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Open AccessArticle

Storm Event to Seasonal Evolution of Nearshore Bathymetry Derived from Shore-Based Video Imagery

1
CNES-LEGOS, UMR-5566, 14 Avenue Edouard Belin, 31400 Toulouse, France
2
CPRG, School of Biological and Marine Sciences, University of Plymouth, Drake Circus, Plymouth PL4 8AA, UK
3
IRD-LEGOS, UMR-5566, 14 Avenue Edouard Belin, 31400 Toulouse, France
*
Author to whom correspondence should be addressed.
Current address: Laboratoire d’Etudes en Géophysique et Océanographie Spatiales (LEGOS), 14 Avenue Edouard Belin, 31400 Toulouse, France.
Remote Sens. 2019, 11(5), 519; https://doi.org/10.3390/rs11050519
Received: 22 January 2019 / Revised: 22 February 2019 / Accepted: 26 February 2019 / Published: 4 March 2019
(This article belongs to the Section Ocean Remote Sensing)
Coastal evolution occurs on a wide range of time-scales, from storms, seasonal and inter-annual time-scales to longer-term adaptation to changing environmental conditions. Measuring campaigns typically either measure morphological evolution on a short-time scale (days) with high frequency (hourly) or long-time scales (years) but intermittently (monthly). This leaves an important observational gap that limits morphological variability assessments. Traditional echo sounding measurements on this long time-scale and high-frequency sampling require a significant financial injection. Shore-based video systems with high spatiotemporal resolution can bridge this gap. For the first time, hourly Kalman filtered video-derived bathymetries covering 1.5 years of morphological evolution with an hourly resolution obtained at Porhtowan, UK are presented. Here, the long-term hourly dataset is used and aims to show its added value for, and provide an in-depth, morphological analyses with unprecedented temporal resolution. The time-frame includes calm and extreme (storm) wave conditions in a macro-tidal environment. The video-derived bathymetries allow hourly beach state classification while before this was not possible due to the dependence on foam patterns of wave breaking (e.g., saturation during storms). The study period covers extreme storm erosion during the most energetic winter season in 60 years (2013–2014). Recovery of the beach takes place on several time-scales: (1) an immediate initial recovery after the storm season (first 2 months), (2) limited recovery during low energetic summer conditions and (3) accelerated recovery as the wave conditions picked up in the subsequent fall—under wave conditions that are typically erosive. The video-derived bathymetries are shown to be effective in determining bar-positions, outer-bar three-dimensionality and volume analyses with an unprecedented hourly temporal resolution. View Full-Text
Keywords: beach morphodynamics; remote sensing; bathymetry inversion; multi-scale monitoring beach morphodynamics; remote sensing; bathymetry inversion; multi-scale monitoring
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MDPI and ACS Style

Bergsma, E.W.J.; Conley, D.C.; Davidson, M.A.; O'Hare, T.J.; Almar, R. Storm Event to Seasonal Evolution of Nearshore Bathymetry Derived from Shore-Based Video Imagery. Remote Sens. 2019, 11, 519. https://doi.org/10.3390/rs11050519

AMA Style

Bergsma EWJ, Conley DC, Davidson MA, O'Hare TJ, Almar R. Storm Event to Seasonal Evolution of Nearshore Bathymetry Derived from Shore-Based Video Imagery. Remote Sensing. 2019; 11(5):519. https://doi.org/10.3390/rs11050519

Chicago/Turabian Style

Bergsma, Erwin W.J.; Conley, Daniel C.; Davidson, Mark A.; O'Hare, Tim J.; Almar, Rafael. 2019. "Storm Event to Seasonal Evolution of Nearshore Bathymetry Derived from Shore-Based Video Imagery" Remote Sens. 11, no. 5: 519. https://doi.org/10.3390/rs11050519

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