10,000+ results returned
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Title: Cropland Data Layer, New York, 2020
Contributors:- Raster data
- 2021
Summary: The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2020 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, the Disaster Monitoring Constellation (DMC) DEIMOS-1, the ISRO ResourceSat-2 LISS-3, and the ESA SENTINEL-2 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) and the imperviousness and canopy data layers from the USGS National Land Cover Database 2016 (NLCD 2016). Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The most current version of the NLCD 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. The purpose of the Cropland Data Layer Program is to use satellite imagery to (1) provide planted acreage estimates to the Agricultural Statistics Board for the state's major commodities and (2) produce digital, crop-specific, categorized geo-referenced output products.
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Title: Soil Survey, Tompkins County NY, 1965
Contributors:- Polygon data
- 1965
Summary: Various county departments, local municipal agencies, and other not-for-profit organizations have identified the need for a digital soil coverage data set for Tompkins County, NY. The Tompkins County ITS GIS Division initiated and developed a digital soil coverage from the official analog soil map series produced and published by the United States Geology Survey (USGS) and Cornell University Agricultural Experiment Station. The field survey has been conducted during the 60es. To provide a GIS countywide coverage that consists of polygons defining the soils boundaries and to add enough basic attributes to achieve a fundamental degree of categorization. Open, all-purpose data set.
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Title: Outline map of the United States
Contributors:- Not specified
- 1920
Summary: Shows boundaries of states and counties. on sheets 59 x 91 centimeters
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Title: Outline map of the United States
Contributors:- Not specified
- 1860
Summary: County names and boundaries printed in turquoise.; "June 1, 1860." 54 x 84 centimeters
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Title: Cropland Data Layer, New York State, 2002
Contributors:- Raster data
- 2006
Summary: The USDA-NASS 2002 New York Cropland Data Layer (CDL) is a raster, geo-referenced, categorized land cover data layer produced using satellite imagery from the Thematic Mapper (TM) instrument on Landsat 5 and the Enhanced Thematic Mapper (ETM+) on Landsat 7. The imagery was collected between May 4, 2002 and September 12, 2002. The approximate scale is 1:100,000 with a ground resolution of 30 meters by 30 meters. The CDL emphasis is on agricultural land cover. The area of coverage is the entire State of New York. This land cover dataset is part of a one-time series in which ten Mid-Atlantic States were categorized based on the extensive field observations collected during the 2002 annual NASS June Agricultural Survey. No farmer reported data is included or derivable from the Cropland Data Layer. The area of coverage for the 2002 Mid-Atlantic CDL includes the entire states of Connecticut, Delaware, Maryland, New Jersey, New York, North Carolina, Pennsylvania, Rhode Island, Virginia and West Virginia. The funding for this project was shared between the USDA-NASS and Towson State University. The 2002 Mid-Atlantic CDL is currently a special one-time project. However, the possibility does exist to establish an annual cropland data layer for any state that shows significant interest and can offer an in-state cooperative agreement with another federal, state, local, or university agency or group. If interested, please contact the Section Head of the USDA-NASS Spatial Analysis Research Section at 703/877-8000. There are several additional Mid-Western States for which Cropland Data Layers are produced on an annual basis. The website below provides information and examples of all publicly available Cropland Data Layers: http://www.nass.usda.gov/research/Cropland/SARS1a.htm The purpose of the Cropland Data Layer Program is to use satellite imagery to (1) provide supplemental acreage estimates for the state's major commodities and (2) produce digital, crop specific, categorized geo-referenced output products. These data are intended for geographic display and analysis at the state level. The cropland data layers are provided "as is". USDA-NASS does not warrant results you may obtain using the data.
