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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer with a ground resolution of 56 meters. The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Some Cropland Data Layer states used Landsat 5 TM and/or Landsat 7 ETM+ satellite imagery to supplement the classification. Ancillary classification inputs include: the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer...
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This tabular data set represents the percent of land cover classes from the 2014 Crop land Data Layer compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "2014 Crop Land Data Layer" produced by the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS, 2015). Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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This tabular data set represents the percent of land cover classes from the 2013 Crop land Data Layer compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "2014 Crop Land Data Layer" produced by the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS, 2015). Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes...
The Great Plains Landscape Conservation Cooperative (GPLCC, http://www.greatplainslcc.org/) is a partnership that provides applied science and decision support tools to assist natural resource managers conserve plants, fish and wildlife in the mid- and short-grass prairie of the southern Great Plains. It is part of a national network of public-private partnerships — known as Landscape Conservation Cooperatives (LCCs, http://www.fws.gov/science/shc/lcc.html) — that work collaboratively across jurisdictions and political boundaries to leverage resources and share science capacity. The Great Plains LCC identifies science priorities for the region and helps foster science that addresses these priorities to support wildlife...
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This tabular data set represents the percent of land cover classes from the 2012 Crop land Data Layer compiled for two spatial components of the NHDPlus version 2 data suite (NHDPlusv2) for the conterminous United States; 1) individual reach catchments and 2) reach catchments accumulated upstream through the river network. This dataset can be linked to the NHDPlus version 2 data suite by the unique identifier COMID. The source data is the "2012 Crop Land Data Layer" produced by the United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS, 2015). Reach catchment information characterizes data at the local scale. Reach catchments accumulated upstream through the river network characterizes...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...
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Crop cover maps have become widely used in a range of research applications. Multiple crop cover maps have been developed to suite particular research interests. The National Agricultural Statistics Service (NASS) Cropland Data Layers (CDL) are a series of commonly used crop cover maps for the conterminous United States (CONUS) that span from 2008-2013. In this investigation we wanted to expand the temporal coverage of the NASS CDL archive back to 2000 by creating yearly NASS CDL-like crop cover maps derived from a classification tree model algorithm. We used over 11 million crop sample records to train a classification tree algorithm and to develop a crop classification model (CCM). The model was used to create...


map background search result map search result map USDA, National Agricultural Statistics Service, 2009 Cropland Data Layer Wyoming 2010 Cropland Data Layer for the Great Plains Landscape Conservation Cooperative Attributes for NHDPlus Version 2.1 Catchments and Modified Routing of Upstream Watersheds for the Conterminous United States: Crop Land Data Layer 2012 Attributes for NHDPlus Version 2.1 Catchments and Modified Routing of Upstream Watersheds for the Conterminous United States: Crop Land Data Layer 2013 Attributes for NHDPlus Version 2.1 Reach Catchments and Modified Routed Upstream Watersheds for the Conterminous United States: Crop Land Data Layer 2014 Modeled conterminous United States Crop Cover datasets for 2000 - 2013 Modeled conterminous United States Crop Cover datasets for 2000 Modeled conterminous United States Crop Cover datasets for 2001 Modeled conterminous United States Crop Cover datasets for 2002 Modeled conterminous United States Crop Cover datasets for 2003 Modeled conterminous United States Crop Cover datasets for 2004 Modeled conterminous United States Crop Cover datasets for 2005 Modeled conterminous United States Crop Cover datasets for 2006 Modeled conterminous United States Crop Cover datasets for 2007 Modeled conterminous United States Crop Cover datasets for 2008 Modeled conterminous United States Crop Cover datasets for 2009 Modeled conterminous United States Crop Cover datasets for 2010 Modeled conterminous United States Crop Cover datasets for 2011 Modeled conterminous United States Crop Cover datasets for 2012 Modeled conterminous United States Crop Cover datasets for 2013 USDA, National Agricultural Statistics Service, 2009 Cropland Data Layer Wyoming 2010 Cropland Data Layer for the Great Plains Landscape Conservation Cooperative Attributes for NHDPlus Version 2.1 Catchments and Modified Routing of Upstream Watersheds for the Conterminous United States: Crop Land Data Layer 2012 Attributes for NHDPlus Version 2.1 Catchments and Modified Routing of Upstream Watersheds for the Conterminous United States: Crop Land Data Layer 2013 Attributes for NHDPlus Version 2.1 Reach Catchments and Modified Routed Upstream Watersheds for the Conterminous United States: Crop Land Data Layer 2014 Modeled conterminous United States Crop Cover datasets for 2000 - 2013 Modeled conterminous United States Crop Cover datasets for 2000 Modeled conterminous United States Crop Cover datasets for 2001 Modeled conterminous United States Crop Cover datasets for 2002 Modeled conterminous United States Crop Cover datasets for 2003 Modeled conterminous United States Crop Cover datasets for 2004 Modeled conterminous United States Crop Cover datasets for 2005 Modeled conterminous United States Crop Cover datasets for 2006 Modeled conterminous United States Crop Cover datasets for 2007 Modeled conterminous United States Crop Cover datasets for 2008 Modeled conterminous United States Crop Cover datasets for 2009 Modeled conterminous United States Crop Cover datasets for 2010 Modeled conterminous United States Crop Cover datasets for 2011 Modeled conterminous United States Crop Cover datasets for 2012 Modeled conterminous United States Crop Cover datasets for 2013