The Grain Elevators in Canada - 2021 dataset maps the list of grain elevators in Canada as provided by the Canadian Grain Commission (CGC). The elevators have been located as much as possible to an actual location rather than generalizing to the station name centroid. Additionally car spot information from CN, CP and the grain companies has been added where this has been published. This dataset attempts to provide a temporal and geographical extent of the grain elevators in Canada.

The Grain Elevators in Canada - 2018 dataset maps the list of grain elevators in Canada as provided by the Canadian Grain Commission (CGC). The elevators have been located as much as possible to an actual location rather than generalizing to the station name centroid. Additionally car spot information from CN, CP and the grain companies has been added where this has been published. This dataset attempts to provide a temporal and geographical extent of the grain elevators in Canada.

The Census of Agriculture is disseminated by Statistics Canada's standard geographic units (boundaries). Since these census units do not reflect or correspond with biophysical landscape units (such as ecological regions, soil landscapes or drainage areas), Agriculture and Agri-Food Canada in collaboration with Statistics Canada's Agriculture Division, have developed a process for interpolating (reallocating or proportioning) Census of Agriculture information from census polygon-based units to biophysical polygon-based units. In the “Interpolated census of agriculture”, suppression confidentiality procedures were applied by Statistics Canada to the custom tabulations to prevent the possibility of associating statistical data with any specific identifiable agricultural operation or individual. Confidentiality flags are denoted where "-1" appears in data cell. This indicates information has been suppressed by Statistics Canada to protect confidentiality. Null values/cells simply indicate no data is reported.

The data represents the relative amount of manure production in the agricultural area of Alberta. It is an estimate of the degree to which livestock production may contribute to nutrient loading, pathogens and odour. The classes shown on the map are ranked between 0 (lowest) and 1 (highest). This resource was created in 2002 using ArcGIS.

Web application showing locations of Manitoba companies that offer agri-food by-products and/or related services. This web application shows the geographical locations of Manitoba companies that offer agri-food by-products and/or related services. This list is not inclusive nor an endorsement for services. For more information, visit Manitoba Agriculture. Contact Manitoba Agriculture at agindustrydev@gov.mb.ca to have your business added to the listing.   This app uses the Manitoba Agri-Food By-Product Directory feature layer and the Manitoba Agri-Food By-Product Map.

The Estimated Historical Crop Yields in Canada by SLC (kg\hectare) dataset is produced by combining three complementary sources of yield information at the Soil Landscapes of Canada (SLC) level. First, provincial-level yields for seven major crops are allocated down to SLC polygons using area-based adjustments and statistical scaling. Second, forage yields (alfalfa, improved pasture, unimproved pasture) are taken directly from the EPIC model, which already outputs data at the SLC level. Third, insurance yield datasets (for the Prairies) are linked to SLC polygons and incorporated where available. These three sources are harmonized, ensuring consistency across crops and regions, resulting in a comprehensive SLC-level crop yield dataset for national-scale modeling and reporting. This dataset was created primarily in support of Statistics Canada’s Census of Environment. This data can also be used for national scale modelling, calibration of agricultural models, and reporting for the agri-environmental indicators.

The Canada Land Inventory (CLI), 1 100,000, Land Capability and Limitation for Agriculture dataset illustrates the varying potential of a specific area for agricultural production. Classes of land capability for agriculture are based on mineral soils grouped according to their potential and limitations for agricultural use. The classes indicate the degree of limitation imposed by the soil in its use for mechanized agriculture. The subclasses indicate the kinds of limitations that individually or in combination with others, are affecting agricultural land use. Characteristics of the soil as determined by soil surveys.

The “Biomass Agriculture Inventory 1-in-10 Probability” dataset is a table that contains the estimated 1-in-10 year low for agricultural residue yield and crop production for each Biomass Report Framework. It provides the tenth percentile values for the years 1985-2016. The table includes straw or stover information for barley, wheat, flax, oats and corn, and crop information for barley, wheat, flax, oats, corn, canola and soybean. This dataset also includes information about the type of tillage used in the area and demand for straw for cattle bedding and feed. These values are derived from Statistics Canada data. Additionally, the dataset includes the amount of agricultural residue calculated as necessary to remain on the field to prevent soil degradation. Soil degradation is determined by the type of tillage in use as well as the landscape of the area.

The Grain Elevators in Canada – 2017 dataset maps the list of grain elevators in Canada as provided by the Canadian Grain Commission (CGC). The elevators have been located as much as possible to an actual location rather than generalizing to the station name centroid. Additionally car spot information from CN, CP and the grain companies has been added where this has been published. This dataset attempts to provide a temporal and geographical extent of the grain elevators in Canada.

In 2019, 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) 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 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, Charlottetown, Fredericton, and Guelph.