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

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

The "AAFC Annual Unit Runoff in Canada - 2013" report aims to illustrate runoff trends across the country by calculating annual unit runoff for a variety of probabilities of exceedence commonly used by decision makers. Annual unit runoff is a measure of runoff volume per square kilometre. It includes a point data set for the hydrologic stations that were analyzed and seven sets of linework to show the adjusted isolines for 10%, 25%, 50%, 70%, 75%, 80%, and 90% probability of exceedence. It is an update and expansion of the work completed in the 1994 report "Annual Unit Runoff on the Canadian Prairies". For more information, visit: http://open.canada.ca/data/en/dataset/a905bafc-74b5-4ec5-b5f9-94b2e19815d0

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

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

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/7dd83e31-c843-421d-9764-e0569b40ee33

The National Ecological Framework for Canada provides a consistent, national spatial framework that allows various ecosystems to be described, monitored and reported on. It provides standard ecological units that allow different jurisdictions and disciplines to use common communication and reporting, and a common ground to report on the state of the environment and the sustainability of ecosystems in Canada. The framework was developed between 1991 and 1999 by the Ecosystems Science Directorate, Environment Canada and the Center for Land and Biological Resources Research, Agriculture and Agri-Food Canada. Over 100 federal and provincial agencies, non-governmental organizations and private sector companies contributed to its development. For more information, visit: http://open.canada.ca/data/en/dataset/3ef8e8a9-8d05-4fea-a8bf-7f5023d2b6e1

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 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 2014, 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 our regional AAFC colleagues. For more information, visit: http://open.canada.ca/data/en/dataset/ae61f47e-8bcb-47c1-b438-8081601fa8fe