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Intercomparison of surface velocimetry techniques for drone-based marine current characterization

Iain Fairley, Nicholas King, Jason McIlvenny Orcid Logo, Matthew Lewis, Simon Neill Orcid Logo, Benjamin J. Williamson Orcid Logo, Ian Masters Orcid Logo, Dominic Reeve Orcid Logo

Estuarine, Coastal and Shelf Science, Volume: 299

Swansea University Authors: Iain Fairley, Nicholas King, Ian Masters Orcid Logo, Dominic Reeve Orcid Logo

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DOI (Published version): 10.1016/j.ecss.2024.108682

Abstract

Mapping tidal currents is important for a variety of coastal and marine applications. Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive....

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Published in: Estuarine, Coastal and Shelf Science
ISSN: 0272-7714
Published: Elsevier BV 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa65660
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Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive. Previous application of particle image velocimetry to tidal current measurements demonstrated that accuracy depends on site and environmental conditions. This study compares surface velocimetry techniques across a range of these conditions. Various open-source tools and image pre-processing methods were applied to six sets of videos and validation data that cover a variety of site and weather conditions. When wind-driven ripples are present in imagery, it was found a short-wave celerity inversion performed best, with mean absolute percentage error (MAPE) of 5–6% compared to surface drifters. During lower wind speeds, current-advected surface features are visible and techniques which track these work best, of which the most appropriate technique depends on specifics of the collected imagery; MAPEs of 9–21% were obtained. This work has quantified accuracy and demonstrated that surface current maps can be obtained from drones under both high and low wind speeds and at a variety of sites. By following these suggested approaches, practitioners can use drones as a current mapping tool at coastal and offshore sites with confidence in the outputs.</abstract><type>Journal Article</type><journal>Estuarine, Coastal and Shelf Science</journal><volume>299</volume><journalNumber/><paginationStart/><paginationEnd/><publisher>Elsevier BV</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>0272-7714</issnPrint><issnElectronic/><keywords>Drones; Tidal currents; Surface velocimetry; Particle image velocimetry; Particle tracking velocimetry; Optical flow</keywords><publishedDay>1</publishedDay><publishedMonth>4</publishedMonth><publishedYear>2024</publishedYear><publishedDate>2024-04-01</publishedDate><doi>10.1016/j.ecss.2024.108682</doi><url/><notes/><college>COLLEGE NANME</college><department>Science and Engineering - Faculty</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>FGSEN</DepartmentCode><institution>Swansea University</institution><apcterm>Another institution paid the OA fee</apcterm><funders>The financial support of the Selkie Project is acknowledged. The Selkie Project is funded by the European Regional Development Fund through the Ireland Wales Cooperation programme. The authors would also like to acknowledge the financial support of the EPSRC Supergen ORE Hub (EP/S000747/1) funded V-SCORES project and the support of SEEC (Smart Efficient Energy Centre) at Bangor University, part-funded by the European Regional Development Fund (ERDF), administered by the Welsh Government. 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spelling v2 65660 2024-02-21 Intercomparison of surface velocimetry techniques for drone-based marine current characterization 568e6f260489dc8139afe77757553513 Iain Fairley Iain Fairley true false 2305b5d9c024cf97a2feeb832af9228b Nicholas King Nicholas King true false 6fa19551092853928cde0e6d5fac48a1 0000-0001-7667-6670 Ian Masters Ian Masters true false 3e76fcc2bb3cde4ddee2c8edfd2f0082 0000-0003-1293-4743 Dominic Reeve Dominic Reeve true false 2024-02-21 FGSEN Mapping tidal currents is important for a variety of coastal and marine applications. Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive. Previous application of particle image velocimetry to tidal current measurements demonstrated that accuracy depends on site and environmental conditions. This study compares surface velocimetry techniques across a range of these conditions. Various open-source tools and image pre-processing methods were applied to six sets of videos and validation data that cover a variety of site and weather conditions. When wind-driven ripples are present in imagery, it was found a short-wave celerity inversion performed best, with mean absolute percentage error (MAPE) of 5–6% compared to surface drifters. During lower wind speeds, current-advected surface features are visible and techniques which track these work best, of which the most appropriate technique depends on specifics of the collected imagery; MAPEs of 9–21% were obtained. This work has quantified accuracy and demonstrated that surface current maps can be obtained from