A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden
The Svalbardsis one of the most intensively studied marine regions in the Artic; here the composition and distribution of marine assemblages are changing under the effect of global change, and marine communities are monitored in order to understand the long-term effects on marine biodiversity. In th...
Published in: | Environmental Modelling & Software |
---|---|
Main Authors: | , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | http://hdl.handle.net/10447/549870 https://doi.org/10.1016/j.envsoft.2022.105401 |
id |
ftunivpalermo:oai:iris.unipa.it:10447/549870 |
---|---|
record_format |
openpolar |
spelling |
ftunivpalermo:oai:iris.unipa.it:10447/549870 2024-02-11T10:05:35+01:00 A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden Giacalone, Giovanni Barra, Marco Bonanno, Angelo Basilone, Gualtiero Fontana, Ignazio Calabrò, Monica Genovese, Simona Ferreri, Rosalia Buscaino, Giuseppa Mazzola, Salvatore Noormets, Riko Nuth, Christopher Lo Bosco, Giosuè Rizzo, Riccardo Aronica, Salvatore Giacalone, Giovanni Barra, Marco Bonanno, Angelo Basilone, Gualtiero Fontana, Ignazio Calabrò, Monica Genovese, Simona Ferreri, Rosalia Buscaino, Giuseppa Mazzola, Salvatore Noormets, Riko Nuth, Christopher Lo Bosco, Giosuè Rizzo, Riccardo Aronica, Salvatore 2022-06 http://hdl.handle.net/10447/549870 https://doi.org/10.1016/j.envsoft.2022.105401 eng eng info:eu-repo/semantics/altIdentifier/wos/WOS:000800212300005 volume:152 firstpage:1 lastpage:10 numberofpages:10 journal:ENVIRONMENTAL MODELLING & SOFTWARE http://hdl.handle.net/10447/549870 doi:10.1016/j.envsoft.2022.105401 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85129021633 info:eu-repo/semantics/openAccess Fish school Multi-beam K-means 3D pattern Cluster Settore INF/01 - Informatica Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni info:eu-repo/semantics/article 2022 ftunivpalermo https://doi.org/10.1016/j.envsoft.2022.105401 2024-01-23T23:32:43Z The Svalbardsis one of the most intensively studied marine regions in the Artic; here the composition and distribution of marine assemblages are changing under the effect of global change, and marine communities are monitored in order to understand the long-term effects on marine biodiversity. In the present work, acoustic data collected in the Kongsfjorden using multi-beam technology was analyzed to develop a methodology for identifying and classifying 3D acoustic patterns related to fish aggregations. In particular, morphological, energetic and depth features were taken into account to develop a multi-variate classification procedure allowing to discriminate fish species. The results obtained from clustering suggest that from a mathematical point of view three distinct groups could be identified. The proposed approach, that allows to discriminate the acoustic patterns identified in the water column, seems promising for improving the monitoring programs of the marine resources, also in view of the ongoing climate changes. Article in Journal/Newspaper Kongsfjord* Kongsfjorden IRIS Università degli Studi di Palermo Environmental Modelling & Software 152 105401 |
institution |
Open Polar |
collection |
IRIS Università degli Studi di Palermo |
op_collection_id |
ftunivpalermo |
language |
English |
topic |
Fish school Multi-beam K-means 3D pattern Cluster Settore INF/01 - Informatica Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni |
spellingShingle |
Fish school Multi-beam K-means 3D pattern Cluster Settore INF/01 - Informatica Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni Giacalone, Giovanni Barra, Marco Bonanno, Angelo Basilone, Gualtiero Fontana, Ignazio Calabrò, Monica Genovese, Simona Ferreri, Rosalia Buscaino, Giuseppa Mazzola, Salvatore Noormets, Riko Nuth, Christopher Lo Bosco, Giosuè Rizzo, Riccardo Aronica, Salvatore A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden |
topic_facet |
Fish school Multi-beam K-means 3D pattern Cluster Settore INF/01 - Informatica Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni |
description |
The Svalbardsis one of the most intensively studied marine regions in the Artic; here the composition and distribution of marine assemblages are changing under the effect of global change, and marine communities are monitored in order to understand the long-term effects on marine biodiversity. In the present work, acoustic data collected in the Kongsfjorden using multi-beam technology was analyzed to develop a methodology for identifying and classifying 3D acoustic patterns related to fish aggregations. In particular, morphological, energetic and depth features were taken into account to develop a multi-variate classification procedure allowing to discriminate fish species. The results obtained from clustering suggest that from a mathematical point of view three distinct groups could be identified. The proposed approach, that allows to discriminate the acoustic patterns identified in the water column, seems promising for improving the monitoring programs of the marine resources, also in view of the ongoing climate changes. |
author2 |
Giacalone, Giovanni Barra, Marco Bonanno, Angelo Basilone, Gualtiero Fontana, Ignazio Calabrò, Monica Genovese, Simona Ferreri, Rosalia Buscaino, Giuseppa Mazzola, Salvatore Noormets, Riko Nuth, Christopher Lo Bosco, Giosuè Rizzo, Riccardo Aronica, Salvatore |
format |
Article in Journal/Newspaper |
author |
Giacalone, Giovanni Barra, Marco Bonanno, Angelo Basilone, Gualtiero Fontana, Ignazio Calabrò, Monica Genovese, Simona Ferreri, Rosalia Buscaino, Giuseppa Mazzola, Salvatore Noormets, Riko Nuth, Christopher Lo Bosco, Giosuè Rizzo, Riccardo Aronica, Salvatore |
author_facet |
Giacalone, Giovanni Barra, Marco Bonanno, Angelo Basilone, Gualtiero Fontana, Ignazio Calabrò, Monica Genovese, Simona Ferreri, Rosalia Buscaino, Giuseppa Mazzola, Salvatore Noormets, Riko Nuth, Christopher Lo Bosco, Giosuè Rizzo, Riccardo Aronica, Salvatore |
author_sort |
Giacalone, Giovanni |
title |
A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden |
title_short |
A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden |
title_full |
A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden |
title_fullStr |
A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden |
title_full_unstemmed |
A pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in Kongsfjorden |
title_sort |
pattern recognition approach to identify biological clusters acquired by acoustic multi-beam in kongsfjorden |
publishDate |
2022 |
url |
http://hdl.handle.net/10447/549870 https://doi.org/10.1016/j.envsoft.2022.105401 |
genre |
Kongsfjord* Kongsfjorden |
genre_facet |
Kongsfjord* Kongsfjorden |
op_relation |
info:eu-repo/semantics/altIdentifier/wos/WOS:000800212300005 volume:152 firstpage:1 lastpage:10 numberofpages:10 journal:ENVIRONMENTAL MODELLING & SOFTWARE http://hdl.handle.net/10447/549870 doi:10.1016/j.envsoft.2022.105401 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85129021633 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.1016/j.envsoft.2022.105401 |
container_title |
Environmental Modelling & Software |
container_volume |
152 |
container_start_page |
105401 |
_version_ |
1790602660596940800 |