Cropland Data Layer, New York, 2010

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Identification_Information

Citation:
Citation_Information:
Originator: United States Department of Agriculture (USDA), National Agricultural Statistics Service (NASS), Research and Development Division (RDD), Geospatial Information Branch (GIB), Spatial Analysis Research Section (SARS)
Publication_Date: 20110110
Title: Cropland Data Layer, New York, 2010
Edition: 2010 Edition
Geospatial_Data_Presentation_Form: raster digital data
Series_Information:
Series_Name: USDA-NASS Cropland Data Layer
Issue_Identification: New York 2010
Publication_Information:
Publication_Place: USDA, NASS Marketing and Information Services Office, Washington, D.C.
Publisher: USDA, NASS
Other_Citation_Details: Available on DVD through the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The most current year of data is available free for download for a limited time at the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The data is also available free for download through the CropScape - Cropland Data Layer website at <http://nassgeodata.gmu.edu/CropScape/>. The data is also available free for download through the Geospatial Data Gateway at <http://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed Geospatial Data Gateway download instructions. The official DVD contains additional accuracy assessment information that is not available through the Geospatial Data Gateway in the form of an associated confidence layer. The following description of the confidence layer is taken from the document entitled 'MDA_NLCD_User_Guide.doc' which is available free for download with the NLCD Mapping Tool at <http://www.mrlc.gov/>. The Confidence Layer "spatially represents the predicted confidence that is associated with that output pixel, based upon the rule(s) that were used to classify it. This is useful in that the user can see the spatial representation of distribution and magnitude of error or confidence for a given classification... This error layer represents a percent confidence associated with each rule and output categorical, classified value. It is expressed as a percentage of confidence. A value of zero would therefore have a low confidence (always wrong), while a value of 100 would have a very high confidence (always right)." For more information on the use of confidence layers please refer to the following paper: Liu, Weiguo, Sucharita Gopal and Curtis E. Woodcock, 2004. Uncertainty and confidence in land cover classification using a hybrid classifier approach, Photogrammetric Engineering & Remote Sensing, 70(8):963-971. Ultimately, however, the confidence value is not a measure of accuracy for a given pixel but rather a how well it fit within the decision tree ruleset.
Online_Linkage: https://cugir.library.cornell.edu/catalog/cugir-008033
Online_Linkage: http://nassgeodata.gmu.edu/CropScape/
Description:
Abstract: The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The 2010 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 Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) 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 USGS National Land Cover Dataset 2001 (NLCD 2001), 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 2001 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.
Purpose: The purpose of the Cropland Data Layer Program is to use satellite imagery to (1) provide acreage estimates to the Agricultural Statistics Board for the state's major commodities and (2) produce digital, crop-specific, categorized geo-referenced output products.