drones under both high and low wind speeds and at a variety of sites. By following these suggested approaches, practitioners can use drones as a current mapping tool at coastal and offshore sites with confidence in the outputs. Journal Article Estuarine, Coastal and Shelf Science 299 Elsevier BV 0272-7714 Drones; Tidal currents; Surface velocimetry; Particle image velocimetry; Particle tracking velocimetry; Optical flow 1 4 2024 2024-04-01 10.1016/j.ecss.2024.108682 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University Another institution paid the OA fee The financial support of the Selkie Project is acknowledged. The Selkie Project is funded by the European Regional Development Fund through the Ireland Wales Cooperation programme. The authors would also like to acknowledge the financial support of the EPSRC Supergen ORE Hub (EP/S000747/1) funded V-SCORES project and the support of SEEC (Smart Efficient Energy Centre) at Bangor University, part-funded by the European Regional Development Fund (ERDF), administered by the Welsh Government. M Lewis also wishes to acknowledge the EPSRC fellowship METRIC: EP/R034664/1. 2024-03-26T14:36:49.1585559 2024-02-21T15:37:30.5930165 Faculty of Science and Engineering School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering Iain Fairley 1 Nicholas King 2 Jason McIlvenny 0000-0002-5342-7003 3 Matthew Lewis 4 Simon Neill 0000-0002-1674-3445 5 Benjamin J. Williamson 0000-0002-7107-7713 6 Ian Masters 0000-0001-7667-6670 7 Dominic Reeve 0000-0003-1293-4743 8 65660__29857__6c387117db474445ac4c88dbb09922dd.pdf 65660.VOR.pdf 2024-03-26T14:31:52.4425494 Output 10958582 application/pdf Version of Record true © 2024 The Authors. This is an open access article under the CC BY license. true eng http://creativecommons.org/licenses/by/4.0/
title Intercomparison of surface velocimetry techniques for drone-based marine current characterization
spellingShingle Intercomparison of surface velocimetry techniques for drone-based marine current characterization
Iain Fairley
Nicholas King
Ian Masters
Dominic Reeve
title_short Intercomparison of surface velocimetry techniques for drone-based marine current characterization
title_full Intercomparison of surface velocimetry techniques for drone-based marine current characterization
title_fullStr Intercomparison of surface velocimetry techniques for drone-based marine current characterization
title_full_unstemmed Intercomparison of surface velocimetry techniques for drone-based marine current characterization
title_sort Intercomparison of surface velocimetry techniques for drone-based marine current characterization
author_id_str_mv 568e6f260489dc8139afe77757553513
2305b5d9c024cf97a2feeb832af9228b
6fa19551092853928cde0e6d5fac48a1
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author_id_fullname_str_mv 568e6f260489dc8139afe77757553513_***_Iain Fairley
2305b5d9c024cf97a2feeb832af9228b_***_Nicholas King
6fa19551092853928cde0e6d5fac48a1_***_Ian Masters
3e76fcc2bb3cde4ddee2c8edfd2f0082_***_Dominic Reeve
author Iain Fairley
Nicholas King
Ian Masters
Dominic Reeve
author2 Iain Fairley
Nicholas King
Jason McIlvenny
Matthew Lewis
Simon Neill
Benjamin J. Williamson
Ian Masters
Dominic Reeve
format Journal article
container_title Estuarine, Coastal and Shelf Science
container_volume 299
publishDate 2024
institution Swansea University
issn 0272-7714
doi_str_mv 10.1016/j.ecss.2024.108682
publisher Elsevier BV
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Aerospace, Civil, Electrical, General and Mechanical Engineering - Mechanical Engineering
document_store_str 1
active_str 0
description Mapping tidal currents is important for a variety of coastal and marine applications. Deriving current maps from in-situ measurements is difficult due to spatio-temporal separation of measurement points. Therefore, low-cost remote sensing tools such as drone-based surface velocimetry are attractive. Previous application of particle image velocimetry to tidal current measurements demonstrated that accuracy depends on site and environmental conditions. This study compares surface velocimetry techniques across a range of these conditions. Various open-source tools and image pre-processing methods were applied to six sets of videos and validation data that cover a variety of site and weather conditions. When wind-driven ripples are present in imagery, it was found a short-wave celerity inversion performed best, with mean absolute percentage error (MAPE) of 5–6% compared to surface drifters. During lower wind speeds, current-advected surface features are visible and techniques which track these work best, of which the most appropriate technique depends on specifics of the collected imagery; MAPEs of 9–21% were obtained. This work has quantified accuracy and demonstrated that surface current maps can be obtained from drones under both high and low wind speeds and at a variety of sites. By following these suggested approaches, practitioners can use drones as a current mapping tool at coastal and offshore sites with confidence in the outputs.
published_date 2024-04-01T14:36:45Z
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