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Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna
Identification of benthic megafauna is commonly based on analysis of physical samples or imagery acquired by cameras mounted on underwater platforms. Physical collection of samples is difficult, particularly from the deep sea, and identification of taxonomic morphotypes from imagery depends on resol...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110793/ https://www.ncbi.nlm.nih.gov/pubmed/30150709 http://dx.doi.org/10.1038/s41598-018-31261-4 |
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author | Dumke, Ines Purser, Autun Marcon, Yann Nornes, Stein M. Johnsen, Geir Ludvigsen, Martin Søreide, Fredrik |
author_facet | Dumke, Ines Purser, Autun Marcon, Yann Nornes, Stein M. Johnsen, Geir Ludvigsen, Martin Søreide, Fredrik |
author_sort | Dumke, Ines |
collection | PubMed |
description | Identification of benthic megafauna is commonly based on analysis of physical samples or imagery acquired by cameras mounted on underwater platforms. Physical collection of samples is difficult, particularly from the deep sea, and identification of taxonomic morphotypes from imagery depends on resolution and investigator experience. Here, we show how an Underwater Hyperspectral Imager (UHI) can be used as an alternative in situ taxonomic tool for benthic megafauna. A UHI provides a much higher spectral resolution than standard RGB imagery, allowing marine organisms to be identified based on specific optical fingerprints. A set of reference spectra from identified organisms is established and supervised classification performed to identify benthic megafauna semi-autonomously. The UHI data provide an increased detection rate for small megafauna difficult to resolve in standard RGB imagery. In addition, seafloor anomalies with distinct spectral signatures are also detectable. In the region investigated, sediment anomalies (spectral reflectance minimum at ~675 nm) unclear in RGB imagery were indicative of chlorophyll a on the seafloor. Underwater hyperspectral imaging therefore has a great potential in seafloor habitat mapping and monitoring, with areas of application ranging from shallow coastal areas to the deep sea. |
format | Online Article Text |
id | pubmed-6110793 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61107932018-08-30 Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna Dumke, Ines Purser, Autun Marcon, Yann Nornes, Stein M. Johnsen, Geir Ludvigsen, Martin Søreide, Fredrik Sci Rep Article Identification of benthic megafauna is commonly based on analysis of physical samples or imagery acquired by cameras mounted on underwater platforms. Physical collection of samples is difficult, particularly from the deep sea, and identification of taxonomic morphotypes from imagery depends on resolution and investigator experience. Here, we show how an Underwater Hyperspectral Imager (UHI) can be used as an alternative in situ taxonomic tool for benthic megafauna. A UHI provides a much higher spectral resolution than standard RGB imagery, allowing marine organisms to be identified based on specific optical fingerprints. A set of reference spectra from identified organisms is established and supervised classification performed to identify benthic megafauna semi-autonomously. The UHI data provide an increased detection rate for small megafauna difficult to resolve in standard RGB imagery. In addition, seafloor anomalies with distinct spectral signatures are also detectable. In the region investigated, sediment anomalies (spectral reflectance minimum at ~675 nm) unclear in RGB imagery were indicative of chlorophyll a on the seafloor. Underwater hyperspectral imaging therefore has a great potential in seafloor habitat mapping and monitoring, with areas of application ranging from shallow coastal areas to the deep sea. Nature Publishing Group UK 2018-08-27 /pmc/articles/PMC6110793/ /pubmed/30150709 http://dx.doi.org/10.1038/s41598-018-31261-4 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Dumke, Ines Purser, Autun Marcon, Yann Nornes, Stein M. Johnsen, Geir Ludvigsen, Martin Søreide, Fredrik Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna |
title | Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna |
title_full | Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna |
title_fullStr | Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna |
title_full_unstemmed | Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna |
title_short | Underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna |
title_sort | underwater hyperspectral imaging as an in situ taxonomic tool for deep-sea megafauna |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6110793/ https://www.ncbi.nlm.nih.gov/pubmed/30150709 http://dx.doi.org/10.1038/s41598-018-31261-4 |
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