A series of relevant spatial datasets were compiled to construct an Agricultural Potential Index model which combines multiple criteria that influence agricultural suitability.  For more information on the Agriculutural Potential Index Model, please see the metadata link.

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 (DT) based methodology was applied using optical (Landsat-8, Sentinel-2, Gaofen-1) 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 BC Ministry of Agriculture, & 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, Kentville, Charlottetown, Fredericton, Guelph, and Summerland.

In 2021, 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 (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 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, Charlottetown, Kentville, Fredericton, Guelph and Summerland. Due to COVID-19 travel restrictions and forest fires, complete sampling coverages in BC was not possible, as a result the general agriculture class (120) is found in this province in areas where there was no ground data collected.

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 (DT) based methodology was applied using optical (Landsat-8, Sentinel-2, Gaofen-1) 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 BC Ministry of Agriculture, & 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, Kentville, Charlottetown, Fredericton, Guelph, and Summerland

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: provincialcrop 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.

In 2015, 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) 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 and point observations from the BC Ministry of Agriculture and our regional AAFC colleagues.

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.

Understanding the state and trends in agriculture production is essential to combat both short-term and long-term threats to stable and reliable access to food for all, and to ensure a profitable agricultural sector. Starting 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 type digital maps. Focusing on the Prairie Provinces in 2009 and 2010, a Decision Tree (DT) based methodology was applied using optical (Landsat-5, AWiFS, DMC) and radar (Radarsat-2) based satellite images. Beginning with the 2011 growing season, this activity has been extended to other provinces in support of a national crop inventory. To date this approach can consistently deliver a crop inventory that meets the overall target accuracy of at least 85% at a final spatial resolution of 30m (56m in 2009 and 2010).

These files from Statistics Canada present Census of Agriculture data allocated by standard census geographic polygons: Provinces and Territories (PR), Census Agricultural Regions (CAR), Census Divisions (CD) and Census Consolidated Subdivisions (CCS). Five datasets are provided:1. Agricultural operation characteristics: includes information on farm type, operating arrangements, paid agricultural work and financial characteristics of the agricultural operation.2. Land tenure and management practices: includes information on land use, land tenure, agricultural practices, land inputs, technologies used on the operation and the renewable energy production on the operation.3. Crops: includes information on hay and field crops, vegetables (excluding greenhouse vegetables), fruits, berries, nuts, greenhouse productions and other crops.4. Livestock, poultry and bees: includes information on livestock, poultry and bees.5. Characteristics of farm operators: includes information on age, sex and the hours of works of farm operators.Note: For all the datasets, confidential values have been assigned a value of -1.Correction notice: On January 18, 2023, selected estimates have been corrected for selected variables in the following 2021 Census of Agriculture domains: Direct sales of agricultural products to consumers (Agricultural operations category), Succession plan for the agricultural operation (Agricultural operators category), and Renewable energy production (Use, tenure and practices category).

Get a list of provincially licensed operators that collect, transport, process and dispose of deadstock (dead farm animals) in Ontario. This dataset includes facility type, name, location/region and contact information of licensed deadstock operators in Ontario. The Ministry of Agriculture, Food and Agribusiness and the Ministry of the Environment, Conservation and Parks, in consultation with stakeholders, have developed regulations for the disposal of deadstock (dead farm animals) in Ontario. The regulations provide more disposal options for livestock producers and meat plant operators, with measures to protect the environment.