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

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

In 2010 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) continued 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, DMC) 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. For more information, visit: http://open.canada.ca/data/en/dataset/6dc5170d-4167-47e4-b80a-93ed2b47f023

Soil and drainage and soil slope maps for Canada (SLC, 1:1,000,000), and detailed soil drainage and soil slope maps for British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Nova Scotia, and Prince Edward Island. Soil zones of the prairies is also included as a separate layer.

This data series represents the volumetric soil moisture (percent saturated soil) for the surface layer, expressed as a difference from the long term average. The average is calculated from all available years for each location and each time period, based on the length of the satellite data record. Values higher than zero represent areas that are wetter than the long term average, and areas lower than zero represent areas drier than the long term average. The data is created daily and is averaged for the ISO standard week and month. The data is produced from passive microwave satellite data collected by the Soil Moisture and Ocean Salinity (SMOS) satellite and converted to soil moisture using version 6.20 of the SMOS soil moisture processor. The data are produced by the European Space Agency and obtained under a Category 1 proposal for Level 2 soil moisture data. The data are gridded to a resolution of 0.25 degrees. Data quality flags have been applied to remove areas where rainfall is present during the acquisition, where snow cover is detected and when Radio Frequency Interference (RFI) is above an acceptable threshold. For more information, visit:http://open.canada.ca/data/en/dataset/723bbb4c-d209-4599-b39b-0ede5a0a0371