Cost-Effective Technologies to Study the Arctic Ocean Environment †

The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets are required to m...

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Published in:Sensors
Main Authors: Piermattei, Viviana, Madonia, Alice, Bonamano, Simone, Martellucci, Riccardo, Bruzzone, Gabriele, Ferretti, Roberta, Odetti, Angelo, Azzaro, Maurizio, Zappalà, Giuseppe, Marcelli, Marco
Format: Text
Language:English
Published: MDPI 2018
Subjects:
Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069410/
http://www.ncbi.nlm.nih.gov/pubmed/30011806
https://doi.org/10.3390/s18072257
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spelling ftpubmed:oai:pubmedcentral.nih.gov:6069410 2023-05-15T14:34:37+02:00 Cost-Effective Technologies to Study the Arctic Ocean Environment † Piermattei, Viviana Madonia, Alice Bonamano, Simone Martellucci, Riccardo Bruzzone, Gabriele Ferretti, Roberta Odetti, Angelo Azzaro, Maurizio Zappalà, Giuseppe Marcelli, Marco 2018-07-13 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069410/ http://www.ncbi.nlm.nih.gov/pubmed/30011806 https://doi.org/10.3390/s18072257 en eng MDPI http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069410/ http://www.ncbi.nlm.nih.gov/pubmed/30011806 http://dx.doi.org/10.3390/s18072257 © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). CC-BY Article Text 2018 ftpubmed https://doi.org/10.3390/s18072257 2018-08-12T00:21:45Z The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets are required to monitor the Arctic marine ecosystem and validate high-resolution satellite observations (e.g., Sentinel), which are necessary to feed climatic and biogeochemical forecasting models. However, the Global Observing System needs to complete its geographic coverage, particularly for the harsh, extreme environment of the Arctic Region. In this scenario, autonomous systems are proving to be valuable tools for increasing the resolution of existing data. To this end, a low-cost, miniaturized and flexible probe, ArLoC (Arctic Low-Cost probe), was designed, built and installed on an innovative unmanned marine vehicle, the PROTEUS (Portable RObotic TEchnology for Unmanned Surveys), during a preliminary scientific campaign in the Svalbard Archipelago within the UVASS project. This study outlines the instrumentation used and its design features, its preliminary integration on PROTEUS and its test results. Text Arctic Arctic Ocean Climate change Svalbard PubMed Central (PMC) Arctic Arctic Ocean Svalbard Svalbard Archipelago Sensors 18 7 2257
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Article
spellingShingle Article
Piermattei, Viviana
Madonia, Alice
Bonamano, Simone
Martellucci, Riccardo
Bruzzone, Gabriele
Ferretti, Roberta
Odetti, Angelo
Azzaro, Maurizio
Zappalà, Giuseppe
Marcelli, Marco
Cost-Effective Technologies to Study the Arctic Ocean Environment †
topic_facet Article
description The Arctic region is known to be severely affected by climate change, with evident alterations in both physical and biological processes. Monitoring the Arctic Ocean ecosystem is key to understanding the impact of natural and human-induced change on the environment. Large data sets are required to monitor the Arctic marine ecosystem and validate high-resolution satellite observations (e.g., Sentinel), which are necessary to feed climatic and biogeochemical forecasting models. However, the Global Observing System needs to complete its geographic coverage, particularly for the harsh, extreme environment of the Arctic Region. In this scenario, autonomous systems are proving to be valuable tools for increasing the resolution of existing data. To this end, a low-cost, miniaturized and flexible probe, ArLoC (Arctic Low-Cost probe), was designed, built and installed on an innovative unmanned marine vehicle, the PROTEUS (Portable RObotic TEchnology for Unmanned Surveys), during a preliminary scientific campaign in the Svalbard Archipelago within the UVASS project. This study outlines the instrumentation used and its design features, its preliminary integration on PROTEUS and its test results.
format Text
author Piermattei, Viviana
Madonia, Alice
Bonamano, Simone
Martellucci, Riccardo
Bruzzone, Gabriele
Ferretti, Roberta
Odetti, Angelo
Azzaro, Maurizio
Zappalà, Giuseppe
Marcelli, Marco
author_facet Piermattei, Viviana
Madonia, Alice
Bonamano, Simone
Martellucci, Riccardo
Bruzzone, Gabriele
Ferretti, Roberta
Odetti, Angelo
Azzaro, Maurizio
Zappalà, Giuseppe
Marcelli, Marco
author_sort Piermattei, Viviana
title Cost-Effective Technologies to Study the Arctic Ocean Environment †
title_short Cost-Effective Technologies to Study the Arctic Ocean Environment †
title_full Cost-Effective Technologies to Study the Arctic Ocean Environment †
title_fullStr Cost-Effective Technologies to Study the Arctic Ocean Environment †
title_full_unstemmed Cost-Effective Technologies to Study the Arctic Ocean Environment †
title_sort cost-effective technologies to study the arctic ocean environment †
publisher MDPI
publishDate 2018
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069410/
http://www.ncbi.nlm.nih.gov/pubmed/30011806
https://doi.org/10.3390/s18072257
geographic Arctic
Arctic Ocean
Svalbard
Svalbard Archipelago
geographic_facet Arctic
Arctic Ocean
Svalbard
Svalbard Archipelago
genre Arctic
Arctic Ocean
Climate change
Svalbard
genre_facet Arctic
Arctic Ocean
Climate change
Svalbard
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069410/
http://www.ncbi.nlm.nih.gov/pubmed/30011806
http://dx.doi.org/10.3390/s18072257
op_rights © 2018 by the authors.
Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
op_rightsnorm CC-BY
op_doi https://doi.org/10.3390/s18072257
container_title Sensors
container_volume 18
container_issue 7
container_start_page 2257
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