Agriculture and Agri-Food Canada

In 2013, 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...

In 2014, 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...

This data series was compiled by AAFC and Statistics Canada using a combination of agroclimate data and satellite-derived Normalized Difference Vegetation Index (NDVI) data for the current growing season. The forecast is made based on a statistical model using historical yield, climate and NDVI...

In 2012, 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 (except Newfoundland), in support of a national crop...

Information about fees the department may charge under the Service Fees Act; policy on remissions of fees.

AAFC has been conducting the Strategic Issues Survey, a survey of producers, since 2007. The research is designed to provide insight into the views of producers on current agricultural issues in Canada and on priorities and policies that affect the agriculture and agri-food sector. The survey...

Building on previous research waves in 2011 and 2016, Agriculture and Agri-Food Canada (AAFC) launched a third wave of public opinion research to assess Canadians’ perceptions and attitudes towards emerging agricultural technologies and their applications in the sector, and to gather information...

This data series was compiled by AAFC and Statistics Canada using a combination of agroclimate data and satellite-derived Normalized Difference Vegetation Index (NDVI) data for the current growing season. The forecast is made based on a statistical model using historical yield, climate and NDVI...

This data represents the dryness of the land surface based on vegetation conditions. The data is created weekly and uses weekly information on precipitation anomalies (namely the Standardized Precipitation Index or SPI) and satellite vegetation condition derived from Normalized Difference...

The probability of effective growing season degree days above 100 for warm season crops. This condition must be maintained for at least 5 consecutive days in order for EGDD to be accumulated (egdd_warm_100prob). Week 1 and week 2 forecasted probability is available daily from April 1 to October...

LiDAR data collected in 2018 of water control structures in Tennaille, Newton, and Huff Lake in Saskatchewan, Canada. Includes Digital Terrain Models, Contours, and Orthorectified imagery. LiDAR Data to be used by AAFC to assess whether additional land control should be pursued and other...

AAFC’s Canadian Ag-Land Monitoring System (CALMS), operational since 2009, was developed by AAFC’s Earth Observation Service (EOS) to deliver weekly NDVI-based maps of crop condition in near-real-time. The CALMS uses data collected by the Moderate Resolution Imaging Spectro-radiometer (MODIS), a...

This table contains quality-controlled weather station data from various sources across Canada since 2006.

This data shows spatial density of oats cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which oats are more expected. Results are provided as rasters with numerical values for each pixel indicating the spatial density calculated...

Agriculture is an important primary production sector in Canada. Agricultural production, profitability, sustainability and food security depend on many agrometeorological factors, including drought. The Canadian Drought Outlook predicts whether drought across Canada will emerge, stay the same...

The Crop Stress Index is the ratio of actual evapotranspiration (AET) to potential evapotranspiration (PET) express as: CSI = 1-(AET/PET) AET and PET are calculated within the Versatile Soil Moisture Budget (VSMB) model using temperature and precipitation data and a crop-specific...

The “Prairie Agricultural Landscapes (PAL)” datasets identify areas of the agricultural portions of the Canadian Prairies with similar land and water resources, land use and farming practices. They are represented by vector polygons. Based on selected attributes from the Soil Landscapes of...

The Versatile Soil Moisture Budget (VSMB) is a soil water budget model that is continuous and deterministic in nature and was developed by AAFC. It is based on the premise that the water available for plant growth is gained by precipitation or irrigation, and lost through evapotranspiration and...

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...

Crop development stage in a numerical scale. All living organisms move from one stage of development to the next over time. For annual crops, it life cycle (growing season) completed within a year. Crop water use differs from one stage to another mostly due to the differences in the amount of...