Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models

Detalhes bibliográficos
Autor(a) principal: Vieira, Manuel
Data de Publicação: 2020
Outros Autores: Amorim, M Clara P, Sundelöf, Andreas, Prista, Nuno, Fonseca, Paulo
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10451/47184
Resumo: Passive acoustic monitoring (PAM) is emerging as a cost-effective non-intrusive method to monitor the health and biodiversity of marine habitats, including the impacts of anthropogenic noise on marine organisms. When long PAM recordings are to be analysed, automatic recognition and identification processes are invaluable tools to extract the relevant information. We propose a pattern recognition methodology based on hidden Markov models (HMMs) for the detection and recognition of acoustic signals from marine vessels passages and test it in two different regions, the Tagus estuary in Portugal and the Öresund strait in the Baltic Sea. Results show that the combination of HMMs with PAM provides a powerful tool to monitor the presence of marine vessels and discriminate different vessels such as small boats, ferries, and large ships. Improvements to enhance the capability to discriminate different types of small recreational boats are discussed.
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spelling Underwater noise recognition of marine vessels passages: two case studies using hidden Markov modelsPassive acoustic monitoring (PAM) is emerging as a cost-effective non-intrusive method to monitor the health and biodiversity of marine habitats, including the impacts of anthropogenic noise on marine organisms. When long PAM recordings are to be analysed, automatic recognition and identification processes are invaluable tools to extract the relevant information. We propose a pattern recognition methodology based on hidden Markov models (HMMs) for the detection and recognition of acoustic signals from marine vessels passages and test it in two different regions, the Tagus estuary in Portugal and the Öresund strait in the Baltic Sea. Results show that the combination of HMMs with PAM provides a powerful tool to monitor the presence of marine vessels and discriminate different vessels such as small boats, ferries, and large ships. Improvements to enhance the capability to discriminate different types of small recreational boats are discussed.Oxford University PressRepositório da Universidade de LisboaVieira, ManuelAmorim, M Clara PSundelöf, AndreasPrista, NunoFonseca, Paulo2021-11-01T01:30:21Z2020-112020-11-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/47184engVieira, M., Amorim, M. C. P., Sundelo¨f, A., Prista, N., and Fonseca, P. J. 2020. Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models. – ICES Journal of Marine Science, 77: 2157-2170. doi:10.1093/icesjms/fsz194.10.1093/icesjms/fsz194info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-08T16:49:50Zoai:repositorio.ul.pt:10451/47184Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:59:14.082014Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
title Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
spellingShingle Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
Vieira, Manuel
title_short Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
title_full Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
title_fullStr Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
title_full_unstemmed Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
title_sort Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
author Vieira, Manuel
author_facet Vieira, Manuel
Amorim, M Clara P
Sundelöf, Andreas
Prista, Nuno
Fonseca, Paulo
author_role author
author2 Amorim, M Clara P
Sundelöf, Andreas
Prista, Nuno
Fonseca, Paulo
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Vieira, Manuel
Amorim, M Clara P
Sundelöf, Andreas
Prista, Nuno
Fonseca, Paulo
description Passive acoustic monitoring (PAM) is emerging as a cost-effective non-intrusive method to monitor the health and biodiversity of marine habitats, including the impacts of anthropogenic noise on marine organisms. When long PAM recordings are to be analysed, automatic recognition and identification processes are invaluable tools to extract the relevant information. We propose a pattern recognition methodology based on hidden Markov models (HMMs) for the detection and recognition of acoustic signals from marine vessels passages and test it in two different regions, the Tagus estuary in Portugal and the Öresund strait in the Baltic Sea. Results show that the combination of HMMs with PAM provides a powerful tool to monitor the presence of marine vessels and discriminate different vessels such as small boats, ferries, and large ships. Improvements to enhance the capability to discriminate different types of small recreational boats are discussed.
publishDate 2020
dc.date.none.fl_str_mv 2020-11
2020-11-01T00:00:00Z
2021-11-01T01:30:21Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10451/47184
url http://hdl.handle.net/10451/47184
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Vieira, M., Amorim, M. C. P., Sundelo¨f, A., Prista, N., and Fonseca, P. J. 2020. Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models. – ICES Journal of Marine Science, 77: 2157-2170. doi:10.1093/icesjms/fsz194.
10.1093/icesjms/fsz194
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Oxford University Press
publisher.none.fl_str_mv Oxford University Press
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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instacron:RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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