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Title: NAIP Aerial Mosaics (UTM), WI 2024
Contributors:- Raster data
- 2024
Summary: 2024 NAIP imagery for Wisconsin has a 0.6-meter (60cm) spatial resolution. County mosaics are stored in MrSID format as four-band images (Red, Green, Blue, Near Infrared) [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP acquires digital ortho imagery during the agricultural growing seasons in the continental U.S. A primary goal of the NAIP program is to enable availability of ortho imagery within one year of acquisition. The NAIP provides 60 centimeter ground sample distance (GSD) ortho imagery rectified to a horizontal accuracy within +/- 4 meters of reference digital ortho quarter quads (DOQQ's) from the National Digital Ortho Program (NDOP) or from the National Agriculture Imagery Program (NAIP). The tiling format of NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. The NAIP imagery is formatted to the UTM coordinate system using the North American Datum of 1983 (NAD83). The NAIP imagery may contain as much as 10% cloud cover per tile. This file was generated by compressing NAIP imagery that cover the county extent. Two types of compression may be used for NAIP imagery: MrSID and JPEG 2000. The target value for the compression ratio is 40:1 for imagery.]
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Title: Cropland Data Layer: Wisconsin 2023
Contributors:- Raster data
- 2023
Summary: The USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer produced using satellite imagery and extensive agricultural ground reference data. The program began in 1997 with limited coverage and in 2008 forward expanded coverage to the entire Continental United States. Please note that no farmer reported data are derivable from the Cropland Data Layer. The 2008 to current CDLs have a spatial resolution of 30 meters and were produced using moderate spatial resolution satellite imagery. The current program uses Landsat 8 and 9 OLI/TIRS and ESA SENTINEL-2A and -2B collected throughout the growing season. Past years of CDL have used other satellite-based sensors such as Landsat 5 and 7, ISRO ResourceSat-2 LISS-3, IRS AWiFS, Diemos-1 and UK-DMC-2, and MODIS 16-Day NDVI Composite. Some CDL states used additional ancillary inputs to supplement and improve the land cover classification including historical CDL data, the United States Geological Survey (USGS) National Elevation Dataset (NED), USDA National Resources Conservation Service (NRCS) National Commodity Crop Productivity Index (NCCPI), and the most current versions of the USGS National Land Cover Database imperviousness and the tree canopy data layers. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. Some CDL states incorporate additional crop-specific ground reference obtained from the following non-FSA sources which are detailed in the 'Lineage' Section of this metadata: US Bureau of Reclamation, NASS Citrus Data Layer (internal use only), California Department of Water Resources, Florida Department of Agriculture and Consumer Services Office of Agricultural Water Policy, Cornell University grape/vineyard data, Oregon State University tree crop and vineyard data, Utah Department of Water Resources, and Washington State Department of Agriculture. The most current version of the NLCD is used as non-agricultural training and validation data.
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Title: Cropland Data Layer: Wisconsin 2022
Contributors:- Raster data
- 2022
Summary: The USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer produced using satellite imagery and extensive agricultural ground reference data. The program began in 1997 with limited coverage and in 2008 forward expanded coverage to the entire Continental United States. Please note that no farmer reported data are derivable from the Cropland Data Layer. The 2008 to current CDLs have a spatial resolution of 30 meters and were produced using moderate spatial resolution satellite imagery. The current program uses Landsat 8 and 9 OLI/TIRS and ESA SENTINEL-2A and -2B collected throughout the growing season. Past years of CDL have used other satellite-based sensors such as Landsat 5 and 7, ISRO ResourceSat-2 LISS-3, IRS AWiFS, Diemos-1 and UK-DMC-2, and MODIS 16-Day NDVI Composite. Some CDL states used additional ancillary inputs to supplement and improve the land cover classification including historical CDL data, the United States Geological Survey (USGS) National Elevation Dataset (NED), USDA National Resources Conservation Service (NRCS) National Commodity Crop Productivity Index (NCCPI), and the most current versions of the USGS National Land Cover Database imperviousness and the tree canopy data layers. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. Some CDL states incorporate additional crop-specific ground reference obtained from the following non-FSA sources which are detailed in the 'Lineage' Section of this metadata: US Bureau of Reclamation, NASS Citrus Data Layer (internal use only), California Department of Water Resources, Florida Department of Agriculture and Consumer Services Office of Agricultural Water Policy, Cornell University grape/vineyard data, Oregon State University tree crop and vineyard data, Utah Department of Water Resources, and Washington State Department of Agriculture. The most current version of the NLCD is used as non-agricultural training and validation data.
