Applicability of video-derived bathymetry estimates to nearshore current model predictions

Radermacher, M.; Wengrove, Meagan; Vries, Jaap van Thiel de; Holman, Robert A.

doi:10.2112/si70-049.1

Cited by 19 publications

(11 citation statements)

References 14 publications

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“…Video-based cBathy bathymetry estimates have been compared with vessel-based bathymetry surveys for a range of beaches (Table 1), but rarely with waves bigger than 1.7 m, and never for waves bigger than 2.0 m because of the difficulty of performing in-situ surveys in the presence of large waves. Root mean square differences between cBathy-estimated and surveyed seafloor elevations in previous studies range between 0.51 and 2.05 m (Table 1, Rutten et al, 2017;Radermacher et al, 2014;Holman and Stanley, 2013;Wengrove and Henriquez, 2013;Bergsma et al, 2016)). Errors frequently are largest in shallow water near the shoreline, where (1) linear theory may not be valid; (2) the rapid cross-shore depth changes (over a cBathy sample domain or smoothing distance) cannot be resolved; and (3) wave speed estimates can be distorted by wave runup.…”

Section: Introductionmentioning

confidence: 90%

“…Although in development for more than 20 years, remote sensing methods rarely have been used in applied coastal engineering projects to quantify surfzone bathymetry, and initial tests to calculate surfzone sediment volumes have poor skill (Rutten et al, 2017). A potential application is to use the data as boundary conditions for numerical models of surfzone processes (Radermacher et al, 2014;Díaz M endez et al, 2015;Smith et al, 2017). For example, using remotely sensed data to estimate the position of the sandbar in a surfzone bathymetric grid significantly increases the fidelity of numerical simulations of surfzone circulation (Holman et al, 2014;Wilson et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of video-based linear depth inversion performance and applications using altimeters and hydrographic surveys in a wide range of environmental conditions

Brodie

Palmsten

Hesser

et al. 2018

Coastal Engineering

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The performance of a linear depth inversion algorithm, cBathy, applied to coastal video imagery was assessed using observations of water depth from vessel-based hydrographic surveys and in-situ altimeters for a wide range of wave conditions (0.3 < significant wave height < 4.3 m) on a sandy Atlantic Ocean beach near Duck, North Carolina. Comparisons of video-based cBathy bathymetry with surveyed bathymetry were similar to previous studies (root mean square error (RMSE) ¼ 0.75 m, bias ¼ À0.26 m). However, the cross-shore locations of the surfzone sandbar in video-derived bathymetry were biased onshore 18-40 m relative to the survey when offshore wave heights exceeded 1.2 m or were greater than half of the bar crest depth, and broke over the sandbar. The onshore bias was 3-4 m when wave heights were less than 0.8 m and were not breaking over the sandbar. Comparisons of video-derived seafloor elevations with in-situ altimeter data at three locations onshore of, near, and offshore of the surfzone sandbar over~1 year provide the first assessment of the cBathy technique over a wide range of wave conditions. In the outer surf zone, video-derived results were consistent with long-term patterns of bathymetric change (r 2 ¼ 0.64, RMSE ¼ 0.26 m, bias ¼ À0.01 m), particularly when wave heights were less than 1.2 m (r 2 ¼ 0.83). However, during storms when wave heights exceeded 3 m, video-based cBathy overestimated the depth by up to 2 m. Near the sandbar, the sign of depth errors depended on the location relative to wave breaking, with video-based depths overestimated (underestimated) offshore (onshore) of wave breaking in the surfzone. Wave speeds estimated by video-based cBathy at the initiation of wave breaking often were twice the speeds predicted by linear theory, and up to three times faster than linear theory during storms. Estimated wave speeds were half as fast as linear theory predictions at the termination of wave breaking shoreward of the sandbar. These results suggest that video-based cBathy should not be used to track the migration of the surfzone sandbar using data when waves are breaking over the bar nor to quantify morphological evolution during storms. However, these results show that during low energy conditions, cBathy estimates could be used to quantify seasonal patterns of seafloor evolution.

