Estimation of wave phase speed and nearshore bathymetry from video imagery

Stockdon, Hilary F.; Holman, Robert A.

doi:10.1029/1999jc000124

Cited by 208 publications

(152 citation statements)

References 27 publications

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“…The first is based on variations of the SAR image intensity, which relies on the presence of a current, along with the presence of small-scale waves on the sea surface to provide the radar backscatter (Alpers and Hennings, 1984;Stockdon and Holman., 2000;Calkoen et al, 2001;Yang et al, 2010a;2010b;Fan et al, 2008b;2012). The Bathymetry Assessment System (BAS) is typical of this method, and is based on the theory of imaging processes of underwater bottom topography by SAR as proposed by Alpers and Hennings (Alpers and Hennings, 1984;Calkoen et al, 2001).…”

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confidence: 99%

Estimation of Shallow Water Depth Using HJ-1C S-band SAR Data

2015

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This paper presents a shallow water depth estimation methodology using S-band Synthetic Aperture Radar (SAR) data from the HJ-1C satellite. It is based on the shoaling and refraction of long surface gravity waves as they propagate shoreward. A two-scale Bragg scattering model is used to describe the imaging process of long waves by SAR. By computing the Fast Fourier Transformation (FFT) for the selected sub image, wavelength and direction of the long wave can be retrieved from the two-dimensional (2D) spectra with wave tracking technology. Shallow water depths are then obtained from the linear dispersion relation with the calculated angular wave frequency obtained from other sources or first guesses of initial water depths or wave periods. Applicability and effectiveness are tested in the near-shore area of the Fujian province, China. Comparison between the derived results and water depths from an Electronic Navigational Chart (ENC) indicates that HJ-1C SAR is capable of higher resolution underwater topography detection, and the methodology can be used for shallow water depth estimation with good accuracy. The average absolute error and average relative error of the estimated results is 0·86 m and 11·05%, respectively. K E Y WO R D S 1. Synthetic Aperture Radar (SAR).

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confidence: 99%

Estimation of Shallow Water Depth Using HJ-1C S-band SAR Data

2015

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“…Elles ont été employées pour détecter la forme des bandes sableuses submergées [9], la période et la direction des vagues [10], la localisation de la ligne de côte [13] et la bathymétrie proche de la côte [14]. Comparée à l'emploi de radars ou de capteurs, cette technique a l'avantage d'avoir un faible coût d'installation et d'utilisation [1].…”

Section: Introductionunclassified

Détection de courants marins côtiers à partir de séquences vidéo

et al. 2014

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Abstract. In nearshore applications, the estimation of currents is of primary importance since it controls the sediment transport and coastal evolution. Direct estimation of currents using in-situ instruments is difficult and costly. Low cost remote sensing systems based on video observations constitute a promising alternative when the drifting sea foam left after the passage of breaking waves is visible. Only few methods have been proposed in the literature to take advantage of this.In this paper we describe two new methods: one based on the full video frames and one based on longshore timestacks that necessitates less data. The first approach is an extension of Particle Image Velocimetry method. The second approach uses the Radon transform applied on the time series derived from timestacks to produce an estimate of the longshore component of nearshore surface currents detected from the foam signature in video images.The videos used in this article come from a field campaign conducted in the Mataquito rivermouth area in the Maule region (Chile). They are part of a study on the post-tsunami coastal recovery of the Mataquito area after 2010 Chilean Tsunami. Field tests comparison was also made against in situ current meter from the 2008 Truc Vert experiment in Aquitaine (France). It took place during a tempest which has provoked a sandbar evolution.Résumé. Les courants marins à proximité d'une côte contrôlent le transport de sédiment et son évolution. Or leur estimation par des instruments sur site est difficile et coûteuse. Les systèmes de télédétection reposant sur des observations constituent une alternative prometteuse lorsque la mousse dérivante laissée après le passage de vagues déferlantes est visible. Pourtant, seules quelques méthodes ont été proposées à ce jour dans la littérature.Dans cet article, nous décrivons deux nouvelles méthodes : l'une basée sur les images vidéos considérées dans leur globalité et l'autre basée sur des timestacks le long de la côte. La première approche est une extension de la méthode Particle Image Velocimetry (PIV). La seconde approche produit une estimation de la composante parallèle à la côte des courants de surface en utilisant la transformée de Radon sur des séries temporelles de données en une dimension. Cette dernière nécessite moins de données.Les vidéos utilisées dans cet article proviennent d'une campagne menée sur la zone de l'embouchure de Mataquito dans la région de Maule au Chili. Elles font partie d'une étude sur l'évolution côtière de la zone de Mataquito après le tsunami chilien de 2010. Une comparaison a été également réalisée avec les mesures d'un courantomètre prises lors de la campagne du Truc Vert de 2008 en Aquitaine, France. Elle a eu lieu lors d'une tempête qui a provoqué l'évolution d'une barre sableuse. * Nous remercions la région Lorraine, l'équipe associée franco-chilienne Anestoc-Tosca d'Inria, et le Centre Inria CIRIC au Chili pour leurs financements.

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“…This could be overcome by updating the profile using remote-sensing techniques (e.g. Stockdon and Holman, 2000;Aarninkhof et al, 2005) or data-model assimilation (e.g., van Dongeren et al, 2008, although these techniques are still being developed. Alternatively given the low computation time for each run, confidence intervals could be created around the initial forecasts by running ensembles of the initial bathymetry as well as forcing parameters.…”

Section: Advantages and Limitationsmentioning

confidence: 99%

An Early Warning System for the on-Line Prediction of Coastal Storm Risk on the Italian Coastline

Harley

Valentini²,

Armaroli³

et al. 2012

Int. Conf. Coastal. Eng.

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The ability to predict the imminent arrival of coastal storm risks is a valuable tool for civil protection agencies in order to prepare themselves and, if needs be, execute the appropriate hazard-reduction measures. In this study we present a prototype Early Warning System (EWS) for coastal storm risk on the Emilia-Romagna coastline in Northern Italy. This EWS is run by executing a chain of numerical models (SWAN, ROMS and XBeach) daily, with the final output transformed into a format suitable for decision making by end-users. The storm impact indicator selected for this site is the Safe Corridor Width (SCW), which is a measure of how much dry beach width is available for safe passage by beach users. A three-day time-series of the predicted SCW is generated daily by the prototype EWS. If the minimum SCW exceeds a certain threshold, a warning is issued to end-users via an automated email service. All available prediction information is also updated daily on-line. Over the one year that the EWS has been operating (June 2011 until June 2012), 13 "code red" and 16 "code orange" warnings have been issued, with the remaining 305 predictions indicating low hazard in terms of the SCW. The reliability of the predictions from the perspective of the end-user has meant that the EWS is currently being expanded to include the entire Emilia-Romagna coastline.

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Estimation of wave phase speed and nearshore bathymetry from video imagery

Cited by 208 publications

References 27 publications

Estimation of Shallow Water Depth Using HJ-1C S-band SAR Data

Estimation of Shallow Water Depth Using HJ-1C S-band SAR Data

Détection de courants marins côtiers à partir de séquences vidéo

An Early Warning System for the on-Line Prediction of Coastal Storm Risk on the Italian Coastline

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