Phase Speed Inversion for Shallow Water Bathymetry Mapping

This study explored the use of top-view movies of propagating gravity water waves to reconstruct the underwater bed profile of shallow water bodies. Water waves of 2.8 and 3.1 Hz were generated by a microcontroller-driven flat flap in a wave flume of dimensions 0.48 × 1.80 × 0.40 m<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula>. Three different bed profiles, i.e., sloped, stepped, and split surfaces, were used to imitate typical seabeds near shorelines. Top-view movies of the propagating waves were recorded and converted to spatial phase-speed images via video analysis. The phase speed images can be used to reconstruct the underwater bed profile using the dispersion relation of linear water waves. We also proposed a demodulation method to correct the phase-speed alteration due to wave interference. The correction method helped improve the mean average percentage error for depth profile predictions from 15% to 10% for the sloped profile and from 45% to 15% for the stepped profile. However, the approach was inferior for the split profile due to wall effects and complex interference patterns. This study suggests the proposed approach can determine the depth level around shorelines using time-evolution or video data with an adequate accuracy of 10% with minimal interference.

Authors

Institutions

Publication Details

Journal
IEEE Journal of Oceanic Engineering
Published
2024-08-16
DOI
https://doi.org/10.1109/joe.2024.3412227
Citations
1
Primary Topic
Underwater Acoustics Research
Type
article
Field-Weighted Citation Impact
0.48
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Phase Speed Inversion for Shallow Water Bathymetry Mapping

Sorasak Danworaphong, Roberto Li Voti, Worakrit Thida
1 citations
IEEE Journal of Oceanic Engineering
Underwater Acoustics Research
0.48
article

Phase Speed Inversion for Shallow Water Bathymetry Mapping

Sorasak Danworaphong, Roberto Li Voti, Worakrit Thida
article en
1 citations

Abstract

This study explored the use of top-view movies of propagating gravity water waves to reconstruct the underwater bed profile of shallow water bodies. Water waves of 2.8 and 3.1 Hz were generated by a microcontroller-driven flat flap in a wave flume of dimensions 0.48 × 1.80 × 0.40 m<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^{3}$</tex-math></inline-formula>. Three different bed profiles, i.e., sloped, stepped, and split surfaces, were used to imitate typical seabeds near shorelines. Top-view movies of the propagating waves were recorded and converted to spatial phase-speed images via video analysis. The phase speed images can be used to reconstruct the underwater bed profile using the dispersion relation of linear water waves. We also proposed a demodulation method to correct the phase-speed alteration due to wave interference. The correction method helped improve the mean average percentage error for depth profile predictions from 15% to 10% for the sloped profile and from 45% to 15% for the stepped profile. However, the approach was inferior for the split profile due to wall effects and complex interference patterns. This study suggests the proposed approach can determine the depth level around shorelines using time-evolution or video data with an adequate accuracy of 10% with minimal interference.

IEEE Journal of Oceanic EngineeringVol. 49(4)
Sapienza University of Rome (IT), King Mongkut's Institute of Technology Ladkrabang (TH), Walailak University (TH)
Openalex Percentile: Top 35%
Underwater Acoustics Research
0.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.