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Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Evaluation of video-based linear depth inversion performance and applications using altimeters and hydrographic surveys in a wide range of environmental conditions

Brodie

Palmsten

Hesser

et al. 2018

Coastal Engineering

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“…Timeseries of water depth estimates on a 20 Â 10 m analysis grid (alongshore x cross-shore spacing) are then fed into a Kalman filter (Kalman, 1960) in order to reduce noise and make the depth estimates more robust. Applications of the cBathy algorithm to Argus imagery at various field sites and under a range of environmental conditions have demonstrated its capability to resolve nearshore bathymetry with a bulk root-mean-squared error of approximately 50 cm Wengrove et al, 2013;Radermacher et al, 2014;Sembiring et al, 2015;Bergsma et al, 2016;Rutten et al, 2017). Depth estimates were obtained every four hours during daytime since installation of the camera tower in 2013, with the exception of several periods of down-time ( Fig.…”

Section: Remotely-sensed Bathymetrymentioning

confidence: 99%

“…Alternatively, nearshore bathymetry can be estimated operationally using remote sensing techniques. The technical feasibility of coupling remotely-sensed bathymetry to nearshore hydrodynamic predictions was presented by Radermacher et al (2014) and Sembiring et al (2015), successfully demonstrating the potential of this combination. While they report the accuracy of the resulting simulated flow fields at their respective field sites, they do not address the coupling between errors in the remotely-sensed bathymetry and the simulated flow fields.…”

Section: Introductionmentioning

confidence: 97%

“…Traditionally, the accuracy of remotely-sensed bathymetry with respect to in-situ techniques is assessed from bulk error metrics, such as the root-mean-squared error (RMSE), bias and correlation, or from difference maps (Plant et al, 2007;Senet et al, 2008;Van Dongeren et al, 2008;Holman et al, 2013;Rutten et al, 2017). Previous attempts to assess the quality of hydrodynamic predictions on remotely-sensed bathymetry by Radermacher et al (2014) and Sembiring et al (2015) demonstrated the difficulty of linking bathymetric errors to hydrodynamic errors purely based on bulk point-wise error metrics. Nearshore currents do not just depend on the local water depth, but are influenced by bathymetric features that span a range of length scales (Wilson et al, 2013;Plant et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

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Sensitivity of rip current forecasts to errors in remotely-sensed bathymetry

Radermacher

Schipper

Reniers

2018

Coastal Engineering

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Sensitivity of rip current forecasts to errors in remotely-sensed bathymetry Radermacher, M.; de Schipper, M. A.; Reniers, A. J.H.M. A B S T R A C TOperational nearshore current forecasts based on numerical model simulations are gaining popularity as a measure to increase the safety of swimmers. Applying remotely-sensed bathymetry in these model simulations is often proposed in order to cope with rapidly changing nearshore bathymetry. Errors in the remotely-sensed bathymetry may negatively affect performance of the hydrodynamic model. Hence, this study aims to determine the sensitivity of modelled nearshore currents (with a strong focus on rip currents) to errors in remotelysensed bathymetries.The errors in the remotely-sensed bathymetries (depth inversion algorithm applied to video stream) were quantified with a length scale-aware validation technique, providing useful insights in the contribution of pattern and amplitude errors to the total error throughout the analysis domain and over a range of bathymetric length scales. Subsequently, simulations with a nearshore hydrodynamic model were performed, using both in-situ and remotely-sensed bathymetries as an input. A comparison of predicted rip currents on either bathymetry yielded performance statistics for operational current forecasts on remotely-sensed bathymetries, taking the model with in-situ bathymetry as a reference. Linking these performance statistics back to the quantified errors in the remotely-sensed bathymetry finally revealed the relation between errors in flow and bathymetry.Of all rip currents generated on an in-situ bathymetry, 55% were reproduced on the remotely-sensed bathymetry, showing that models predicting nearshore currents on remotely-sensed bathymetry have predictive value. Positive rip current predictions were promoted significantly by accurate reproduction of the pattern and amplitude of nearshore bars at length scales between 200 and 400 m. In contrast to the length-scale aware validation technique applied here, commonly used domain-wide bulk error metrics lack important information about spatial variations in the quality of remotely-sensed bathymetry.

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Sea state from ocean video with singular spectrum analysis and extended Kalman filter

Loizou

Christmas

2021

SIViP

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A method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component of the movement of water in the video, which we propose is associated with the dominant frequency of the ocean. To accomplish this, the singular spectrum analysis algorithm and the extended Kalman filter are used. Then, the shape of an empirical spectrum is used in order to translate the dominant frequency output into a significant wave height estimation.

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Applicability of video-derived bathymetry estimates to nearshore current model predictions

Cited by 19 publications

References 14 publications

Evaluation of video-based linear depth inversion performance and applications using altimeters and hydrographic surveys in a wide range of environmental conditions

Evaluation of video-based linear depth inversion performance and applications using altimeters and hydrographic surveys in a wide range of environmental conditions

Sensitivity of rip current forecasts to errors in remotely-sensed bathymetry

Sea state from ocean video with singular spectrum analysis and extended Kalman filter

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