The "South Tobacco Creek Watershed - 10 cm Contours" dataset is a linear representation of the LiDAR DEM data set to the closest 0.1 meters. For more information, visit: http://open.canada.ca/data/en/dataset/734078a9-9aa1-44a1-9e74-dc9387a9ecfe

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 Canada (SLC) and the 1996 Census of Agriculture, the Prairies were classified into 13 (thirteen) classes of Land Practices Group and five (5) Major Land Practices Groups. Typical attributes used to define the Land Practice Groups include: land in pasture, land in summerfallow, crop mixture, farm size and the level of chemical and fertilizer inputs. The five (5) Major Groups were devised to help better understand the relationships between the groups. For more information, visit: https://open.canada.ca/data/en/dataset/0b2303be-ef05-49a8-8082-44a3eabcfa57

This data shows spatial density of Corn cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Corn 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 Corn based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/92f73de5-5f46-4a8c-bc5f-c3872f268ecb

These agricultural capability / Limitation maps can be used at the regional level for making decisions on land improvement and farm consolidation, for developing landuse plans, and for preparing equitable land assessments. For more information, visit: http://open.canada.ca/data/en/dataset/0c113e2c-e20e-4b64-be6f-496b1be834ee

LiDAR Services International (LSI), a Calgary based LiDAR company completed an airborne LiDAR survey for the Redberry Lake Biosphere Reserve (RLBR) and Agriculture and Agri-Foods Canada (AAFC) in October 2011. The project involved collection of LiDAR data for a 362.97 km2 block area, 252.77 km2 for Redberry Lake and 110.20 km2 for AAFC northwest of Saskatoon, SK. For more information, visit: http://open.canada.ca/data/en/dataset/c12645b7-4f70-4c37-808d-0b1ff3bd0051

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 2015 AAFC annual crop inventory data.For more information, visit: http://open.canada.ca/data/en/dataset/e0df876e-f56f-4797-8a7d-758e23bfa2b8

The Plant Hardiness Zones map outlines the different zones in Canada where various types of trees, shrubs and flowers will most likely survive. It is based on the average climatic conditions of each area. The first such map for North America, released by the United States Department of Agriculture in 1960, was based only on minimum winter temperatures. In 1967, Agriculture Canada scientists created a plant hardiness map using Canadian plant survival data and a wider range of climatic variables, including minimum winter temperatures, length of the frost-free period, summer rainfall, maximum temperatures, snow cover, January rainfall and maximum wind speed. Natural Resources Canada's Canadian Forest Service scientists have now updated the plant hardiness zones using the same variables and more recent climate data (1961-90). They have used modern climate mapping techniques and incorporated the effect of elevation. The new map indicates that there have been changes in the hardiness zones that are generally consistent with what is known about climate change. These changes are most pronounced in western Canada. The new hardiness map is divided into nine major zones: the harshest is 0 and the mildest is 8. Subzones (e.g., 4a or 4b, 5a or 5b) are also noted in the map legend. These subzones are most familiar to Canadian gardeners. Some significant local factors, such as micro-topography, amount of shelter and subtle local variations in snow cover, are too small to be captured on the map. Year-to-year variations in weather and gardening techniques can also have a significant impact on plant survival in any particular location. For more information see: http://open.canada.ca/data/en/dataset/50f9f293-f288-4de6-98ad-f69cf85d21ea

The 'Circa 1995 Landcover of the Prairies' dataset is a geospatial raster data layer portraying the rudimentary land cover types of all grain-growing areas of Manitoba, Saskatchewan, Alberta and northeastern British Columbia at a 30-metre resolution for the 1995 timeframe. It is the collection of all the classified imagery (1993 to 1995) of the Western Grain Transition Payment Program (WGTPP) assembled into a single seamless raster data layer. For more information, visit: http://open.canada.ca/data/en/dataset/e9dee957-e04d-46fb-b7e4-701739736173

The 1990 Land Use (LU) map covers all areas of Canada south of 60oN at a spatial resolution of 30 metres. The LU classes follow the protocol of the Intergovernmental Panel on Climate Change (IPCC) and consist of: Forest, Water, Cropland, Grassland, Settlement and Otherland. The 1990 Land Use (LU) map was developed in response to a need for explicit, high-accuracy, high-resolution land use data to meet AAFC's commitments in international reporting.For more information, visit: http://open.canada.ca/data/en/dataset/02202cec-b4a1-4a1d-9997-edcbaca92d41

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, and Quebec; point observations from the BC Ministry of Agriculture, and 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. For more information, visit: http://open.canada.ca/data/en/dataset/b8e4da73-fb5f-4e6e-93a4-8b1f40d95b51