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A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats

We developed a novel integrated technology for diver-operated surveying of shallow marine ecosystems. The HyperDiver system captures rich multifaceted data in each transect: hyperspectral and color imagery, topographic profiles, incident irradiance and water chemistry at a rate of 15–30 m(2) per min...

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Autores principales: Chennu, Arjun, Färber, Paul, De’ath, Glenn, de Beer, Dirk, Fabricius, Katharina E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541065/
https://www.ncbi.nlm.nih.gov/pubmed/28769060
http://dx.doi.org/10.1038/s41598-017-07337-y
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author Chennu, Arjun
Färber, Paul
De’ath, Glenn
de Beer, Dirk
Fabricius, Katharina E.
author_facet Chennu, Arjun
Färber, Paul
De’ath, Glenn
de Beer, Dirk
Fabricius, Katharina E.
author_sort Chennu, Arjun
collection PubMed
description We developed a novel integrated technology for diver-operated surveying of shallow marine ecosystems. The HyperDiver system captures rich multifaceted data in each transect: hyperspectral and color imagery, topographic profiles, incident irradiance and water chemistry at a rate of 15–30 m(2) per minute. From surveys in a coral reef following standard diver protocols, we show how the rich optical detail can be leveraged to generate photopigment abundance and benthic composition maps. We applied machine learning techniques, with a minor annotation effort (<2% of pixels), to automatically generate cm-scale benthic habitat maps of high taxonomic resolution and accuracy (93–97%). The ability to efficiently map benthic composition, photopigment densities and rugosity at reef scales is a compelling contribution to modernize reef monitoring. Seafloor-level hyperspectral images can be used for automated mapping, avoiding operator bias in the analysis and deliver the degree of detail necessary for standardized environmental monitoring. The technique can deliver fast, objective and economic reef survey results, making it a valuable tool for coastal managers and reef ecologists. Underwater hyperspectral surveying shares the vantage point of the high spatial and taxonomic resolution restricted to field surveys, with analytical techniques of remote sensing and provides targeted validation for aerial monitoring.
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spelling pubmed-55410652017-08-07 A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats Chennu, Arjun Färber, Paul De’ath, Glenn de Beer, Dirk Fabricius, Katharina E. Sci Rep Article We developed a novel integrated technology for diver-operated surveying of shallow marine ecosystems. The HyperDiver system captures rich multifaceted data in each transect: hyperspectral and color imagery, topographic profiles, incident irradiance and water chemistry at a rate of 15–30 m(2) per minute. From surveys in a coral reef following standard diver protocols, we show how the rich optical detail can be leveraged to generate photopigment abundance and benthic composition maps. We applied machine learning techniques, with a minor annotation effort (<2% of pixels), to automatically generate cm-scale benthic habitat maps of high taxonomic resolution and accuracy (93–97%). The ability to efficiently map benthic composition, photopigment densities and rugosity at reef scales is a compelling contribution to modernize reef monitoring. Seafloor-level hyperspectral images can be used for automated mapping, avoiding operator bias in the analysis and deliver the degree of detail necessary for standardized environmental monitoring. The technique can deliver fast, objective and economic reef survey results, making it a valuable tool for coastal managers and reef ecologists. Underwater hyperspectral surveying shares the vantage point of the high spatial and taxonomic resolution restricted to field surveys, with analytical techniques of remote sensing and provides targeted validation for aerial monitoring. Nature Publishing Group UK 2017-08-02 /pmc/articles/PMC5541065/ /pubmed/28769060 http://dx.doi.org/10.1038/s41598-017-07337-y Text en © The Author(s) 2017 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
Chennu, Arjun
Färber, Paul
De’ath, Glenn
de Beer, Dirk
Fabricius, Katharina E.
A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats
title A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats
title_full A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats
title_fullStr A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats
title_full_unstemmed A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats
title_short A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats
title_sort diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5541065/
https://www.ncbi.nlm.nih.gov/pubmed/28769060
http://dx.doi.org/10.1038/s41598-017-07337-y
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