Highway Planning and Design's 2018 Manitoba Road Network.The 2018 Manitoba Road Network was created by Manitoba Infrastructure, Highway Engineering, Highway Planning and Design (HPD). The department’s linear referencing system (LRS) uses Control Sections as a linear referencing method (LRM). The LRM is the digital representation of the Highway Network in Manitoba. The features indicate highway number and highway identity. This data was corrected using 1:60,000 digital ortho aerial photography dated from 1991-1998. Linear features have been updated on a yearly basis using GPS data, CAD files and 50cm imagery from 2007-2014, and is considered accurate to two-to-seven metres. Please note that this feature layer primarily contains only the roads that Manitoba Infrastructure is responsible for, i.e. Provincial Trunk Highways, Provincial Roads and Access Roads. However, you may also see Earth Roads (under construction) or Other roads (such as those passing through national parks and are federal responsibility).Fields included (Alias (Field Name): Field description.) OBJECTID (OBJECTID): Sequential, unique whole numbers are automatically generated. SHAPE (SHAPE): A field to hold geometry information.  ID (ID): Unique Identifier generated by Oracle. Control Section ID (CS_ID): Non unique identifier linking segment to its respective control section. Road Number Signed (ROAD_NO_SIGNED): The road number. Note though, that in the case of co-routes, the lower highway number appears. This is a text field and differs from ROAD_NO only where there are city routes, for example 1A. Road Location (ROAD_LOCATION): Access Road locations. Road Description (DESCRIPTION): A text description of the start and end locations of each segment.  Control Section Key (CS_KEY): An information rich key containing Region (two digits), Road Number (three digits), Section number (three digits), the Road Type (one character), and direction of travel (one character). MI Region (REGION_NO): The Manitoba Infrastructure region the segment is in. Regions 1-5. Road Number (ROAD_NO): The road number. Note co-routes will have the lesser highway number.  Section Number (SECTION_NO): The control section's section number. Start Kilometre (KM) (START_KM): The beginning of the Control Section (always zero). End Kilometre (KM) (END_KM): The number of kilometres to the end of the Control Section. Length Kilometres (KM) (LENGTH_KM): End Kilometre minus the Start Kilometre.  Road Type (ROAD_TYPE): The road type, i.e. PTHs, PRs, and Access Roads (Earth roads under construction may also be included).  Road Direction (ROAD_DIRECTION): A = ahead direction on a divided highway (i.e. following the digitizing direction), B = Back direction on a divided Highway (i.e. against the digitizing direction, and U= an undivided highway. Road Identity (ROAD_IDENTITY): Road identity i.e. Provincial Road, Earth Road, Access Road and Other Road. National Highway Classification (NATIONAL_HIGHWAY_CLASS): The national highway classification standard. Start Date (START_DATE): The date the segment was created in the database.  Inventory Year (INVENTORY_YEAR): The year the road segment was opened to the public. 