Supplemental_Information: If the following table does not display properly, then please visit the following website to view the original metadata file <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm>. USDA, National Agricultural Statistics Service 2010 New York Cropland Data Layer CLASSIFICATION INPUTS: AWIFS DATE 20100618 PATH 284 ROW(S)&QUADRANT(S) 40ABCD 45CD 50AB AWIFS DATE 20100703 PATH 287 ROW(S)&QUADRANT(S) 40BD 41C 45BD 46AC AWIFS DATE 20100704 PATH 292 ROW(S)&QUADRANT(S) 40B 41AC 46A AWIFS DATE 20100820 PATH 287 ROW(S)&QUADRANT(S) 40BD 45B AWIFS DATE 20100829 PATH 284 ROW(S)&QUADRANT(S) 40BD LANDSAT 5 TM DATE 20100413 PATH 015 ROW(S) 29-31 34-37 41-43 LANDSAT 5 TM DATE 20100415 PATH 013 ROW(S) 27-32 LANDSAT 5 TM DATE 20100420 PATH 016 ROW(S) 29-42 LANDSAT 5 TM DATE 20100429 PATH 015 ROW(S) 29-37 41 LANDSAT 5 TM DATE 20100531 PATH 015 ROW(S) 29-37 41-43 LANDSAT 5 TM DATE 20100602 PATH 013 ROW(S) 29-32 LANDSAT 5 TM DATE 20100625 PATH 014 ROW(S) 29-36 LANDSAT 5 TM DATE 20100702 PATH 015 ROW(S) 29-35 37 41-42 LANDSAT 5 TM DATE 20100704 PATH 013 ROW(S) 27-32 LANDSAT 5 TM DATE 20100727 PATH 014 ROW(S) 29-34 36 LANDSAT 5 TM DATE 20100801 PATH 017 ROW(S) 30-32 38-41 LANDSAT 5 TM DATE 20100819 PATH 015 ROW(S) 29-33 36-37 41-43 LANDSAT 5 TM DATE 20100828 PATH 014 ROW(S) 29-36 LANDSAT 5 TM DATE 20100902 PATH 017 ROW(S) 30-41 LANDSAT 5 TM DATE 20100906 PATH 013 ROW(S) 27-32 LANDSAT 7 ETM DATE 20100414 PATH 014 ROW(S) 29-34 LANDSAT 7 ETM DATE 20100419 PATH 017 ROW(S) 30-41 LANDSAT 7 ETM DATE 20100521 PATH 017 ROW(S) 30-33 35-41 LANDSAT 7 ETM DATE 20100530 PATH 016 ROW(S) 29-43 LANDSAT 7 ETM DATE 20100615 PATH 016 ROW(S) 29-31 34-43 LANDSAT 7 ETM DATE 20100703 PATH 014 ROW(S) 29-36 LANDSAT 7 ETM DATE 20100708 PATH 017 ROW(S) 30-41 LANDSAT 7 ETM DATE 20100802 PATH 016 ROW(S) 30-31 34-35 38-41 43 LANDSAT 7 ETM DATE 20100820 PATH 014 ROW(S) 29-36 LANDSAT 7 ETM DATE 20100903 PATH 016 ROW(S) 29-43 USGS, NATIONAL ELEVATION DATASET ELEVATION USGS, NATIONAL LAND COVER DATASET 2001 TREE CANOPY USGS, NATIONAL LAND COVER DATASET 2001 IMPERVIOUSNESS TRAINING AND VALIDATION: USDA, FARM SERVICE AGENCY 2010 COMMON LAND UNIT DATA USGS, NATIONAL LAND COVER DATASET 2001 NOTE: The final extent of the CDL is clipped to the state boundary even though the raw input data may encompass a larger area.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20090925
Ending_Date: 20101230
Currentness_Reference: 2010 growing season
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -79.974336
East_Bounding_Coordinate: -70.596893
North_Bounding_Coordinate: 45.838882
South_Bounding_Coordinate: 40.116635
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: farming
Theme_Keyword: environment
Theme_Keyword: imageryBaseMapsEarthCover
Theme:
Theme_Keyword_Thesaurus: Global Change Master Directory (GCMD) Science Keywords
Theme_Keyword: Earth Science > Biosphere > Terrestrial Ecosystems > Agricultural Lands
Theme_Keyword: Earth Science > Land Surface > Land Use/Land Cover > Land Cover
Theme:
Theme_Keyword_Thesaurus: Global Change Master Directory (GCMD) Instrument Keywords
Theme_Keyword: MODIS > Moderate-Resolution Imaging Spectroradiometer
Theme_Keyword: MODIS > Moderate-Resolution Imaging Spectroradiometer
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: crop cover
Theme_Keyword: cropland
Theme_Keyword: agriculture
Theme_Keyword: land cover
Theme_Keyword: crop estimates
Theme_Keyword: AWiFS
Theme_Keyword: MODIS
Theme_Keyword: Landsat
Theme_Keyword: Cropscape
Theme:
Theme_Keyword_Thesaurus: CUGIR Category
Theme_Keyword: agriculture
Theme_Keyword: environment
Theme_Keyword: landcover
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: New York
Temporal:
Temporal_Keyword_Thesaurus: None
Temporal_Keyword: 2010
Access_Constraints: None
Use_Constraints: The USDA, NASS Cropland Data Layer is provided to the public as is and is considered public domain and free to redistribute. The USDA, NASS does not warrant any conclusions drawn from these data. If the user does not have software capable of viewing GEOTIF (.tif) file formats then we suggest using the Cropscape website <http://nassgeodata.gmu.edu/CropScape/> or the freeware browser ESRI ArcGIS Explorer <http://www.esri.com/>.
