Vessel Density Mapping of 2014 AIS Data in the Northwest Atlantic

Vessel Density Mapping of 2014 AIS Data in the Northwest Atlantic The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning. In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets. 2024-02-16 Fisheries and Oceans Canada tyler.veinot@dfo-mpo.gc.ca Nature and EnvironmentTransportAtlantic CanadaAutomatic Identification SystemVessel DensityShippingTransportationCargoFishingTankerTransportVesselsMarine safetyFishing ships Vessel Density Mapping of 2019 Automatic Identification System (AIS) Data in the Northwest AtlanticPDF https://waves-vagues.dfo-mpo.gc.ca/library-bibliotheque/41105163.pdf Vessel Density Mapping of 2014 Automatic Identification System (AIS) Data in the Northwest AtlanticGeoTIF https://api-proxy.edh.azure.cloud.dfo-mpo.gc.ca/catalogue/records/a3107ec8-b644-4d3a-b9db-7eafda8a54d3/attachments/NorthwestAtlantic_VesselDensity_2014_AIS.zip AIS Vessel density legendPNG https://api-proxy.edh.azure.cloud.dfo-mpo.gc.ca/catalogue/records/e60a7e32-5a67-45d6-900d-e6ab6b581a51/attachments/Legend.png Vessel Density Mapping of 2014 Automatic Identification System (AIS) Data in the Northwest AtlanticFGDB/GDB https://api-proxy.edh.azure.cloud.dfo-mpo.gc.ca/catalogue/records/a3107ec8-b644-4d3a-b9db-7eafda8a54d3/attachments/NorthwestAtlantic_VesselDensity_2014_AIS.gdb.zip Vessel Density Mapping of 2014 Automatic Identification System (AIS) Data in the Northwest AtlanticESRI REST https://gisp.dfo-mpo.gc.ca/arcgis/rest/services/FGP/Vessel_Density_Mapping_of_2014_AIS_Data_in_the_Northwest_Atlantic/MapServer Vessel Density Mapping of 2014 Automatic Identification System (AIS) Data in the Northwest AtlanticESRI REST https://gisp.dfo-mpo.gc.ca/arcgis/rest/services/FGP/Vessel_Density_Mapping_of_2014_AIS_Data_in_the_Northwest_Atlantic/MapServer

The Automatic Identification System (AIS) is a global, satellite-based and terrestrial-based ship tracking system that uses shipborne equipment to remotely track vessel identification and positional information and is typically required on vessels of 300 gross tonnage or more on an international voyage, of 500 gross tonnage or more not on an international voyage, and passenger ships of all sizes. AIS tracking technologies are primarily used in support of real-time maritime domain awareness and for maritime security and safety of life at sea. This report describes a geographic information system (GIS) analysis of 2019 AIS data to produce yearly and monthly vessel density maps of all vessel classes combined and yearly density maps of each vessel class. The year 2019 was selected to portray shipping densities in a pre-COVID 19 pandemic depiction of the maritime transport sector in the Northwest Atlantic. Vessel density map applications include use in spatial analysis and decision support for marine spatial planning.

In 2023 the process was applied to the years 2013 through to 2022 and were made available using the same processes that were applied to the original 2019 datasets.

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Electronic Mail Address: tyler.veinot@dfo-mpo.gc.ca

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