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

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. For more information, visit: http://open.canada.ca/data/en/dataset/ce7873ff-fbc0-4864-946e-6a1b4d739154

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 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

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

The source of the layers in this mxd are derived products originating from the Agri-Environmental (AEI) dataset series. The original source data was re- formatted to enable time display on the layers, with individual soil landscape polygons being dissolved out to allow web optimization. For Layer Names with a year in the title, the source points to the Time Series Datasets, however they have a definition query applied to only display the data corresponding t o a particular year. The datasets in the series should be used in web applications only.

The AAFC Infrastructure Flood Mapping in Saskatchewan - 50 centimetres is the LiDAR contours with an interval of 0.5m of the capture area of Saskatchewan. The contours were modeled from the ground class at a maximum vertical distance of 0.5m and a horizontal distance of 20 m. Breaklines were not used around water features therefore a uniform height of water bodies is not necessarily present if overlapping data was collected on different days. Major contours were defined every 5m and minor contours every 0.5 m. For more information, visit: http://open.canada.ca/data/en/dataset/4e964f96-1821-4214-9247-1faacda5af9c

This data series represents the volumetric soil moisture (percent saturated soil) for the surface layer (<5 cm). The data is created daily and is averaged for the ISO standard week and month. The datais produced from passive microwave satellite data collected by the Soil Moisture and Ocean Salinity (SMOS) satellite and converted to soil moisture using version 5.51 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/a0533280-2bf6-40ba-a126-bc7ed2336017

The Agriculture and Agri-Food Canada's LiDAR Projects dataset was created from existing spatial data. It contains the footprints (outlines) of all the LiDAR data that is openly distributed by Agriculture and Agri-Food Canada. LiDAR (Light Detection And Ranging) is a method of acquiring survey points using optical remote sensing technology. The dataset indicates basic information about the location, source and properties of the data. For more information, visit: http://open.canada.ca/data/en/dataset/a760f9e0-7013-4187-9261-2e69b01edd9a

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