The “Oilseeds Science Sector by CCS” data was derived from the 2011 Census of Agriculture using published documentation describing the Science Sector. It was created for facilitating the geographic description, analysis, and reporting of the sector. The selection of 2011 Census of Agriculture variables was derived from the “AAFC Science and Technology Branch Science Strategy for the AgriFood Sector “Oilseed sector”” ;“At present, the strategy covers the following crop types: canola and rapeseed, mustard, soybeans (oilseed and food-grade), flax, sunflower, hemp, safflower” NOTE: The identified “hemp” and “safflower” making up part of the this sector are not included in this dataset because the data, although collected in the 2011 Census of Agriculture, was published as “Other crops” along with a number of other crops not included in this scope of this sector. For more information, visit: www.agr.gc.ca/atlas/metadata/1f4dcc5c-23d8-4b08-a98e-64c1c93f083c

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

In 2011, the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) expanded the process of generating annual crop inventory digital maps using satellite imagery to include British Columbia, Ontario, Quebec, and the Maritime provinces, in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (Landsat-5, DMC) 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/58ca7629-4f6d-465a-88eb-ad7fd3a847e3

The Grain Elevators in Canada dataset maps the list of grain elevators in Canada as provided by the Canadian Grain Commission (CGC). The elevators have been located as much as possible to an actual location rather than generalizing to the station name centroid. Additionally car spot information from CN, CP and the grain companies has been added where this has been published. This dataset attempts to provide a temporal and geographical extent of the grain elevators in Canada. For more information, visit: www.agr.gc.ca/atlas/metadata/5e0b5778-80cd-4697-8b84-23b4a814c1ae

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 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 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

This data shows spatial density of pulses cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which pulese 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 pulses based on analysis of the 2009 to 2015 AAFC annual crop inventory data. For more information, visit: http://open.canada.ca/data/en/dataset/f6d91e82-c783-4a63-8235-7bf53b16b706

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

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