Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDB

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address...

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Main Authors: Noam Ginio, Michael Lindenbaum, Barak Fishbain, Dan Liberzon
Format: Article
Language:English
Published: Elsevier 2025-02-01
Series:Data in Brief
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Online Access:http://www.sciencedirect.com/science/article/pii/S2352340924012290
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author Noam Ginio
Michael Lindenbaum
Barak Fishbain
Dan Liberzon
author_facet Noam Ginio
Michael Lindenbaum
Barak Fishbain
Dan Liberzon
author_sort Noam Ginio
collection DOAJ
description Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polarization filter equipped camera as the main sensor and Machine Learning (ML) algorithms for data processing [1,2]. The developed method training and evaluation was based on in-house made supervised dataset. Here we present this supervised dataset of polarimetric images of the water surface coupled with the water surface elevation measurements made by a linear array of resistance-type wave gauges (WG). The water waves were mechanically generated in a laboratory waves basin, and the polarimetric images were captured under an artificial light source. Meticulous camera and WGs calibration and instruments synchronization supported high spatio-temporal resolution. The data set covers several wavefield conditions, from simple monochromatic wave trains of various steepness, to irregular wavefield of JONSWAP prescribed spectral shape and several wave breaking scenarios. The dataset contains measurements repeated in several camera positions relative to the wave field propagation direction.
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issn 2352-3409
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publishDate 2025-02-01
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series Data in Brief
spelling doaj-art-c0168858bc8c4f94bf3b78e324cf9ec02025-01-31T05:11:45ZengElsevierData in Brief2352-34092025-02-0158111267Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDBNoam Ginio0Michael Lindenbaum1Barak Fishbain2Dan Liberzon3Faculty of Civil and Environmental Engineering, Technion, Haifa 320003, Israel; Corresponding author.Faculty of Computer Science, Technion, Haifa 320003, Israel; Interdisciplinary Program for Marine Engineering, Technion 320003 Haifa, IsraelFaculty of Civil and Environmental Engineering, Technion, Haifa 320003, IsraelFaculty of Civil and Environmental Engineering, Technion, Haifa 320003, Israel; Interdisciplinary Program for Marine Engineering, Technion 320003 Haifa, IsraelEffective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polarization filter equipped camera as the main sensor and Machine Learning (ML) algorithms for data processing [1,2]. The developed method training and evaluation was based on in-house made supervised dataset. Here we present this supervised dataset of polarimetric images of the water surface coupled with the water surface elevation measurements made by a linear array of resistance-type wave gauges (WG). The water waves were mechanically generated in a laboratory waves basin, and the polarimetric images were captured under an artificial light source. Meticulous camera and WGs calibration and instruments synchronization supported high spatio-temporal resolution. The data set covers several wavefield conditions, from simple monochromatic wave trains of various steepness, to irregular wavefield of JONSWAP prescribed spectral shape and several wave breaking scenarios. The dataset contains measurements repeated in several camera positions relative to the wave field propagation direction.http://www.sciencedirect.com/science/article/pii/S2352340924012290Spatio-temporal measurementsWater surface elevationWater wavesLight polarizationPolarimetric cameraLight reflection
spellingShingle Noam Ginio
Michael Lindenbaum
Barak Fishbain
Dan Liberzon
Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDB
Data in Brief
Spatio-temporal measurements
Water surface elevation
Water waves
Light polarization
Polarimetric camera
Light reflection
title Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDB
title_full Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDB
title_fullStr Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDB
title_full_unstemmed Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDB
title_short Dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arrayScienceDB
title_sort dataset of polarimetric images of mechanically generated water surface waves coupled with surface elevation records by wave gauges linear arraysciencedb
topic Spatio-temporal measurements
Water surface elevation
Water waves
Light polarization
Polarimetric camera
Light reflection
url http://www.sciencedirect.com/science/article/pii/S2352340924012290
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