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Revealing the global longline fleet with satellite radar
Because many vessels use the Automatic Identification System (AIS) to broadcast GPS positions, recent advances in satellite technology have enabled us to map global fishing activity. Understanding of human activity at sea, however, is limited because an unknown number of vessels do not broadcast AIS...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9722684/ https://www.ncbi.nlm.nih.gov/pubmed/36470894 http://dx.doi.org/10.1038/s41598-022-23688-7 |
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author | Kroodsma, David A. Hochberg, Timothy Davis, Pete B. Paolo, Fernando S. Joo, Rocío Wong, Brian A. |
author_facet | Kroodsma, David A. Hochberg, Timothy Davis, Pete B. Paolo, Fernando S. Joo, Rocío Wong, Brian A. |
author_sort | Kroodsma, David A. |
collection | PubMed |
description | Because many vessels use the Automatic Identification System (AIS) to broadcast GPS positions, recent advances in satellite technology have enabled us to map global fishing activity. Understanding of human activity at sea, however, is limited because an unknown number of vessels do not broadcast AIS. Those vessels can be detected by satellite-based Synthetic Aperture Radar (SAR) imagery, but this technology has not yet been deployed at scale to estimate the size of fleets in the open ocean. Here we combine SAR and AIS for large-scale open ocean monitoring, developing methods to match vessels with AIS to vessels detected with SAR and estimate the number of non-broadcasting vessels. We reveal that, between September 2019 and January 2020, non-broadcasting vessels accounted for about 35% of the longline activity north of Madagascar and 10% of activity near French Polynesia and Kiribati’s Line Islands. We further demonstrate that this method could monitor half of the global longline activity with about 70 SAR images per week, allowing us to track human activity across the oceans. |
format | Online Article Text |
id | pubmed-9722684 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97226842022-12-07 Revealing the global longline fleet with satellite radar Kroodsma, David A. Hochberg, Timothy Davis, Pete B. Paolo, Fernando S. Joo, Rocío Wong, Brian A. Sci Rep Article Because many vessels use the Automatic Identification System (AIS) to broadcast GPS positions, recent advances in satellite technology have enabled us to map global fishing activity. Understanding of human activity at sea, however, is limited because an unknown number of vessels do not broadcast AIS. Those vessels can be detected by satellite-based Synthetic Aperture Radar (SAR) imagery, but this technology has not yet been deployed at scale to estimate the size of fleets in the open ocean. Here we combine SAR and AIS for large-scale open ocean monitoring, developing methods to match vessels with AIS to vessels detected with SAR and estimate the number of non-broadcasting vessels. We reveal that, between September 2019 and January 2020, non-broadcasting vessels accounted for about 35% of the longline activity north of Madagascar and 10% of activity near French Polynesia and Kiribati’s Line Islands. We further demonstrate that this method could monitor half of the global longline activity with about 70 SAR images per week, allowing us to track human activity across the oceans. Nature Publishing Group UK 2022-12-05 /pmc/articles/PMC9722684/ /pubmed/36470894 http://dx.doi.org/10.1038/s41598-022-23688-7 Text en © The Author(s) 2022 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 Kroodsma, David A. Hochberg, Timothy Davis, Pete B. Paolo, Fernando S. Joo, Rocío Wong, Brian A. Revealing the global longline fleet with satellite radar |
title | Revealing the global longline fleet with satellite radar |
title_full | Revealing the global longline fleet with satellite radar |
title_fullStr | Revealing the global longline fleet with satellite radar |
title_full_unstemmed | Revealing the global longline fleet with satellite radar |
title_short | Revealing the global longline fleet with satellite radar |
title_sort | revealing the global longline fleet with satellite radar |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9722684/ https://www.ncbi.nlm.nih.gov/pubmed/36470894 http://dx.doi.org/10.1038/s41598-022-23688-7 |
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