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).

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 applied using both optical (AWiFS, Landsat-5) and radar (RADARSAT-2) based satellite imagery, and having a final spatial resolution of 56m. Methods were also developed to enhance the optical classification with RADARSAT-2 imagery, addressing issues associated with cloud cover. In conjunction with satellite acquisitions, ground-truth information was provided by provincial crop insurance companies and point observations from our regional AAFC colleagues. The overall process for Crop Inventory Map includes: satellite data acquisition; field data acquisition for classification training and accuracy assessment; and, operational implementation of the classification methodology. The initial methodology was developed in partnership with AAFC Research Branch, and supported in part by the Canadian Space Agency. The long-term objective of this endeavour is to expand from the Prairies and produce an annual crop inventory of the entire agricultural extent of Canada.

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.

Contained within the 3rd Edition (1957) of the Atlas of Canada is a map that shows two condensed maps illustrating the division of Canada into agricultural regions based on the percentage of total gross farm revenue obtained from a particular source in 1951. The four primary divisions were made according to specific criteria. For Livestock Specialty divisions 70% or more of the gross farm revenue was from sales of livestock and livestock products. This was divided into three subdivisions: Dairy Emphasis, where sales of dairy products made up over 40% of total sales; Cattle Emphasis, where sales of cattle made up over 40% of sales; and General, where neither dairy products or cattle sales represented over 40% of total sales of livestock and livestock products. For Grain Specialty divisions 70% or more of the gross farm revenue was from sales of grain and hay. This was divided into two subdivisions: General, where no single crop acreage exceeded 40% of the total acreage; and Wheat, where the wheat acreage exceeded 40% of the total acreage. For Combination Grain and Livestock divisions less than 70% of the gross farm revenue was from either crops or livestock. This was divided into two subdivisions: Cash Crop Emphasis, where the gross revenue from cash crops and grain exceeded that of livestock; and Livestock Emphasis, where the gross revenue from livestock exceeded that from grain and cash crops. For Special Crops divisions 50% or more of the gross farm revenue was from some special crops. This was divided into three subdivisions: Tobacco or Potatoes, where 50% or more of the gross farm revenue was from sales of tobacco, potatoes or other root crops; Fruits and Vegetables, where 50% or more of the gross farm revenue was from sales of fruits and vegetables; and Forest Products, where 50% or more of the gross farm revenue was from sales of forest products. Variations within the subdivisions were the basis for a further breakdown into 266 regions to each of which a number and name were assigned.

Beginning with the 2011 grow season, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) started collecting ground truth data via windshield surveys. This observation data is collected in support of the generation of an annual crop inventory digital map. These windshield surveys take place in provinces where AAFC does not have access to crop insurance data. The collection routes driven attempt to maximize not only the geographical distribution of observations but also to target unique or specialty crop types within a given region. Windshield surveys are mainly collected by the AAFC Earth Observation team (Ottawa) with the support of regional AAFC Research Centres (St John’s NL; Kentville NS; Charlottetown PE; Moncton NB; Guelph ON; Summerland BC). Support is also provided by provincial agencies in British Columbia, Ontario, and Prince Edward Island, and by contractors when needed.

