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Multispectral multibeam backscatter response of heterogeneous rhodolith beds
Acoustic backscatter has been used as a tool to map the seafloor in greater detail and plays an increasingly important role in seafloor mapping to meet multiple ocean management needs. An outstanding challenge to the use of backscatter for seafloor mapping is the distinction between acoustically sim...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657437/ https://www.ncbi.nlm.nih.gov/pubmed/37980368 http://dx.doi.org/10.1038/s41598-023-46240-7 |
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author | Menandro, Pedro S. Misiuk, Benjamin Brown, Craig J. Bastos, Alex C. |
author_facet | Menandro, Pedro S. Misiuk, Benjamin Brown, Craig J. Bastos, Alex C. |
author_sort | Menandro, Pedro S. |
collection | PubMed |
description | Acoustic backscatter has been used as a tool to map the seafloor in greater detail and plays an increasingly important role in seafloor mapping to meet multiple ocean management needs. An outstanding challenge to the use of backscatter for seafloor mapping is the distinction between acoustically similar substrates, such as mixed sediments from rhodoliths. Rhodolith beds are a biogenic substrate that provides important ecological services, and are typically classified as a single categorical substrate type—though nodules coverage may be spatially variable. Recently, multispectral acoustic backscatter has demonstrated great potential to improve thematic seafloor mapping compared to single-frequency systems. This work employs multispectral multibeam backscatter and underwater imagery to characterize and map rhodolith beds in the Costa das Algas Marine Protected Area (Brazil). A support vector machine classifier was used to classify multifrequency backscatter mosaics according to rhodolith classes identified from underwater imagery. Results suggest that multispectral backscatter is effective both in providing information for mapping different proportions of rhodolith coverage and in predicting the presence or absence of these nodules. The backscatter of the lowest frequency was the most useful for distinguishing variable proportions of rhodolith coverage, and the two higher frequencies were better predictors of presence and absence. |
format | Online Article Text |
id | pubmed-10657437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106574372023-11-18 Multispectral multibeam backscatter response of heterogeneous rhodolith beds Menandro, Pedro S. Misiuk, Benjamin Brown, Craig J. Bastos, Alex C. Sci Rep Article Acoustic backscatter has been used as a tool to map the seafloor in greater detail and plays an increasingly important role in seafloor mapping to meet multiple ocean management needs. An outstanding challenge to the use of backscatter for seafloor mapping is the distinction between acoustically similar substrates, such as mixed sediments from rhodoliths. Rhodolith beds are a biogenic substrate that provides important ecological services, and are typically classified as a single categorical substrate type—though nodules coverage may be spatially variable. Recently, multispectral acoustic backscatter has demonstrated great potential to improve thematic seafloor mapping compared to single-frequency systems. This work employs multispectral multibeam backscatter and underwater imagery to characterize and map rhodolith beds in the Costa das Algas Marine Protected Area (Brazil). A support vector machine classifier was used to classify multifrequency backscatter mosaics according to rhodolith classes identified from underwater imagery. Results suggest that multispectral backscatter is effective both in providing information for mapping different proportions of rhodolith coverage and in predicting the presence or absence of these nodules. The backscatter of the lowest frequency was the most useful for distinguishing variable proportions of rhodolith coverage, and the two higher frequencies were better predictors of presence and absence. Nature Publishing Group UK 2023-11-18 /pmc/articles/PMC10657437/ /pubmed/37980368 http://dx.doi.org/10.1038/s41598-023-46240-7 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Menandro, Pedro S. Misiuk, Benjamin Brown, Craig J. Bastos, Alex C. Multispectral multibeam backscatter response of heterogeneous rhodolith beds |
title | Multispectral multibeam backscatter response of heterogeneous rhodolith beds |
title_full | Multispectral multibeam backscatter response of heterogeneous rhodolith beds |
title_fullStr | Multispectral multibeam backscatter response of heterogeneous rhodolith beds |
title_full_unstemmed | Multispectral multibeam backscatter response of heterogeneous rhodolith beds |
title_short | Multispectral multibeam backscatter response of heterogeneous rhodolith beds |
title_sort | multispectral multibeam backscatter response of heterogeneous rhodolith beds |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10657437/ https://www.ncbi.nlm.nih.gov/pubmed/37980368 http://dx.doi.org/10.1038/s41598-023-46240-7 |
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