These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

These structure, isopach and zero edge files are part of a series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project.The series of stratigraphic framework maps for the Saskatchewan Phanerozoic Fluids and Petroleum Systems (SPFPS) project have been produced using 2 km equi-spaced modified grids generated from Golden Software’s Surfer 9 kriging algorithm. The dataset used to produce each of the maps in this series was created using data from several projects completed by the Ministry (Christopher, 2003; Saskatchewan Industry and Resources et al., 2004; Kreis et al., 2004; Marsh and Heinemann, 2006; Saskatchewan Ministry of Energy and Resources et al., 2007; Heinemann and Marsh, 2009); these data were validated and edited as required to facilitate correlations between the various regional projects. In addition, to minimize edge effects during contouring, the senior author also generated stratigraphic data from wells in adjacent jurisdictions.

This dataset presents the first comprehensive, high-resolution (10-meter) wetland inventory map covering the entire 32.2 million square kilometers of the Pan-Arctic region, of which 14 million square kilometers (43%) is terrestrial and 18.4 million square kilometers (57%) is marine. Generated through advanced Earth Observation and machine learning techniques, the map was produced using multi-year (2020–2022), multi-source satellite imagery—including Sentinel‑1, Sentinel‑2, and ALOS PALSAR‑2—as well as various environmental features such as elevation. Over 1,000 wetland polygons were analyzed using an object-based random forest classification workflow on the Google Earth Engine cloud platform, achieving an average overall classification accuracy of 89%.The mapping extent was defined according to the Arctic Council’s Conservation of Arctic Flora and Fauna (CAFF) boundary, resulting in the identification of 2,947,618 km² of wetlands, representing 20% of the land area within the Pan-Arctic region. This dataset establishes a consistent and authoritative baseline for pan-Arctic wetlands, leveraging the latest advances in Earth Observation, machine learning, and cloud computing. The Canadian Wetland Classification System was used and includes the major wetland classes: bog, fen, marsh, swamp, and water.The overall wetlands coverage by country within the CAFF boundary was: Canada (27%), United States of America (i.e., Alaska 39%), Finland (31%), Iceland (8%), Norway (17%), Sweden (26%), Kingdom of Denmark (i.e., Greenland 1%), and the Russian Federation (21%).​Development of this product was undertaken by Natural Resource Canada's Canada Centre for Mapping and Earth Observation and the Canadian Geospatial Data Infrastructure Division in collaboration with the Arctic Council’s CAFF biodiversity group, CAFF Wetland Experts Group, national organisations mandated to monitor wetlands, and Arctic National Mapping Agencies, and Canadian company C-CORE, integrating ground truth data collected from Alaska, Finland, Sweden, and the Kingdom of Denmark through partner agencies and digital image interpretation. More than 60,000 images (2020-2022), primarily covering summer periods, were processed to ensure robust results.This dataset provides essential baseline information for Earth Observation monitoring of climate change impacts and supports critical environmental surveillance for Arctic and remote northern communities.

The DND Air Weapons Range dataset is comprised of all the polygons that represent the Air Weapons Range established by the Department of National Defence, Government of Canada, within the Province of Alberta. Air Weapons Range is the area used as a practice and firing range with restricted access provisions and which is owned and operated by the Department of National Defence, Government of Canada.

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 National Interest Land Mass (NILM) comprises a set of lands (mainly-NCC owned) considered essential to the functioning and experience of Canada's Capital. The NILM is the dominant tool guiding federal land management and ownership in support of Capital functions. The NILM was approved by Treasury Board in 1998 and the first update was approved in 2001. The 2020 NILM Update is the second update.

A Stock Range is an administrative area established to coincide with local livestock association areas. Generally, stock ranges are made up of one or more range units. Stock ranges are found in select areas of the province where applicable; not all areas of the province contain stock ranges

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.

The Gulf of St. Lawrence At-Sea Observer Program is part of the Fisheries Monitoring Policy of the Department of Fisheries and Oceans Canada (DFO) (https://www.dfo-mpo.gc.ca/reports-rapports/regs/sff-cpd/fishery-monitoring-surveillance-des-peches-eng.htm#toc13). Its purpose is to ensure accurate verification of fishing activities at sea by an independent third party, and to provide DFO with scientific data on catches. The fishing industry and DFO depend on the proper communication of this information for fisheries management, monitoring and scientific research activities.Biological data on fish and marine invertebrates collected by the At-Sea Observer Program is one of the sources of information used by DFO to assess the status of these resources. Biological data protocols are the subject of an annual consultation with the biologists responsible for assessing each of the exploited stocks.This dataset contains the sum of weight data for species caught, by NAFO (Northwest Atlantic Fisheries Organization) sub-division and by year from 1999-2023, from commercial species directed fisheries for stock assessments in the Quebec region. It also includes length frequencies for species caught when required by protocol.To preserve the confidentiality of the fishing industry, data are only presented when fishing activity has been observed on a minimum of 5 vessels in a given NAFO area. The data presented are raw and should be interpreted with caution. They may contain errors such as spatial coordinates, landing weights or inaccurate or unreliable species identifications. A brief review of the taxonomy was carried out by DFO taxonomist cited as collaborator. His comments can be found in the “REMARK_IDENT” column preceded by the code “Claude_Nozere”.