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Title: NAIP Natural Color Aerial Mosaics (UTM), WI 2022
Contributors:- Raster data
- 2022
Summary: 2022 NAIP imagery for Wisconsin has a .6-meter (60cm) spatial resolution. [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are originally formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.]
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Title: NAIP Color Infrared Aerial Mosaics (UTM), WI 2022
Contributors:- Raster data
- 2022
Summary: 2022 NAIP imagery for Wisconsin has a .6-meter (60cm) spatial resolution. [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are originally formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.]
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Title: NAIP Aerial Imagery DOQQs (UTM), WI 2022
Contributors:- Raster data
- 2022
Summary: 2022 NAIP imagery for Wisconsin has a .6-meter (60cm) spatial resolution. [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are originally formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.]
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Title: Cropland Data Layer: Wisconsin 2021
Contributors:- Raster data
- 2021
Summary: The USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer produced using satellite imagery and extensive agricultural ground reference data. The program began in 1997 with limited coverage and in 2008 forward expanded coverage to the entire Continental United States. Please note that no farmer reported data are derivable from the Cropland Data Layer. The 2008 to current CDLs have a spatial resolution of 30 meters and were produced using moderate spatial resolution satellite imagery. The current program uses Landsat 8 and 9 OLI/TIRS and ESA SENTINEL-2A and -2B collected throughout the growing season. Past years of CDL have used other satellite-based sensors such as Landsat 5 and 7, ISRO ResourceSat-2 LISS-3, IRS AWiFS, Diemos-1 and UK-DMC-2, and MODIS 16-Day NDVI Composite. Some CDL states used additional ancillary inputs to supplement and improve the land cover classification including historical CDL data, the United States Geological Survey (USGS) National Elevation Dataset (NED), USDA National Resources Conservation Service (NRCS) National Commodity Crop Productivity Index (NCCPI), and the most current versions of the USGS National Land Cover Database imperviousness and the tree canopy data layers. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. Some CDL states incorporate additional crop-specific ground reference obtained from the following non-FSA sources which are detailed in the 'Lineage' Section of this metadata: US Bureau of Reclamation, NASS Citrus Data Layer (internal use only), California Department of Water Resources, Florida Department of Agriculture and Consumer Services Office of Agricultural Water Policy, Cornell University grape/vineyard data, Oregon State University tree crop and vineyard data, Utah Department of Water Resources, and Washington State Department of Agriculture. The most current version of the NLCD is used as non-agricultural training and validation data.
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Title: NAIP Imagery DOQQ Tile Index, Wisconsin 2020
Contributors:- Polygon data
- 2020
Summary: This data represents the tile index for the National Agricultural Imagery Program (NAIP) digital ortho quarter quad (DOAA) tiles in Wisconsin for 2020. The tile index is designed to help determine appropriate images covering a specific area of interest.
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Title: Cropland Data Layer: Wisconsin 2020
Contributors:- Raster data
- 2020
Summary: The USDA-NASS Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer. The CDL Program began with one state in 1997 and expanded to cover the entire Continental United States in 2008.The CDL has a ground resolution of 30 or 56 meters depending on the state and year. For metadata files with detailed product and technical information or to download a national seamless Cropland Data Layer (.img raster in Albers Conical Equal Area projection), please visit: https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php or the CropScape web portal at https://nassgeodata.gmu.edu/CropScape The data layer is aggregated to a possible 85 standardized categories for display purposes, with the emphasis being agricultural land cover. Most data layers average about 10 to 20 categories out of the 85 possible categories.The purpose of the Cropland Data Layer Program is to use satellite imagery on an annual basis to (1) provide supplemental acreage estimates for the state's major commodities and (2) produce digital, crop specific, categorized geo-referenced output products.This program represents a cooperative venture between three USDA Agencies (headquarters units of NASS, the Foreign Agriculture Service, and the Farm Service Agency) plus in-state agreements among the Agricultural Statistics Service, the Department of Natural Resources and the Department of Agriculture.Maps are included for all available years when the product is ordered. However, previewing the metadata or image in step two will only show the most recent year. All states do not have all years in the maps delivered from the Gateway. Use 'Status Maps' to see a map with labels of the years that are available.
