Determination of Bathymetry Using Marine Radar Images of Waves

Bell, Paul S.

doi:10.1061/40604(273)26

Cited by 6 publications

(6 citation statements)

References 5 publications

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“…At Porthtowan, median depth estimates deviate more from the ground truth but remain ∆d < 2.0 m for depths d < 10 m (Figure 8b). Errors are largest in the breaking region where depths are d = 2 − 3 m, which is a common observation in depth inversion studies e.g., [92]. This is similar for Narrabeen (Figure 8d).…”

Section: Resultssupporting

confidence: 73%

A Self-Adaptive Method for Mapping Coastal Bathymetry On-The-Fly from Wave Field Video

2021

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Mapping coastal bathymetry from remote sensing becomes increasingly more attractive for the coastal community. It is facilitated by a rising availability of drone and satellite data, advances in data science, and an open-source mindset. Coastal bathymetry, but also wave directions, celerity and near-surface currents can simultaneously be derived from aerial video of a wave field. However, the required video processing is usually extensive, requires skilled supervision, and is tailored to a fieldsite. This study proposes a video-processing algorithm that resolves these issues. It automatically adapts to the video data and continuously returns mapping updates and thereby aims to make wave-based remote sensing more inclusive to the coastal community. The code architecture for the first time includes the dynamic mode decomposition (DMD) to reduce the data complexity of wavefield video. The DMD is paired with loss-functions to handle spectral noise and a novel spectral storage system and Kalman filter to achieve fast converging measurements. The algorithm is showcased for fieldsites in the USA, the UK, the Netherlands, and Australia. The performance with respect to mapping bathymetry was validated using ground truth data. It was demonstrated that merely 32 s of video footage is needed for a first mapping update with average depth errors of 0.9–2.6 m. These further reduced to 0.5–1.4 m as the videos continued and more mapping updates were returned. Simultaneously, coherent maps for wave direction and celerity were achieved as well as maps of local near-surface currents. The algorithm is capable of mapping the coastal parameters on-the-fly and thereby offers analysis of video feeds, such as from drones or operational camera installations. Hence, the innovative application of analysis techniques like the DMD enables both accurate and unprecedentedly fast coastal reconnaissance. The source code and data of this article are openly available.

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Section: Resultssupporting

confidence: 73%

A Self-Adaptive Method for Mapping Coastal Bathymetry On-The-Fly from Wave Field Video

2021

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“…Although conceptually proven, these early developments were applied to limited datasets and lacked quantitative validation. Later, based on two single daily-averaged estimates from Egmond aan Zee (NL) and Teignmouth Pier (UK), Bell (2001) demonstrated that error margins could be within 1 m accuracy for depths up to 12 m, with exception of the breaker zone where errors were approximately 2 m.…”

Section: Introductionmentioning

confidence: 99%

The application of a radar-based depth inversion method to monitor near-shore nourishments on an open sandy coast and an ebb-tidal delta

Gawehn

Dongeren

Vries

et al. 2020

Coastal Engineering

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“…Stockdon and Holman, 2000;Plant and Holman, 1997] or radars [e.g. Bell, 1999;Bell, 2001] have been employed for temporal coastal imaging supported by digital technologies and becoming popular for continuous monitoring. Video cameras can monitor sea surface patterns with high temporal resolution and can provide color images, which enable the detection of wave breaking, suspension of foams, sediment concentrations, etc.…”

Section: Aim Of the Studymentioning

confidence: 99%

Wave Run-Up Analyses Under Dissipative Condition UsingX-Band Radar

Hasan

Takewaka

2009

Coastal Engineering Journal

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An X-band nautical radar system was employed to examine wave run-up during a typhoon around the research pier HORS in Hasaki, Japan. Analyses on radar echo images were done to estimate the spatio-temporal variation of water fronts by manually digitizing cross-shore time stack images. Digitized instantaneous water fronts were validated with wave gauge measurements with an acceptable agreement. Longshore distribution of mean shoreline positions and inter-tidal foreshore slopes were then estimated using time-averaged images. Run-up, the height of discrete water level maxima, was estimated from the digitized water fronts with the help of foreshore profile. Run-up variations under dissipative condition were parameterized with surf similarity parameter. Low frequency variances in the run-up motion were observed, which travelled in the longshore direction.

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Determination of Bathymetry Using Marine Radar Images of Waves

Cited by 6 publications

References 5 publications

A Self-Adaptive Method for Mapping Coastal Bathymetry On-The-Fly from Wave Field Video

A Self-Adaptive Method for Mapping Coastal Bathymetry On-The-Fly from Wave Field Video

The application of a radar-based depth inversion method to monitor near-shore nourishments on an open sandy coast and an ebb-tidal delta

Wave Run-Up Analyses Under Dissipative Condition UsingX-Band Radar

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