Underwater noise recognition of marine vessels passages: two case studies using hidden Markov models
Autor(a) principal: | |
---|---|
Data de Publicação: | 2020 |
Outros Autores: | , , , |
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. |
id |
RCAP_349fc680f6d795bf81a61edd927e81b4 |
---|---|
oai_identifier_str |
oai:repositorio.ul.pt:10451/47184 |
network_acronym_str |
RCAP |
network_name_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository_id_str |
7160 |
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) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
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 |
repository.mail.fl_str_mv |
|
_version_ |
1799134538246389760 |