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

The cloud-corrected NDVI data extracted from historical MODIS satellite images at 250 metre resolution provides reliable, objective, and timely information on the state of vegetation throughout Canada and the northern United States. The methodology applied to the images has remained the same as for the program formerly known as the Crop Condition Assessment Program (CCAP). Since the 2000 growing season, Statistics Canada has been processing and compiling MODerate-resolution Imaging Spectoradiometer (MODIS) data (250 metre resolution). The Multi-Spectral Instrument (MSI) captures two spectral bands (red and infrared) that have proven to be extremely useful to produce the Normalized Difference Vegetation Index (NDVI) utilized for vegetation monitoring. The original NDVI image composites were produced by Agriculture and Agri-Food Canada (link to original data in the resources section). Additional computations were completed by Statistics Canada to remove the effects of residual clouds and to calculate and extract the NDVI by geographic region. This dataset provides access to the MODIS images from 2000 to present in GeoTIFF format and covers the crop area during the growing season (Julian weeks 15 to 37; mid-April to mid-September). It also provides access to a database that contains the statistical NDVI by geographic regions (Townships, Census Consolidated Subdivisions (CCS), Census Divisions (CD) and Census Agricultural Regions (CAR)) and agricultural masks (Agriculture (AGR), Crop (CROP) and Pasture (PAS)).

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

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

In 2020, 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) 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, Manitoba, & Quebec; point observations from the PEI Department of Environment, Water and Climate Change; 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, Charlottetown, Fredericton, and Guelph. Due to COVID-19 travel restrictions, complete sampling coverages in NL, NS, NB and BC were not possible, as a result the general agriculture class (120) is found in these provinces in areas where there was no ground data collected.

Crop rotation is an agricultural production and land management practice beneficial to sustainable agriculture in Canada. Agriculture and Agri-Food Canada (AAFC) produces crop rotation data annually showing the crop rotations used within the agricultural extent of Canada for the last four complete growing seasons (based on available data). This data can be used by producers, land managers, and policy makers to assess current rotations to assist in future land management decisions.Crop rotation data is derirved from AAFC's publicly-available annual crop inventory data.

Feature point layer showing locations of co-packer services in Manitoba. null

Fish stocking records from Nova Scotia fish hatcheries. Includes trout and salmon stocking, size, number, location, stock and growth stage. Records contain both fall and spring distributions.

The cloud-corrected representation of the NDVI using historical AVHRR and VIIRS satellite images at 1 kilometre resolution provides reliable, objective and timely information on the state of vegetation throughout Canada and the northern United States. The methodology applied to the images has remained the same as for the program formerly known as the Crop Condition Assessment Program (CCAP). Since 1987, the National Oceanic and Atmospheric Administration (NOAA) series of satellites carrying the Advanced Very High-Resolution Radiometer (AVHRR) records images of the entire Earth's surface twice a day at 1kilometre resolution. This sensor captures two spectral bands (red and infrared) that have proven to be extremely useful for vegetation monitoring to produce the Normalized Difference Vegetation Index (NDVI). NDVI image composites on crop condition were produced by GeoManitoba until the end of the 2020 growing season. In 2021, Statistics Canada started producing the weekly composites using an application developed by Dr. Rasim Latifovic from National Resources Canada. Since 2022, due to the aging AVHRR sensor affecting the quality of the weekly composites, the team has transitioned to the NOAA-20 - Visible Infrared Imaging Radiometer Suite (VIIRS) satellite. VIIRS is a new-generation satellite with spectral characteristics comparable to those of its predecessor. To keep the NDVI values stable and continuous throughout the time series, the VIIRS composite values are normalized to obtain comparable NDVI values. Additional computations were performed by Statistics Canada for Julian weeks 15 to 41 to remove residual clouds from the NDVI composites and statistical extractions by geographic regions using three different types of agricultural masks. This dataset gives access to AVHRR images from 1987 to mid-2022 and VIIRS images from mid-2022 to present in GeoTIFF format and covers the agricultural land during the growing season of the field crops in Canada (Julian weeks 15 to 41). It also provides access to a database that contains the statistical NDVI by geographic regions (Townships, Census Consolidated Subdivisions (CCS), Census Divisions (CD) and Census Agricultural Regions (CAR)) and agricultural masks (Agriculture (AGR), Crop (CROP) and Pasture (PAS)).

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