Agriculture and Agri-Food Canada

OneSoil employs a proprietary machine learning (ML) model based on state-of-the-art instance segmentation to detect field boundaries. Utilizing raw Sentinel-2 data aggregated according to local vegetation season maps and an additional upscaling module to enhance boundary accuracy, we ensure...

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...

In 2023, 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. This year we...

The “Agricultural Major Land Practices Groups of the Canadian Prairies” dataset lays out the areas of the 5 Major Land Practices Groups of the agricultural portions of the Canadian Prairies. They are represented by vector polygons amalgamated (dissolved) from the Version 1.9 SLC polygons sharing...

The Agriculture and Agri-Food Canada (AAFC) Annual Crop Inventory (ACI) is produced at a national scale, covering Canada’s entire agricultural extent. It has been generated operationally since 2011 for the entire country (2009 for the Prairie Provinces). This product is spatially continuous and...

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...

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...

The “Agricultural Land Practices Groups of the Canadian Prairies” dataset lays out the areas of the 13 Land Practices Groups of the agricultural portions of the Canadian Prairies. They are represented by vector polygons amalgamated (dissolved) from the Version 1.9 SLC polygons sharing common...

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...

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...

In 2011, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) expanded the process of generating annual crop inventory digital maps using satellite imagery to include British Columbia, Ontario, Quebec, and the Maritime provinces, in...

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...

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 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...

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 “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...

These products represent crop health indices derived from the Versatile Soil Moisture Budget (VSMB) model using crop specific coefficients and station based precipitation and temperature measurements to simulate crop growth. The VSMB model simulates soil moisture dynamics and water stress...

This data set was compiled by AAFC from the historic yields of major crops as provided by Statistics Canada and provides support on estimates of crop yield and related statistics.