Highway Planning and Design's 2017 Manitoba Road Network.The 2017 Manitoba Road Network was created by Manitoba Infrastructure --> Highway Engineering--> Highway Planning and Design. The department’s linear referencing system (LRS) uses Control Sections as a linear referencing method (LRM). The LRM is the digital representation of the Highway Network in Manitoba. The features indicate highway number and highway identity. This data was corrected using 1:60,000 digital ortho aerial photography dated from 1991-1998. Linear features have been updated on a yearly basis using GPS data, CAD files and 50cm imagery from 2007-2014, and is considered accurate to two-to-seven metres. Please note that this feature layer primarily contains only the roads that Manitoba Infrastructure is responsible for, i.e. Provincial Trunk Highways, Provincial Roads and Access Roads. However, you may also see Earth Roads (under construction) or Other roads (such as those passing through national parks and are federal responsibility). A newer version of this data is available: Manitoba Road Network 2018. Field List - FIELD NAME (Field Alias (i.e. display name)) in parenthesis)OBJECTID (OBJECTID) - Sequential, unique whole numbers are automatically generated.SHAPE (SHAPE) - A field to hold geometry information. ID (ID) - Unique Identifier generated by Oracle.CS_ID (Control Section ID) - Non unique identifier linking segment to its respective control section.ROAD_NO_SIGNED (Road Number Signed) - The road number. Note though, that in the case of co-routes, the lower highway number appears. This is a text field and differs from ROAD_NO only where there are city routes, for example 1A.ROAD_LOCATION (Road Location) - Access Road locations.DESCRIPTION (Road Description) - A text description of the start and end locations of each segment. CS_KEY (Control Section Key) - An information rich key containing Region (two digits), Road Number (three digits), Section number (three digits), the Road Type (one character), and direction of travel (one character).REGION_NO (MI Region) - The Manitoba Infrastructure region the segment is in. Regions 1-5.ROAD_NO (Road Number) - The road number. Note co-routes will have the lesser highway number. SECTION_NO (Section Number) - The control section's section number.START_KM (Start Kilometre (KM)) - The beginning of the Control Section (always zero).END_KM (End Kilometre (KM)) - The number of kilometres to the end of the Control Section.LENGTH_KM (Length Kilometres (KM)) - End Kilometre minus the Start Kilometre. ROAD_TYPE (Road Type) - The road type, i.e. PTHs, PRs, and Access Roads (Earth roads under construction may also be included). ROAD_DIRECTION (Road Direction) - A = ahead direction on a divided highway (i.e. following the digitizing direction), B = Back direction on a divided Highway (i.e. against the digitizing direction, and U= an undivided highway.ROAD_IDENTITY (Road Identity) - Road identity i.e. Provincial Road, Earth Road, Access Road and Other Road.NATIONAL_HIGHWAY_CLASS (National Highway Classification) - The national highway classification standard.START_DATE (Start Date) - The date the segment was created in the database. INVENTORY_YEAR (Inventory Year) - The year the road segment was opened to the public. SHAPE_Length (Segment Length) - An automatically generated length field based on geometry.

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.

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.

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.

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.

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.

The Registered Fur Management Area dataset is comprised of all the polygons that represent the Registered Fur Management Areas in Alberta. A Registered Fur Management Area (RFMA) is a parcel of public land, the boundary of which is described on the Registered Fur Management Licence. If a Registered Fur Management Area is described by reference to a line, that area includes all land within 0.5 mile on each side of that line. A Registered Fur Management Licence permits the licence holder to hunt and trap fur-bearing animals on the lands described on the licence.

The Labour Force Distribution (LFD) maps are derived from the CanEcumene 2.0 Geodatabase using custom tabulations of census-based labour force data. These LFD maps were calculated for each of the five major natural resource sectors in Canada: Forestry, Fisheries, Agriculture, Minerals, and Petroleum and Coal. The measure used is the labour force of each sector as a proportion of the goods-producing sectors in the economy. Labour force proportions were first calculated at the individual community level, and then interpolated on a regional level using GIS (see Eddy et. al. 2020 for more detail). In effect, these maps show the strong importance of Canada’s natural resource sectors in various regions of the country. The darker the tone in each map indicates a region’s higher degree of dependency on a given sector for their economic livelihood.

Natural gas onshore facilities used to receive, unload, load, store, gasify, liquefy, process and transport by ship, natural gas that is imported from a foreign country, exported to a foreign country, or interior commerce.Mapping Resources implemented as part of the North American Cooperation on Energy Information (NACEI) between the Department of Energy of the United States of America, the Department of Natural Resources of Canada, and the Ministry of Energy of the United Mexican States.The participating Agencies and Institutions shall not be held liable for improper or incorrect use of the data described and/or contained herein. These data and related graphics, if available, are not legal documents and are not intended to be used as such. The information contained in these data is dynamic and may change over time and may differ from other official information. The Agencies and Institutions participants give no warranty, expressed or implied, as to the accuracy, reliability, or completeness of these data.