The "Canada's First Fall Frost Normals (1981-2010)" dataset contains the Mean and Median First Fall Frost Julian day calculated from the ANUSPLIN gridded data set using the date range from January 1, 1981 - December 31, 2010. The dataset also includes the Mean and Median Frost Free Period (given as a count of calendar days). For the purposes of this dataset a Frost Free day is defined as a day where the minimum daily temperature is greater than 0.0 Celsius.For more information, visit: http://open.canada.ca/data/en/dataset/c293739c-4e16-4384-bff8-e3fdaddc5e5f

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

This dataset is aligned to a grid that with a dataset of soil attributes following GlobalSoilMap standards and specifications at specified depth increments extending over the agricultural portion of Canada. The SLC map polygons were rasterized and combined with the Shuttle Radar Topography Mission (SRTM) 90 metre grid to create the gridded raster dataset. Weighted averages of soil attribute properties are generated from existing soil horizon information to conform to recognized fixed depth increments. Soil attribute weighted means are calculated by using all the soil components based on their areal extent in each SLC polygon. The polygonal attribute weighted mean averages are spatially represented by the grid. For more information, visit: http://open.canada.ca/data/en/dataset/cb29b370-3639-4645-9ef9-b1ef131837b7

Contour Lines generated from LiDAR data captured by McElhanney Consulting Services Ltd (MCSL). The contour lines connect points of equal elevation for the landscape covered by this project. For more information, visit: http://open.canada.ca/data/en/dataset/9bdc1a9c-baf7-4eb0-a532-c1057b284b8f

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, 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: https://open.canada.ca/data/en/dataset/cb3d7dec-ecc6-498b-ac17-949e03f29549

Topographic data for lakes within the Qu'Appelle River Valley in central Saskatchewan. This data was collected in the fall of 2008 and consists of contour lines, shorelines, spot heights, and tile index. For more information, visit: http://open.canada.ca/data/en/dataset/d838afd0-8918-42e1-acdd-8c69f9b5a7e1

In 2018, 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 (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: https://open.canada.ca/data/en/dataset/1f2ad87e-6103-4ead-bdd5-147c33fa11e6

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 (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/4b1d45b0-5bfe-4c6d-bcd3-96c9d821ad3b

The "Science Strategies Summary by CCS (2016)" data was derived from the 2016 Census of Agriculture using published and draft documentation describing the Science Strategies defined by the AAFC Science and Technology Branch. It was created for facilitating the geographic description, analysis, and reporting of the sectors. NOTE: The geometry in this service has been generalized from the original for quicker display. For more information, visit: http://open.canada.ca/data/en/dataset/0313f880-492c-4f4e-95ef-f53e4216576d

This dataset is aligned to a grid that with a dataset of soil attributes following GlobalSoilMap standards and specifications at specified depth increments extending over the agricultural portion of Canada. The SLC map polygons were rasterized and combined with the Shuttle Radar Topography Mission (SRTM) 90 metre grid to create the gridded raster dataset. Weighted averages of soil attribute properties are generated from existing soil horizon information to conform to recognized fixed depth increments. Soil attribute weighted means are calculated by using all the soil components based on their areal extent in each SLC polygon. The polygonal attribute weighted mean averages are spatially represented by the grid. For more information, visit: http://open.canada.ca/data/en/dataset/cb29b370-3639-4645-9ef9-b1ef131837b7