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA, NASS, Spatial Analysis Research Section
Contact_Person: USDA, NASS, Spatial Analysis Research Section staff
Contact_Address:
Address_Type: mailing and physical address
Address: 3251 Old Lee Highway, Room 305
City: Fairfax
State_or_Province: Virginia
Postal_Code: 22030-1504
Country: USA
Contact_Voice_Telephone: 703-877-8000
Contact_Facsimile_Telephone: 703-877-8044
Contact_Electronic_Mail_Address: HQ_RDD_GIB@nass.usda.gov
Browse_Graphic:
Browse_Graphic_File_Name: https://cugir-data.s3.amazonaws.com/00/80/33/preview.png
Browse_Graphic_File_Description: preview of the dataset
Browse_Graphic_File_Type: PNG
Data_Set_Credit: USDA, National Agricultural Statistics Service
Security_Information:
Security_Classification_System: None
Security_Classification: Unclassified
Security_Handling_Description: None
Native_Data_Set_Environment: Microsoft Windows XP; ERDAS Imagine Versions 9.1, 9.2 and 9.3 <http://www.erdas.com/>; ESRI ArcGIS Version 9.3 <http://www.esri.com/>; Rulequest See5.0 Release 2.07 <http://www.rulequest.com/>; NLCD Mapping Tool <http://www.mrlc.gov/>. ERDAS Imagine is used in the pre- and post- processing of all raster-based data. ESRI ArcGIS is used to prepare the vector-based Farm Service Agency (FSA) Common Land Unit (CLU) training and validation data. Rulequest See5.0 is used to create a decision-tree based classifier. The NLCD Mapping Tool is used to apply the See5.0 decision-tree via ERDAS Imagine. This is a departure from older versions of the CDL that were created using in-house software (Peditor) based upon a maximum likelihood classifier approach. Check this section and the 'Process Description' section of the specific state and year metadata file to verify what methodology was used.

Data_Quality_Information

Attribute_Accuracy:
Attribute_Accuracy_Report: If the following table does not display properly, then please visit this internet site <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm> to view the original metadata file. USDA, National Agricultural Statistics Service, 2010 New York Cropland Data Layer STATEWIDE AGRICULTURAL ACCURACY REPORT Crop-specific covers only *Correct Accuracy Error Kappa ------------------------- ------- -------- ------ ----- OVERALL ACCURACY** 866026 73.87% 26.13% 0.6654 Cover Attribute *Correct Producer's Omission User's Commission Cond'l Type Code Pixels Accuracy Error Kappa Accuracy Error Kappa ---- ---- ------ -------- ----- ----- -------- ----- ----- Corn 1 354275 94.59% 5.41% 0.9307 89.35% 10.65% 0.8657 Sorghum 4 58 7.65% 92.35% 0.0765 54.21% 45.79% 0.5419 Soybeans 5 100468 84.60% 15.40% 0.8356 88.04% 11.96% 0.8720 Sunflower 6 15 4.76% 95.24% 0.0476 27.27% 72.73% 0.2726 Sweet Corn 12 3944 51.73% 48.27% 0.5159 76.72% 23.28% 0.7662 Pop. or Orn. Corn 13 0 0.00% 100.00% 0.0000 n/a n/a n/a Barley 21 280 12.67% 87.33% 0.1263 37.43% 62.57% 0.3736 Spring Wheat 23 43 12.80% 87.20% 0.1279 33.08% 66.92% 0.3306 Winter Wheat 24 26407 85.97% 14.03% 0.8573 85.30% 14.70% 0.8505 Dbl. Crop WinWht/Soy 26 0 0.00% 100.00% 0.0000 n/a n/a n/a Rye 27 606 18.21% 81.79% 0.1816 51.62% 48.38% 0.5153 Oats 28 9123 60.52% 39.48% 0.6025 73.98% 26.02% 0.7377 Millet 29 1 0.67% 99.33% 0.0067 100.00% 0.00% 1.0000 Speltz 30 325 29.52% 70.48% 0.2950 