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.

This data shows spatial density of Cereals cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Cereals 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 Cereals based on analysis of the 2009 to 2021 AAFC annual crop inventory data. Cereals consist of the following specific crop types from the AAFC annual crop inventory; Cereals, Barley (including Spring and Winter), Greenfeed / Mixed Cereals, Millet, Oats, Rye (including Spring and Winter), Spelt, Triticale (including Spring and Winter), Wheat (including Spring and Winter), and Other Cereal

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.

[Archived] Deployment locations and configuration details of Acoustic Doppler Current Profilers (ADCPs) included in the Centre for Marine Applied Research’s (CMAR) “Current Data” county datasets. This data has not been maintained or updated. Users looking for the latest information should refer to Nova Scotia Current and Wave Data: Deployment Information https://data.novascotia.ca/d/uban-q9i2.

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.

This data shows spatial density of Wheat cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Wheat is 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 Wheat based on analysis of the 2009 to 2021 AAFC annual crop inventory data. Wheat consists of all types of wheat including winter wheat from the AAFC annual crop inventory.

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 following dataset correspond to the 230 m agricultural mask from Statistics Canada’s Crop Condition Assessment Program (CCAP). The mask have been generated from the classes 110 to 199 of the 2015 Agriculture and Agri-Food Canada’s landcover classification. The selection was then generalized to a spatial resolution of 230 m. The 2015 mask was used from the 2015 to the 2018 growing seasons inclusively.

In 2022, 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, in support of a national crop inventory. New this year, a map of the agricultural regions in the Yukon Territory was also produced. 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; Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph - Ridgetown campus; British Columbia Ministry of Agriculture; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Kentville, Fredericton, Guelph, Summerland and Whitehorse.

This data shows spatial density of lentil cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Lentils lentils 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 Lentils lentils based on analysis of the 2009 to 2021 AAFC annual crop inventory data.