Intertidal Bathymetry Estimation Using Video Images on a Dissipative Beach

Sobral, Fernando; Pereira, Pedro; Cavalcanti, Pablo G.; Guedes, Rafael Marcondes Carvalho; Calliari, Lauro Júlio

doi:10.2112/si65-243.1

Cited by 9 publications

(7 citation statements)

References 13 publications

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“…In addition to morphodynamic-zone studies, the technique can support the use of existing stand-alone automated procedures for coastal image analysis. Specific areas of the image can be previously extracted and/or masked to fasten, for instance, wave breaking height [25,45,46], rip currents [47][48][49][50], shoreline detection [35,[51][52][53][54], wave runup measurements [30,35,[55][56][57][58][59][60][61][62], and intertidal beach topography [28,29,36,61,[63][64][65][66]. The use of the technique can also be coupled to the existing algorithm that focus on beach morphological features detection [67][68][69][70][71] for a fully description of coastal area from coastal imaging.…”

Section: Discussionmentioning

confidence: 99%

Nearshore Wave Transformation Domains from Video Imagery

Andriolo¹

2019

JMSE

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Within the nearshore area, three wave transformation domains can be distinguished based on the wave properties: shoaling, surf, and swash zones. The identification of these distinct areas is relevant for understanding nearshore wave propagation properties and physical processes, as these zones can be related, for instance, to different types of sediment transport. This work presents a technique to automatically retrieve the nearshore wave transformation domains from images taken by coastal video monitoring stations. The technique exploits the pixel intensity variation of image acquisitions, and relates the pixel properties to the distinct wave characteristics. This allows the automated description of spatial and temporal extent of shoaling, surf, and swash zones. The methodology was proven to be robust, and capable of spotting the three distinct zones within the nearshore, both cross-shore and along-shore dimensions. The method can support a wide range of coastal studies, such as nearshore hydrodynamics and sediment transport. It can also allow a faster and improved application of existing video-based techniques for wave breaking height and depth-inversion, among others.

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Section: Discussionmentioning

confidence: 99%

Nearshore Wave Transformation Domains from Video Imagery

Andriolo¹

2019

JMSE

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“…Time-series of individual radar pixel intensities are gathered from hourly time-averaged images across the selected timescale of two weeks, including a full spring-neap cycle (as an example, June [17][18][19][20][21][22][23][24][25][26][27][28][29][30]2005). Figure 6a displays the cross-shore time stack images within the range between y = 5 m and y = 103 m. The red line marked in Figure 6b indicates the variation of the instantaneous waterline position digitized manually by visual inspection, and Figure 6c is the concurrent tidal records.…”

Section: Intertidal Beach Profile and Shoreline Estimation Using Twm mentioning

confidence: 99%

“…It can also be employed to track the sea surface features with high temporal resolution, as usual contributing several images per second in addition to trace stretches of intertidal sandy beaches at some sites around the world. Several video monitoring techniques have been used for the long-term monitoring of shoreline positions and nearshore beach processes [12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

“…The pixel intensities over two weeks(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) June 2005) at 49 m and (a) 22 m, (b) 27.5 m, (c) 33 m, and (d) 38 m. (e) The tidal binary signal indicating above or below water level −0.2 m: (f) water level 0.0 m and (g) water level 0.2 m. The tables on the right-hand side of a-g illustrate the correlation coefficients between the pixel intensity variation and tidal binary signals. Higher correlation values show strong similarities between pixel intensity variation and binary signal representation of tide records.…”

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confidence: 99%

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Automatic Shoreline Position and Intertidal Foreshore Slope Detection from X-Band Radar Images Using Modified Temporal Waterline Method with Corrected Wave Run-up