72.38% 27.62% 0.7237 Alfalfa 36 123782 66.65% 33.35% 0.6301 69.67% 30.33% 0.6620 Other Hay 37 226177 75.50% 24.50% 0.6974 65.78% 34.22% 0.5898 Sugarbeets 41 109 20.72% 79.28% 0.2071 48.02% 51.98% 0.4800 Dry Beans 42 5333 50.99% 49.01% 0.5079 70.05% 29.95% 0.6988 Potatoes 43 2537 63.06% 36.94% 0.6299 74.62% 25.38% 0.7456 Other Crops 44 79 6.12% 93.88% 0.0611 41.36% 58.64% 0.4132 Misc. Vegs. & Fruits 47 28 12.02% 87.98% 0.1201 44.44% 55.56% 0.4444 Onions 49 900 87.04% 12.96% 0.8703 69.82% 30.18% 0.6980 Peas 53 1882 58.61% 41.39% 0.5855 69.11% 30.89% 0.6906 Tomatoes 54 0 0.00% 100.00% 0.0000 0.00% 100.00% 0.0000 Herbs 57 0 n/a n/a n/a 0.00% 100.00% 0.0000 Clover/Wildflowers 58 992 20.20% 79.80% 0.2013 66.58% 33.42% 0.6649 Sod/Grass Seed 59 743 36.80% 63.20% 0.3676 61.87% 38.13% 0.6182 Switchgrass 60 0 n/a n/a n/a 0.00% 100.00% 0.0000 Fallow/Idle Cropland 61 6223 15.85% 84.15% 0.1507 37.84% 62.16% 0.3646 Pasture/Grass 62 25178 29.69% 70.31% 0.2769 50.31% 49.69% 0.4786 Cherries 66 45 22.50% 77.50% 0.2250 58.44% 41.56% 0.5844 Peaches 67 1 1.18% 98.82% 0.0118 50.00% 50.00% 0.5000 Apples 68 2525 52.47% 47.53% 0.5238 75.24% 24.76% 0.7517 Grapes 69 2254 66.16% 33.84% 0.6611 88.15% 11.85% 0.8813 Christmas Trees 70 30 8.80% 91.20% 0.0880 78.95% 21.05% 0.7894 Other Tree Fruits 73 0 0.00% 100.00% 0.0000 0.00% 100.00% -0.0001 Aquaculture 92 0 0.00% 100.00% 0.0000 n/a n/a n/a Triticale 205 233 17.52% 82.48% 0.1750 56.69% 43.31% 0.5666 Carrots 206 254 67.37% 32.63% 0.6737 62.25% 37.75% 0.6225 Asparagus 207 0 0.00% 100.00% 0.0000 n/a n/a n/a Prunes 210 0 0.00% 100.00% 0.0000 n/a n/a n/a Peppers 216 0 0.00% 100.00% 0.0000 n/a n/a n/a Nectarines 218 0 n/a n/a n/a 0.00% 100.00% 0.0000 Plums 220 0 0.00% 100.00% 0.0000 0.00% 100.00% 0.0000 Strawberries 221 0 0.00% 100.00% 0.0000 0.00% 100.00% 0.0000 Squash 222 91 12.53% 87.47% 0.1253 60.26% 39.74% 0.6025 Vetch 224 0 0.00% 100.00% 0.0000 n/a n/a n/a Dbl. Crop WinWht/Corn 225 2 1.15% 98.85% 0.0115 12.50% 87.50% 0.1249 Lettuce 227 0 0.00% 100.00% 0.0000 n/a n/a n/a Pumpkins 229 49 10.43% 89.57% 0.1042 36.30% 63.70% 0.3628 Blueberries 242 0 0.00% 100.00% 0.0000 0.00% 100.00% 0.0000 Cabbage 243 1067 54.97% 45.03% 0.5493 67.28% 32.72% 0.6724 Cauliflower 244 0 0.00% 100.00% 0.0000 n/a n/a n/a Radishes 246 0 n/a n/a n/a 0.00% 100.00% 0.0000 Eggplants 248 0 0.00% 100.00% 0.0000 n/a n/a n/a Cranberries 250 0 0.00% 100.00% 0.0000 0.00% 100.00% 0.0000 *Correct Pixels represents the total number of independent validation pixels correctly identified in the error matrix. **The Overall Accuracy represents only the FSA row crops and annual fruit and vegetables (codes 1-61 and 200-255). FSA-sampled tree and shrub crops, aquaculture, and all NLCD-sampled categories (codes 62-199) are not included in the Overall Accuracy. The accuracy of the non-agricultural land cover classes within the Cropland Data Layer is entirely dependent upon the USGS, National Land Cover Dataset (NLCD 2001). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover. For more information on the accuracy of the NLCD please reference <http://www.mrlc.gov/>.
Quantitative_Attribute_Accuracy_Assessment:
Attribute_Accuracy_Value: Classification accuracy is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the detailed accuracy report.