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Title: NAIP Natural Color Aerial Mosaics (UTM), WI 2020
Contributors:- Raster data
- 2020
Summary: 2020 NAIP imagery for Wisconsin has a .6-meter (60cm) spatial resolution. There are DOQQ tiles (GeoTIFF format) as well as county mosaics (MrSID format) available. [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are originally formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.]
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Title: NAIP Color Infrared Aerial Mosaics (UTM), WI 2020
Contributors:- Raster data
- 2020
Summary: 2020 NAIP imagery for Wisconsin has a .6-meter (60cm) spatial resolution. There are DOQQ tiles (GeoTIFF format) as well as county mosaics (MrSID format) available. [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are originally formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.]
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Title: NAIP Natural Color Aerial Mosaics (WTM), WI 2020
Contributors:- Raster data
- 2020
Summary: 2020 NAIP imagery for Wisconsin has a .6-meter (60cm) spatial resolution. There are DOQQ tiles (GeoTIFF format) as well as county mosaics (MrSID format) available. [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are originally formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.]
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Title: NAIP Aerial Imagery DOQQs (UTM), WI 2020
Contributors:- Raster data
- 2020
Summary: 2020 NAIP imagery for Wisconsin has a .6-meter (60cm) spatial resolution. There are DOQQ tiles (GeoTIFF format) as well as county mosaics (MrSID format) available. [From USDA: This data set contains imagery from the National Agriculture Imagery Program (NAIP). The NAIP program is administered by USDA FSA and has been established to support two main FSA strategic goals centered on agricultural production. These are, increase stewardship of America's natural resources while enhancing the environment, and to ensure commodities are procured and distributed effectively and efficiently to increase food security. The NAIP program supports these goals by acquiring and providing ortho imagery that has been collected during the agricultural growing season in the U.S. The NAIP ortho imagery is tailored to meet FSA requirements and is a fundamental tool used to support FSA farm and conservation programs. Ortho imagery provides an effective, intuitive means of communication about farm program administration between FSA and stakeholders. New technology and innovation is identified by fostering and maintaining a relationship with vendors and government partners, and by keeping pace with the broader geospatial community. As a result of these efforts the NAIP program provides three main products: DOQQ tiles, Compressed County Mosaics (CCM), and Seamline shape files. The Contract specifications for NAIP imagery have changed over time reflecting agency requirements and improving technologies. These changes include image resolution, horizontal accuracy, coverage area, and number of bands. In general, flying seasons are established by FSA and are targeted for peak crop growing conditions. The NAIP acquisition cycle is based on a minimum 3 year refresh of base ortho imagery. The tiling format of the NAIP imagery is based on a 3.75' x 3.75' quarter quadrangle with a 300 pixel buffer on all four sides. NAIP quarter quads are originally formatted to the UTM coordinate system using the North American Datum of 1983. NAIP imagery may contain as much as 10% cloud cover per tile.]
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Title: Cropland Data Layer: Wisconsin, 2019
Contributors:- Raster data
- 2019
Summary: The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2019 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 8 OLI/TIRS sensor, the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2, the ISRO ResourceSat-2 LISS-3, and the ESA SENTINEL-2 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) and the imperviousness data layer from the USGS National Land Cover Database 2016 (NLCD 2016) and the tree canopy data layer from the NLCD 2011.Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The most current version of the NLCD 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.
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Title: Cropland Data Layer: Wisconsin, 2018
Contributors:- Raster data
- 2018
Summary: The USDA National Agricultural Statistics Service (NASS) releases the annual Cropland Data Layer (CDL) via the NASS CropScape geospatial portal. The CDL product depicts agricultural land cover over the Continental United States at 30 meters resolution. CropScape includes historical data dating back to 1997 for some locales. The CDL is an annual raster, geo-referenced, crop-specific land cover data layer produced using satellite imagery and extensive agricultural ground truth collected during the current growing season. The strength and emphasis of CropScape and the CDL is agricultural land cover. Please note that no farmer reported data are derivable from CropScape or the Cropland Data Layer.Please reference CropScape (https://nassgeodata.gmu.edu/CropScape/) or the official CDL website (https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php) for a list of the available states and years of data and the individual metadata files that contain the technical details. NASS developed both the CropScape and VegScape web services in cooperation with the Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA.