Agriculture and Agri-Food Canada
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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
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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
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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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This data series represents the volumetric soil moisture (percent saturated soil) for the surface layer (<5 cm). The data is created daily and is averaged for the ISO standard week and month. The datais produced from passive microwave satellite data collected by the Soil Moisture and Ocean Salinity (SMOS) satellite and converted to soil moisture using version 5.51 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/a0533280-2bf6-40ba-a126-bc7ed2336017
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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 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 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
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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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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
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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
Arctic SDI catalogue