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 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

This data shows spatial density of Soybean cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Soybeans 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 Soybeans based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/7c444a60-3b82-48d9-a197-efdff0154aaf

The 2010 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 2010 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/9e1efe92-e5a3-4f70-b313-68fb1283eadf

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.

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/17c46ff1-ae53-4835-9ff8-573f835e316c

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

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 Evaporative Stress Index (ESI) describes temporal anomalies in evapotranspiration (ET), highlighting areas with anomalously high or low rates of water use across the land surface. Here, ET is retrieved via energy balance using remotely sensed land-surface temperature (LST) time-change signals. LST is a fast- response variable, providing proxy information regarding rapidly evolving surface soil moisture and crop stress conditions at relatively high spatial resolution. The ESI also demonstrates capability for capturing early signals of "flash drought", brought on by extended periods of hot, dry and windy conditions leading to rapid soil moisture depletion. ESI values quantify standardized anomalies (σvalues) in the ratio of clear-sky actual-to-potential ET (fPET), derived using thermal infrared (TIR) satellite imagery from geostationary platforms. To capture a range in timescales, fPET composites are developed for 1, 2 and 3 month moving windows, advancing at 7-day intervals. Standardized anomalies are then computed with respect to normal conditions (mean and standard deviation) for each compositing interval assessed over a period of record from 2000-2015. For more information, visit: http://open.canada.ca/data/en/dataset/679f676a-330a-456f-9928-a4fafc95f9f8

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