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

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

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

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

This data shows spatial density of Canola cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Canola 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 Canola based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/a1da661a-55b6-4ef5-936a-fb1b6f4fa486

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. For more information, visit: http://open.canada.ca/data/en/dataset/3688e7d9-7520-42bd-a3eb-8854b685fef3

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. For more information, visit: http://open.canada.ca/data/en/dataset/3688e7d9-7520-42bd-a3eb-8854b685fef3

This data shows spatial density of Wheat cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Wheat 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 Wheat based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/a9e958ab-94db-484b-9a6e-7ec74f6b5a25

This data shows spatial density of pulses cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which pulese 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 pulses based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/f6d91e82-c783-4a63-8235-7bf53b16b706

The 2000 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 2000 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/b5f413d9-9acc-4ad7-b9a7-38486ed5fee7