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 "description": "The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2012 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, and the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors collected during the current growing season.Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites.Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data.Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL.The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.Any cell with one of the following classes, was considered non-agriculture. All other land cover types are considered agriculture.Class\tDescription111\t\tOpen Water112\t\tPerennial Ice/Snow121\t\tDeveloped/Open Space122\t\tDeveloped/Low Intensity123\t\tDeveloped/Med Intensity124\t\tDeveloped/High Intensity131\t\tBarren141\t\tDeciduous Forest142\t\tEvergreen Forest143\t\tMixed Forest152\t\tShrubland171\t\tGrassland Herbaceous190\t\tWoody Wetlands195\t\tHerbaceous WetlandsProcessing Steps1. Project From Albers Equal Area Conic to Pacific Northwest Albers maintaining original 30m cell size2. Resample from 30m cell size to 32m cell size using nearest method. This places cells into the Nested Grid structure.3. Reclassify the raster values to 1 for agriculture land cover types and 0 for all other land cover types.4. Use the Neighborhood > Block Statistics tool to count the number of 32m agriculture cells in each 256m cell, using base raster for extent and snap raster.5. Resample from the 32m cell size to the 256m cell size using the nearest method. Each 256m cell now has as its value the number of internal 32m cells that are agriculture.6. Divide each cell value by 64 to get the percent of each cell that is agriculture. Round each percent to the nearest integer.",
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 "copyrightText": "University of Washington School of Environemental and Forest Sciences, Natural Resource Spatial Informatics Group; USDA National Agricultural Statistics Service Cropland Data Layer. 2012. Published crop-specific data layer [Online]. Available at http://nassgeodata.gmu.edu/CropScape/ (accessed Feb. 27, 2013;). USDA-NASS, Washington, DC.",
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