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Open AccessArticle

UBathy: A New Approach for Bathymetric Inversion from Video Imagery

1
ICM (CSIC), Passeig Marítim de la Barceloneta 37–49, 08003 Barcelona, Spain
2
Polytechnic University of Catalonia BarcelonaTech, Jordi Girona 1–3, 08034 Barcelona, Spain
3
IMEDEA (UIB-CSIC), Carrer Miquel Marqués 21, 07190 Esporles, Spain
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Current address: SOCIB, Parc Bit, 07121 Palma de Mallorca, Spain.
Remote Sens. 2019, 11(23), 2722; https://doi.org/10.3390/rs11232722
Received: 24 October 2019 / Revised: 14 November 2019 / Accepted: 15 November 2019 / Published: 20 November 2019
(This article belongs to the Section Remote Sensing in Geology, Geomorphology and Hydrology)
A new approach to infer the bathymetry from coastal video monitoring systems is presented. The methodology uses principal component analysis of the Hilbert transform of video images to obtain the components of the wave propagation field and their corresponding frequency and wavenumber. Incident and reflected constituents and subharmonics components are also found. Local water depth is then successfully estimated through wave dispersion relationship. The method is first applied to monochromatic and polychromatic synthetic wave trains propagated using linear wave theory over an alongshore uniform bathymetry in order to analyze the influence of different parameters on the results. To assess the ability of the approach to infer the bathymetry under more realistic conditions and to explore the influence of other parameters, nonlinear wave propagation is also performed using a fully nonlinear Boussinesq-type model over a complex bathymetry. In the synthetic cases, the relative root mean square error obtained in bathymetry recovery (for water depths 0.75 m h 8.0 m ) ranges from ∼1% to ∼3% for infinitesimal-amplitude wave cases (monochromatic or polychromatic) to ∼15% in the most complex case (nonlinear polychromatic waves). Finally, the new methodology is satisfactorily validated through a real field site video. View Full-Text
Keywords: video monitoring; bathymetry inversion; Principal Component Analysis video monitoring; bathymetry inversion; Principal Component Analysis
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MDPI and ACS Style

Simarro, G.; Calvete, D.; Luque, P.; Orfila, A.; Ribas, F. UBathy: A New Approach for Bathymetric Inversion from Video Imagery. Remote Sens. 2019, 11, 2722.

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