Attribute_Accuracy_Explanation: The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes is entirely dependent upon the USGS, National Land Cover Dataset (NLCD 2001). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover. The official DVD contains additional accuracy assessment information that is not available through the Geospatial Data Gateway in the form of an associated confidence layer. The following description of the confidence layer is taken from the document entitled 'MDA_NLCD_User_Guide.doc' which is available free for download with the NLCD Mapping Tool at <http://www.mrlc.gov/>. The Confidence Layer "spatially represents the predicted confidence that is associated with that output pixel, based upon the rule(s) that were used to classify it. This is useful in that the user can see the spatial representation of distribution and magnitude of error or confidence for a given classification... This error layer represents a percent confidence associated with each rule and output categorical, classified value. It is expressed as a percentage of confidence. A value of zero would therefore have a low confidence (always wrong), while a value of 100 would have a very high confidence (always right)." For more information on the use of confidence layers please refer to the following paper: Liu, Weiguo, Sucharita Gopal and Curtis E. Woodcock, 2004. Uncertainty and confidence in land cover classification using a hybrid classifier approach, Photogrammetric Engineering & Remote Sensing, 70(8):963-971. Ultimately, however, the confidence value is not a measure of accuracy for a given pixel but rather a how well it fit within the decision tree ruleset. These definitions of accuracy statistics were derived from the following book: Congalton, Russell G. and Kass Green. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. Boca Raton, Florida: CRC Press, Inc. 1999. The 'Producer's Accuracy' is calculated for each cover type in the ground truth and indicates the probability that a ground truth pixel will be correctly mapped (across all cover types) and measures 'errors of omission'. An 'Omission Error' occurs when a pixel is excluded from the category to which it belongs in the validation dataset. The 'User's Accuracy' indicates the probability that a pixel from the CDL classification actually matches the ground truth data and measures 'errors of commission'. The 'Commission Error' represent when a pixel is included in an incorrect category according to the validation data. It is important to take into consideration errors of omission and commission. For example, if you classify every pixel in a scene to 'wheat', then you have 100% Producer's Accuracy for the wheat category and 0% Omission Error. However, you would also have a very high error of commission as all other crop types would be included in the incorrect category. The 'Kappa' is a measure of agreement based on the difference between the actual agreement in the error matrix (i.e., the agreement between the remotely sensed classification and the reference data as indicated by the major diagonal) and the chance agreement which is indicated by the row and column totals. The 'Conditional Kappa Coefficient' is the agreement for an individual category within the entire error matrix.
