bc8a006f-0f17-407c-bd44-31effc9a7fb0 Sextant Ifremer ZI Pointe du Diable Plouzane Brittany 29280 France sextant@ifremer.fr https://sextant.ifremer.fr/eng pointOfContact 2025-05-15T23:56:08.439275Z ISO 19115-3 - SEXTANT 1.0 EPSG:4326 2021 Static Dataset: Apparent Fishing Effort 2021-01-01 publication 2016-01-01 creation bc8a006f-0f17-407c-bd44-31effc9a7fb0 Global Fishing Watch is working across the globe to provide governments and authorities with actionable reports and capacity building to help strengthen fisheries monitoring and compliance. Our global team of experts produce analyses to inform monitoring, control and surveillance of fisheries in five key areas: - Illegal, unreported and unregulated fishing - Transshipment - Port controls - Marine protected areas - Operation support Collaboration and information sharing are integral to achieving well-managed fisheries. By working with stakeholders and making analyses available to national, regional and intergovernmental partners, Global Fishing Watch is enabling fisheries agencies to make more informed and cost-efficient decisions. Topics: - Commercial fishing, Global Fishing Watch is harnessing innovative technology to turn transparent data into actionable information and drive tangible change in the way that fisheries are governed. - Transshipment, Through publicly sharing map visualisations and creating data and analysis tools, we seek to inform management and policy efforts and provide a more complete picture of transshipment at sea. - Marine protected areas, Global Fishing Watch is harnessing the data and technology revolution to support the effective design, management and monitoring of marine protected areas. Global Fishing Watch Research and data inquiries GFW research@globalfishingwatch.org pointOfContact GFW Support support@globalfishingwatch.org pointOfContact https://sextant.ifremer.fr/geonetwork/srv/api/records/bc8a006f-0f17-407c-bd44-31effc9a7fb0/attachments/11_GFW.jfif /Human Activities/Industrial Fishing Thèmes Sextant 2023-03-16 publication geonetwork.thesaurus.local.theme.sextant-theme Production and industrial facilities GEMET - INSPIRE themes, version 1.0 2018-07-27T14:39:48 publication geonetwork.thesaurus.external.theme.httpinspireeceuropaeutheme-theme South Brazilian Shelf Canary Current system South Mid-Atlantic Ridge Atlantic Ocean Mission Atlantic - Case Studies 2023-03-16 publication geonetwork.thesaurus.local.theme.mission-atlantic-case-studies WP4 Benthic Mapping WP6 Dynamics of ecosystem state and resources WP3 Pelagic Mapping WP5 Assessing state, drivers and tipping points Mission Atlantic - Work Package 2023-03-16 publication geonetwork.thesaurus.local.theme.mission-atlantic-work-package Socio-economic data Mission Atlantic - Data type (DMP) 2023-03-16 publication geonetwork.thesaurus.local.theme.mission-atlantic-data-type /Human activities/Transport /Human activities/Fisheries Mission Atlantic - BODC Parameters 2023-03-16 publication geonetwork.thesaurus.local.theme.mission-atlantic-bodc-parameters Data Program and project Mission Atlantic - Resources 2023-03-16 publication geonetwork.thesaurus.local.theme.mission-atlantic-resources /International and global data portals Ocean Hackathon - City and challenge 2023-11-10 publication geonetwork.thesaurus.local.place.oh_ville CC-BY-NC (Creative Commons - Attribution, No commercial usage) grid utf8 oceans -180.00 180.00 -90.00 90.00 CSV https://globalfishingwatch.org/dataset-and-code-fishing-effort/ WWW:LINK Datasets and Code: Apparent Fishing Effort https://gateway.api.globalfishingwatch.org/auth?client=gfw&callback=https://globalfishingwatch.org/data-download/datasets/public-fishing-effort WWW:LINK GFW Portal AIS is a GPS-like device that large ships use to broadcast their position in order to avoid collisions. Each year, more than 400,000 AIS devices broadcast vessel location along with other information on vessel identity, course and speed. Ground stations and satellites pick up this information, meaning a ship’s movements can be followed even in the most remote parts of the ocean. Every day we receive raw AIS data from our partner at Spire. These data are first run through a series of our algorithms designed to filter out corrupt or incomplete records and assign additional information to each AIS message, such as the distance from shore, depth and time since the vessel’s previous AIS position. At this point, the AIS data is ready to be used by our machine learning models.