This data shows spatial density of forage crops in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which forage crops are more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated for that location. Higher spatial density values represent higher likelihood to have forage crops based on analysis of the 2009 to 2021 AAFC annual crop inventory data.

Small area data (SAD) on field crops show seeded and harvested area, yield and production estimates for most principal field crops and some special crops in Canada. Most SAD geographies correspond exactly with the Census Agriculture Region (CAR) limits, excepts for some regions of Quebec (where small areas are defined by provincial administrative boundaries), Saskatchewan (where small areas coincide with census divisions boundaries as of 2017) and British Columbia.For exact correspondence between Census Agricultural Regions (CAR) and Small Area Data (SAD) Regions, see the following link:https://www.statcan.gc.ca/eng/statistical-programs/document/3401_D2_V2These regions are associated with Statistics Canada estimates on principal field crops available in the following table: https://www150.statcan.gc.ca/t1/tbl1/en/tv.action?pid=3210000201

These files from Statistics Canada present Census of Agriculture data allocated by standard census geographic polygons: Provinces and Territories (PR), Census Agricultural Regions (CAR), Census Divisions (CD) and Census Consolidated Subdivisions (CCS). Five datasets are provided:1. Agricultural operation characteristics: includes information on farm type, operating arrangements, paid agricultural work and financial characteristics of the agricultural operation.2. Land tenure and management practices: includes information on land use, land tenure, agricultural practices, land inputs, technologies used on the operation and the renewable energy production on the operation.3. Crops: includes information on hay and field crops, vegetables (excluding greenhouse vegetables), fruits, berries, nuts, greenhouse productions and other crops.4. Livestock, poultry and bees: includes information on livestock, poultry and bees.5. Characteristics of farm operators: includes information on age, sex and the hours of works of farm operators.Note: For all the datasets, confidential values have been assigned a value of -1.Correction notice: On January 18, 2023, selected estimates have been corrected for selected variables in the following 2021 Census of Agriculture domains: Direct sales of agricultural products to consumers (Agricultural operations category), Succession plan for the agricultural operation (Agricultural operators category), and Renewable energy production (Use, tenure and practices category).

In 2017, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Sentinel-2, Gaofen-1) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the BC Ministry of Agriculture, & the Ontario Ministry of Agriculture, Food and Rural Affairs; and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, Guelph, and Summerland

In 2016, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery to for all of Canada, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Sentinel-2, Gaofen-1) and radar (RADARSAT-2) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the BC Ministry of Agriculture, & the Ontario Ministry of Agriculture, Food and Rural Affairs; and data collection supported by our regional AAFC Research and Development Centres in St. John’s, Kentville, Charlottetown, Fredericton, Guelph, and Summerland.

In 2024, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) repeated the process of generating annual crop inventory digital maps using satellite imagery for all Canadian provinces and the Yukon Territory, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-8, Landsat-9, Sentinel-2), and radar (RCM) based satellite images, and having a final spatial resolution of 30m. In conjunction with satellite acquisitions, ground-truth information was provided by: provincial crop insurance companies in Alberta, Saskatchewan, Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Kentville, Fredericton, Guelph, Summerland and Whitehorse. Forest Fire Perimeter Estimate polygons from Natural Resources Canada’s Canadian Forest Service are used to show burned areas of landcover (Class - 60).

Compilation of drillholes for mineral exploration and Quaternary studies in the Province of Saskatchewan, Canada.This dataset is compilation of uranium drillholes prior to 2007, and since that time has expanded to include metallic and industrial mineral exploration drillholes and surficial sedimentology drillholes. This is an ongoing compilation whereby recent drillholes that become publically available are added. In addition, improvements are frequently made to more historic drillholes with spurious information. The dataset is not an exhaustive list of drillholes in Saskatchewan. **Please Note – All published Saskatchewan Geological Survey datasets, including those available through the Saskatchewan Mining and Petroleum GeoAtlas, are sourced from the Enterprise GIS Data Warehouse.  They are therefore identical and share the same refresh schedule.

Small area data on field crops show seeded and harvested area, yield and production figures for most principal field crops and some special crops in Canada, at the census agricultural region level (except for Quebec, where small areas are defined by provincial administrative boundaries). The provinces covered are British Columbia, Alberta, Saskatchewan, Manitoba, Ontario and Quebec. The data are available in metric and imperial units of measure, for periods ranging from 1976 to 2024. The data are derived from the results of the November Farm Survey of the preceding year, of which the production estimates were only expressed at the provincial level in early December.

In 2010 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) continued the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5, DMC) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology.

In 2009 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began the process of generating annual crop inventory digital maps using satellite imagery. Focusing on the Prairie Provinces, a Decision Tree (DT) based methodology was applied using both optical (AWiFS, Landsat-5) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology.The initial methodology was developed in partnership with AAFC Research Branch, and supported in part by the Canadian Space Agency. The long-term objective of this endeavour is to expand from the Prairies and produce an annual crop inventory of the entire agricultural extent of Canada.