Logical_Consistency_Report: The Cropland Data Layer (CDL) has been produced using training and independent validation data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program (agricultural data) and United States Geological Survey (USGS) National Land Cover Dataset 2001 (NLCD 2001). More information about the FSA CLU Program can be found at <http://www.fsa.usda.gov/>. More information about the NLCD 2001 can be found at <http://www.mrlc.gov/>. The CDL encompasses the entire state unless noted otherwise in the 'Completeness Report' section of this metadata file.
Completeness_Report: The entire state is covered by the Cropland Data Layer.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report: The Cropland Data Layer retains the spatial attributes of the input imagery. The Landsat 5 TM and Landsat 7 ETM imagery was obtained via download from the USGS Global Visualization Viewer (Glovis) website <http://glovis.usgs.gov/>. Please reference the metadata on the Glovis website for each Landsat scene for positional accuracy. The majority of the Landsat data is available at Level 1T (precision and terrain corrected). The AWiFS imagery used in the production of the Cropland Data Layer is purchased with an orthorectified level of processing. Thus, the CDL will retain the input imagery's positional accuracy of 60 meters at the circular error at the 90 percent confidence level (CE90). CE90 is a standard metric often used for horizontal accuracy in map products and can be interpreted as 90% of well-defined points tested must fall within a certain radial distance.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: Indian Remote-Sensing Satellite series of ISRO (Indian Space Research Organization)
Publication_Date: 2010 growing season
Title: RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS)
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Washington, D.C. 20008
Publisher: EOTec (Earth Observation Technologies, LLC)
Other_Citation_Details: The RESOURCESAT-1 (IRS-P6) AWiFS satellite sensor operates in four spectral bands at a spatial resolution of 56 meters. Additional information about AWiFS data can be obtained at <http://www.isro.org/>. The AWiFS imagery used in the Cropland Data Layer is obtained through a partnership with the USDA, Foreign Agricultural Service, International Production Assessment (IPA) Program. Refer to the 'Supplemental Information' Section of this metadata file for specific scene date, path, row and quadrants used as classification inputs. For the 2010 CDL Program, the AWiFS imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used bilinear interpolation, polynomial approximation, polynomial order of 3.
Source_Scale_Denominator: 56 meter
Type_of_Source_Media: CD-ROM and/or DVD
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20090925
Ending_Date: 20101230
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis
Source_Information:
Source_Citation:
Citation_Information:
Originator: United States Geological Survey (USGS), Earth Resources Observation and Science (EROS)
Publication_Date: 2010 growing season
Title: Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+)
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota 57198-001
Publisher: USGS, EROS
Other_Citation_Details: The Landsat 5 TM and Landsat 7 ETM+ data is free for download through the following website <http://glovis.usgs.gov/>. Additional information about Landsat data can be obtained at <http://eros.usgs.gov/>. Refer to the 'Supplemental Information' Section of this metadata file for specific scene date, path and rows used as classification inputs.
