From 1 - 10 / 127
  • Categories  

    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

  • Categories  

    The Agriculture and Agri-Food Canada's (AAFC) Watersheds Project level series supplies a number of watershed and watershed related datasets for the Prairie Provinces. The levels are greater or smaller assemblages of hydrometric areas, or the components defining them. The Project is organized by the hydrometric gauging station which are sourced from Environment Canada, the United States and Canadian provinces. Additional stations were generated to address structural issues, like river confluences or lake inlets. Collectively, they are referred to as the gauging stations, or simply, the stations. The drainage area that each station monitors, between itself and one or more of its upstream neighbours, is called an 'incremental gross drainage area'. The incremental gross drainage areas are collected into larger or smaller groupings based on size or defined interest to generate the various 'levels'of the series. For more information, visit: http://open.canada.ca/data/en/dataset/c20d97e7-60d8-4df8-8611-4d499a796493

  • Categories  

    These agricultural capability / Limitation maps can be used at the regional level for making decisions on land improvement and farm consolidation, for developing landuse plans, and for preparing equitable land assessments. For more information, visit: http://open.canada.ca/data/en/dataset/0c113e2c-e20e-4b64-be6f-496b1be834ee

  • Categories  

    The 'Circa 1995 Landcover of the Prairies' dataset is a geospatial raster data layer portraying the rudimentary land cover types of all grain-growing areas of Manitoba, Saskatchewan, Alberta and northeastern British Columbia at a 30-metre resolution for the 1995 timeframe. It is the collection of all the classified imagery (1993 to 1995) of the Western Grain Transition Payment Program (WGTPP) assembled into a single seamless raster data layer. For more information, visit: http://open.canada.ca/data/en/dataset/e9dee957-e04d-46fb-b7e4-701739736173

  • Categories  

    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

  • Categories  

    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.

  • Categories  

    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

  • Categories  

    These datasets show the areas where major crops can be expected within the agricultural regions of Canada. Results are provided as rasters with numerical values for each pixel indicating the level of spatial density calculated for a specific crop type in that location. Regions with higher spatial density for a certain crop have higher likelihood to have the same crop based on the previous years mapped crop inventories. For more information, visit: http://open.canada.ca/data/en/dataset/fdf82539-5a74-440b-86ef-a16b7801c706

  • Categories  

    This data shows spatial density of Barley cultivation in Canada. Regions with higher calculated spatial densities represent agricultural regions of Canada in which Barley 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 Barley based on analysis of the 2009 to 2015 AAFC annual crop inventory data.For more information, visit: http://open.canada.ca/data/en/dataset/08ba1d1c-4985-46d4-be2d-495005689db2

  • Categories  

    Census of Agriculture 2011 by Consolidated Census Subdivision, including business, crop, farm, land use, livestock, and operator information.