Agriculture and Agri-Food Canada
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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
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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
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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.
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The 2000 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 2000 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/b5f413d9-9acc-4ad7-b9a7-38486ed5fee7
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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
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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 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
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The Agri-Environmental Indicator (AEI) dataset series provides information that was created using indicators that assess the environmental impact of agricultural activities. These agri-environmental indicators integrate information on soils, climate and land surface features with statistics on land use and crop and livestock management practices. The datasets provide valuable, location-specific information on the overall environmental risks and conditions in agriculture across Canada and how these change over time. This dataset series collects AEI data that is related to geographic features and can be represented on a map. Other types of AEI data are not included. The datasets can be organized into the following major groups: farm land management, soil health, water quality, air quality, and food and beverage industry (not included). Farm land management datasets: soil cover, wildlife habitat, and farm land management (not included). Soil health datasets: soil erosion, soil organic matter, trace elements, and soil salinity. Water quality datasets: nitrogen, phosphorus, coliforms, and pesticides. Air quality datasets: greenhouse gases, ammonia, particulate matter. For more information, visit: http://open.canada.ca/data/en/dataset/e996d9be-6a3b-4059-9afc-17dc68385f05
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In 2009 the Earth Observation Team of the Science and Technology Branch (STB) at Agriculture and Agri-Food Canada (AAFC) began 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) 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/ce7873ff-fbc0-4864-946e-6a1b4d739154
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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
Arctic SDI catalogue