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    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

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    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: http://open.canada.ca/data/en/dataset/05870f11-a52a-4bf4-bc15-910fd0b8a1a3

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    The Census of Agriculture is disseminated by Statistics Canada's standard geographic units (boundaries). Since these census units do not reflect or correspond with biophysical landscape units (such as ecological regions, soil landscapes or drainage areas), Agriculture and Agri-Food Canada, in collaboration with Statistics Canada's Agriculture Division, have developed a process for interpolating (reallocating or proportioning) Census of Agriculture information from census polygon-based units to biophysical polygon-based units. In the "Interpolated census of agriculture", suppression confidentiality procedures were applied by Statistics Canada to the custom tabulations to prevent the possibility of associating statistical data with any specific identifiable agricultural operation or individual. Confidentiality flags are denoted where "-1" appears in data cell. This indicates information has been suppressed by Statistics Canada to protect confidentiality. Null values/cells simply indicate no data is reported. For more information, visit: http://open.canada.ca/data/en/dataset/1dee8513-5c73-43b6-9446-25f7b985cd00

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    This data is part of a nested hierarchy of natural areas. Digital coverages of ecozones, ecoregions and ecodistricts were compiled on the standard 1:1 million scale map bases of the Soil Landscapes of Canada database. Une version en français est disponible à http://nlwis-snite1.agr.gc.ca/cgi-bin/ogc/eco_wms_f?service=wms&request=getcapabilities

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    This series highlights the locations of research centres research farms where scientists, technicians and staff work to create better opportunities for farmers and all Canadians through agricultural research and innovation.

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    The 1990 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 1990 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/02202cec-b4a1-4a1d-9997-edcbaca92d41

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    In 2012, 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 (except Newfoundland), in support of a national crop inventory. A Decision Tree (DT) based methodology was applied using optical (DMC, SPOT) 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/621bb298-116f-4931-8350-741855b007bc

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    The "Prairie Agricultural Landscapes (PAL)" datasets identify areas of the agricultural portions of the Canadian Prairies with similar land and water resources, land use and farming practices. They are represented by vector polygons. Based on selected attributes from the Soil Landscapes of Canada (SLC) and the 1996 Census of Agriculture, the Prairies were classified into 13 (thirteen) classes of Land Practices Group and five (5) Major Land Practices Groups. Typical attributes used to define the Land Practice Groups include: land in pasture, land in summerfallow, crop mixture, farm size and the level of chemical and fertilizer inputs. The five (5) Major Groups were devised to help better understand the relationships between the groups. For more information, visit: https://open.canada.ca/data/en/dataset/0b2303be-ef05-49a8-8082-44a3eabcfa57

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    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

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    The “Cereals and Pulses Science Sector by CCS” data was derived from the 2011 Census of Agriculture using published and draft 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 “STB – AAFC Cereals and Pulses Strategy” (Version 21) document produced on February 25th, 2014 and states;“The cereal and pulse crops that fall within the scope of the STB’s programming and hence this sector science strategy are as follows: Cereals; Wheat (all classes), Barley (malt and feed), oats, rye, triticale, corn for grain Pulses; dry beans (white and coloured), dry peas ( green, yellow and other), lentils, chickpeas”. For more information, visit: www.agr.gc.ca/atlas/metadata/5a8973f8-1d7c-4ead-a1a6-2883b7b9a8b6