects of wave shoaling and refraction were performed for different sea conditions over different seafloors.
The method’s ability to reproduce the original bathymetry is shown to be robust in intermediate and shallow waters, being also validated with a real case with images obtained with a shore-based video station.
The main improvements of the new method compared to the consideration of a single image, as often used in Satellite Derived Bathymetry, is that the use of successive images enables the consideration of different wave periods, improving depth estimations and not requiring the use of subdomains or filters.
This image processing methodology shows very positive results to provide bathymetry maps for shallow marine environments and can be useful to monitor the nearshore with high time- and space-resolution at low cost.
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