Statistics Canada conducts the Census of Agriculture every five years at the same time as the Census of Population. The most recent Census of Agriculture was on May 15, 2001.The Census of Agriculture collects and disseminates a wide range of data on the agriculture industry such as number and type of farms, farm operator characteristics, business operating arrangements, land management practices, crop areas, numbers of livestock and poultry, farm capital, operating expenses and receipts, and farm machinery and equipment. These data provide a comprehensive picture of the agriculture industry across Canada every five years at the national and provincial levels as well as at lower levels of geography. The Census of Agriculture is the cornerstone of Canada's Agriculture Statistics Program. Census of Agriculture data are an indispensable public and private sector tool for analysing important changes in the agriculture and food industries;developing, implementing and evaluating agricultural policies and programs such as farm income safety nets and environmental sustainability; and making production, marketing and investment decisions. Statistics Canada uses the data as benchmarks for its regular surveys on crops, livestock and farm finances between census years. In addition, data extracted from the unique Agriculture Population Linkage Database, which links data from both the Census of Population and Census of Agriculture databases, paint a socio-economic portrait not only of farm operators but also of their families and households. This release contains all farm data and farm operations data plus selected historical files. In 2001, a census farm was defined as an agricultural operation that produces at least one of the following products intended for sale: crops (hay, field crops, tree fruits or nuts, berries or grapes, vegetables, seed); livestock (cattle, pigs, sheep, horses, game animals, other livestock); poultry (hens, chickens, turkeys, chicks, game birds, other poultry); animal products (milk or cream, eggs, wool, furs, meat); or other agricultural products (Christmas trees, greenhouse or nursery products, mushrooms, sod, honey, maple syrup products). For 2001, a new farm type classification based on the North American Industrial Classification System (NAICS) has been added to the historical classification used in previous censuses. All tabulated data are subject to confidentiality restrictions prior to release. Due to confidentiality constraints, data for those geographic areas with very few agricultural operations are not released separately, but rather merged with a geographically adjacent area.

The Agriculture Capability mapping dataset is the digitized equivalent of the legacy Agriculture Capability Scanned Maps, which date from the 1960's to the 1990s. Agriculture Capability mapping is also known as 'Soil Capability for Agriculture' and 'Agricultural Capability' mapping. Agricultural Capability is an interpreted mapping product based on soil and climate information. In general, climate determines the range of crops possible in an area and the soils determine the type and relative level of management practices required. This is legacy data and changes in climate are not reflected. For more information about the classification system see: Land Capability Classification for Agriculture. Use caution utilizing these legacy maps as the classifications were based on common land management practices and typical crops of the 1960s-1990s era, and subsequent site specific land management practices (e.g. installation of drainage) may have modified the soil conditions since the mapping was completed. This Agriculture Capability legacy mapping is included in the Soil Information Finder Tool (SIFT) mapping application. The SIFT application provides more detailed climate data (e.g. Growing Degree Days, Frost Free Period (5 C), (1960-1990 climate normals). The SIFT 'Soil query tools' may be useful for identifying areas with specific 'growing conditions' of interest based on soils present (soil name), soil texture, drainage, coarse fragment content, slope, elevation, growing degree days and frost free period. Note: This Agriculture Capability Mapping dataset is based on soil mapping at 1:100,000, 1:50,000 or 1:20,000 scale, and is more detailed than the 1:250,000 scale Canada Land Inventory (CLI) Agricultural Capability mapping (available here).

There are two types of boundary files: cartographic and digital. Cartographic boundary files portray the geographic areas using only the major land mass of Canada and its coastal islands. Digital boundary files portray the full extent of the geographic areas, including the coastal water area.

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.

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.

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 maps the most probable crop type for every field in Canada, along with the land cover of non-agricultural lands (e.g. wetlands, forest, urban, etc.). It allows AAFC to study and model crop rotation patterns at the field level. To develop the Quantitative Crop Rotation Characteristics of Canada, historical ACI data representing the time series of crops at agricultural field level with annual intervals were applied. They provided the time series of categories of crops for statistical analyses. The results of this work included spatial data sets with several calculated attributes representing crop rotation statistical characteristics. Specifically, a crop sequence turbulence index was shown to be an efficient quantitative measure of mapping the spatial distribution of the sustainability of crop rotation in regions where dominantly annual crops were the active crop rotation. In addition, based on characteristics of observed crops in their time series sequence and the quantitative sequence dynamics represented by the turbulence index, major spatial clusters of crop rotation styles were calculated. To analyze the turbulence index, crop rotation cluster class representing the general style of crop rotation must also be considered. The crop rotation quantitative attributes calculated in this project which are at the field level, can be converted into useful information directing us towards the health and sustainability of crop rotations.