Kumar

Takewaka

2019

JMSE

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Automatic and accurate shoreline position and intertidal foreshore slope detection are challenging and significantly important for coastal dynamics. In the present study, a time series shoreline position and intertidal foreshore slope have been automatically detected using modified Temporal Waterline Method (mTWM) from time-averaged X-band radar images captured throughout the course of two-week tidal cycle variation over an area spanning 5.6 km on the Hasaki coast between 12 April 2005 and 31 December 2008. The methodology is based on the correlation map between the pixel intensity variation of the time-averaged X-band radar images and the binary signal of the tide level ranging from −0.8 m to 0.8 m. In order to ensure the binary signal represented each of the water levels in the intertidal shore profile, determining the water level direction-wise bottom elevation is considered as the modification. Random gaps were detected in the captured images owing to the unclear or oversaturation of the waterline signal. A horizontal shift in the detected shoreline positions was observed compared to the survey data previously collected at Hasaki Oceanographical Research Station (HORS). This horizontal shift can be attributed to wave breaking and high wave conditions. Wave set-up and run-up are the effects of wave breaking and high wave conditions, respectively. The correction of the wave set-up and run-up is considered to allow the upward shift of the water level position, as well as shoreline position, to the landward direction. The findings indicate that the shoreline positions derived by mTWM with the corrected wave run-up reasonably agree with the survey data. The mean absolute bias (MAB) between the survey data and the shoreline positions detected using mTWM with the corrected wave run-up is approximately 5.9 m, which is theoretically smaller than the spatial resolution of the radar measurements. The random gaps in the mTWM-derived shoreline positions are filled by Garcia’s data filling algorithm which is a Penalized Least Squares regression method by means of the Discrete Cosine Transform (PLS-DCT). The MAB between survey data and the gap filled shoreline positions detected using TWM with corrected wave run-up is approximately 5.9 m. The obtained results indicate the accuracy of the mTWM with corrected wave run-up integrated with Garcia’s method compared to the survey observations. The executed approach in this study is considered as an efficient and robust tool to automatically detect shoreline positions and intertidal foreshore slopes extracted from X-band radar images with the consideration of wave run-up correction.

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“…O vídeo imageamento tem se tornado mundialmente utilizado na realização de estudos sobre ambientes costeiros (HOL-MAN & GUZA, 1984;HOLLAND & HOLMAN, 1996;PEREIRA et al, 2011). Este método é repleto de sinais visuais cujo principal objetivo é investigar variações que ocorrem a curto prazo, compreendendo implicações a longo termo (PEREIRA et al, 2012;SOBRAL et al, 2013). Estudos sobre morfodinâmica do espraiamento tem sido bastante divulgados e aperfeiçoados (STAN-CANELLI et al, 2011).…”

Section: Sistema De Monitoramento Por Vídeo Imagensunclassified

Aspectos Sobre O Estado Da Arte De Estudos Da Zona De Espraiamento

Vicente

Pereira

2017

Rev. Bras. Geomorfol.

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Resumo:Dentro do ambiente praial, a zona de espraiamento pode ser considerada como o sub-região mais dinâmico da zona costeira. Muito disso se deve ao fato do espraiamento representar as respostas dos processos hidrodinâmicos externos ocorridos em regiões anteriores a este subambiente (zona de arrebentação e surfe). Assim, o clima de ondas e a amplitude da maré são variáveis indispensáveis nos estudos que tem buscado cada vez mais a quantifi cação destes fenômenos. Os métodos utilizados nestes estudos acompanham a evolução tecnológica dos dias atuais empregando desde de ferramentas de medição in situ, sinais acústicos, sensoriamento remoto, e outros que utilizam técnicas sofi sticadas de lasers e scanners. Com isso, é possível a obtenção de uma gama de dados sufi cientes para que sejam aplicadas abordagens multidisciplinares com enfoque nos processos físicos da interpretação dos resultados. São considerados processos como o transporte de sedimentos e suas implicações, infi ltração/exfi ltração de água na face praial, assim como a saturação, a infl uência da declividade observada no perfi l praial, componentes e feições morfológicas são focalizados nestes estudos. Desse modo, foi comprovado que a depender do estágio praial, determinado movimento no ciclo do espraiamento irá infl uenciar de maneira mais direta a evolução morfológica, como também o desenvolvimento de feições características. Todos estes resultados buscam compreender a relação existente entre a evolução de um determinado processo e as variações dentro da zona de espraiamento. Com a avaliação dos estudos, observa-se a importância desta faixa para o desenvolvimento morfológico da região subaérea praial, uma vez que esta faixa determina toda variação que ocorrerá no perfi l. Os trabalhos também direcionam novos rumos para as pesquisas relacionadas ao espraiamento, sendo necessárias abordagens cada vez mais precisas e detalhadas deste ambiente,

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Intertidal Bathymetry Estimation Using Video Images on a Dissipative Beach

Cited by 9 publications

References 13 publications

Nearshore Wave Transformation Domains from Video Imagery

Nearshore Wave Transformation Domains from Video Imagery

Automatic Shoreline Position and Intertidal Foreshore Slope Detection from X-Band Radar Images Using Modified Temporal Waterline Method with Corrected Wave Run-up

Aspectos Sobre O Estado Da Arte De Estudos Da Zona De Espraiamento

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