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 again produced a map of the agricultural regions in the Yukon Territory. 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; and data collection supported by our regional AAFC Research and Development Centres in St. John's, Kentville, Fredericton, Guelph, Summerland and Whitehorse. New this season, Forest Fire Perimeter Estimate polygons from Natural Resources Canada’s Canadian Forest Service were used to show burned areas of landcover. (Class - 60).

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.

Contained within the 5th Edition (1978 to 1995) of the National Atlas of Canada is a map that shows the distribution of Canada Land Inventory Capability classes for agriculture. Also shows Canada Land Inventory mapping boundary. Tables show summary of areas and crop limitations for each category in each province and territory.

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).Annual Crop Inventory

Canada Harmonized Agriculture Forest Land Cover 2015 The harmonized land cover (HLC) map is produced from Agriculture and Agri-Food Canada (AAFC) and Canadian Forest Service (CFS) data. The HLC product is exhaustive of all area from the northern edge of Canada’s forested ecosystems to the southern border. The land cover is following Intergovernmental Panel on Climate Change (IPCC) categories, represents the year 2015, and is at 30-m spatial resolution. This harmonized land cover map combines two sector-driven land cover products: the Virtual Land Cover Engine or VLCE from the CFS (Hermosilla et al., 2018), and AAFC's Annual Crop Inventory or ACI (Agriculture and Agri-Food Canada, 2018). The harmonization process was conducted using a Latent Dirichlet Allocation (LDA) model. The LDA model used regionalized class co-occurrences from multiple maps to generate a harmonized class label for each pixel by statistically characterizing land attributes from the class co-occurrences, using the information provided by the error matrices and semantic affinity scores. For a complete overview on the data, methods applied, and information on independent accuracy assessment, see Li et al. (2020). When using this data, please cite as: Li, Z., White, J.C., Wulder, M.A., Hermosilla, T., Davidson, A.M., Comber, A.J., 2020. Land cover harmonization using Latent Dirichlet Allocation. International Journal of Geographical Information Science. DOI: https://doi.org/10.1080/13658816.2020.1796131 (Open access) ( Li et al. 2020). For additional resources on the data used and methods applied, please see: Hermosilla, T., Wulder, M.A., White, J.C., Coops, N.C., Hobart, G.W., 2018. Disturbance-informed annual land cover classification maps of Canada’s forested ecosystems for a 29-year Landsat time series. Canadia Journal of Remote Sensing 44(1), 67-87. https://doi.org/10.1080/07038992.2018.1437719 (Open access) ( Hermosilla et al. 2018). Agriculture and Agri-Food Canada, 2018. Annual Crop Inventory [WWW Document]. URL https://open.canada.ca/data/en/dataset/ba2645d5-4458-414d-b196-6303ac06c1c9. ( AAFC, 2018. Annual Crop Inventory ).

Contained within the 4th Edition (1974) of the Atlas of Canada is a set of two maps showing for 1960, the total precipitation for April to September and the variation from average precipitation for April to September. Also included on this map plate is a set of graphs showing farmland use and value of agricultural production for 1961 and for the period 1956 to 1967; percentage of acreage by crop, make up of fruit crops, greenhouse and nursery industry, forest and maple products summary, egg and dairy product summary and livestock summaries.

Contained within the 5th Edition (1978 to 1995) of the National Atlas of Canada is a map that shows the land where data exists as: land in agricultural use, land not in agricultural use but capable of limited agriculture and non-agricultural land. The map uses 1971 data from Canada Land Inventory.

Contained within the 4th Edition (1974) of the Atlas of Canada is a map that shows the number of agricultural products by census division that are statistically significant in terms of value of sales from farms for 1961. The accompanying text is an overview of the Agriculture section of the 4th Edition National Atlas.

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.