Source_Scale_Denominator: 30 meter
Type_of_Source_Media: online download
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20091001
Ending_Date: 20101230
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis
Source_Information:
Source_Citation:
Citation_Information:
Originator: United States Geological Survey (USGS) and National Aeronautics and Space Administration (NASA) Land Processes Distributed Active Archive Center (LP DAAC)
Publication_Date: late 2009 growing season and the entire 2010 growing season
Title: Moderate Resolution Imaging Spectroradiometer (MODIS), 250 meter resolution 16-day composite Normalized Difference Vegetation Index (NDVI) from the Terra satellite (MOD13Q1v4)
Geospatial_Data_Presentation_Form: vegetation indices based on remote-sensing imagery
Publication_Information:
Publication_Place: Sioux Falls, South Dakota 57198 USA
Publisher: USGS Center for Earth Resources Observation and Sciences (EROS)
Other_Citation_Details: The Moderate Resolution Imaging Spectroradiometer (MODIS), 250 meter resolution 16-day composite Normalized Difference Vegetation Index (NDVI) data products from the Terra satellite (MOD13Q1v4) are downloaded from <https://lpdaac.usgs.gov/>. Often late-season MODIS NDVI data are used from the previous growing season in an effort to improve winter wheat detection. Refer to the 'Supplemental Information' Section of this metadata file for specific dates used as classification inputs.
Source_Scale_Denominator: 250 meter
Type_of_Source_Media: online download
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20091001
Ending_Date: 20100930
Source_Currentness_Reference: ground condition
Source_Contribution: NDVI data used in land cover spectral signature analysis
Source_Information:
Source_Citation:
Citation_Information:
Originator: United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Data Center
Publication_Date: Continuously updated
Title: The National Elevation Dataset (NED)
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota 57198 USA
Publisher: USGS, EROS Data Center
Other_Citation_Details: The USGS NED Digital Elevation Model (DEM) is used as an ancillary data source in the production of the Cropland Data Layer. Slope and Aspect derived from the DEM are also used as additional classification inputs. More information on the USGS NED can be found at <http://ned.usgs.gov/>. Refer to the 'Supplemental Information' Section of this metadata file for the complete list of ancillary data sources used as classification inputs.
Source_Scale_Denominator: 30 meter
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: unknown
Source_Currentness_Reference: ground condition
Source_Contribution: spatial and attribute information used in land cover spectral signature analysis
Source_Information:
Source_Citation:
Citation_Information:
Originator: United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Data Center
Publication_Date: 2006
Title: National Land Cover Database 2001 (NLCD 2001)
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota 57198 USA
Publisher: USGS, EROS Data Center
Other_Citation_Details: The NLCD 2001 was used as ground training and validation for non-agricultural categories. Additionally, the USGS NLCD 2001 Imperviousness and Tree Canopy layers were used as ancillary data sources in the Cropland Data Layer classification process. More information on the NLCD 2001 can be found at <http://www.mrlc.gov/>. Refer to the 'Supplemental Information' Section of this metadata file for the complete list of ancillary data sources used as classification inputs.
Source_Scale_Denominator: 30 meter
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: unknown
Source_Currentness_Reference: ground condition
Source_Contribution: spatial and attribute information used in the spectral signature training and validation of non-agricultural land cover
Source_Information:
Source_Citation:
Citation_Information:
Originator: United States Department of Agriculture (USDA), Farm Service Agency (FSA)
Publication_Date: 2010
Title: USDA, FSA Common Land Unit (CLU)
Geospatial_Data_Presentation_Form: vector digital data
Publication_Information:
Publication_Place: Salt Lake City, Utah 84119-2020 USA
Publisher: USDA, FSA Aerial Photography Field Office
Other_Citation_Details: Access to the USDA, Farm Service Agency (FSA) Common Land Unit (CLU) digital data set is currently limited to FSA and Agency partnerships. During the current growing season, producers enrolled in FSA programs report their growing intentions, crops and acreage to USDA Field Service Centers. Their field boundaries are digitized in a standardized GIS data layer and the associated attribute information is maintained in a database known as 578 Administrative Data. This CLU/578 dataset provides a comprehensive and robust agricultural training and validation data set for the Cropland Data Layer. Additional information about the CLU Program can be found at <http://www.fsa.usda.gov/>.
Source_Scale_Denominator: 1:4800
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: unknown
Source_Currentness_Reference: ground condition, updated annually
Source_Contribution: spatial and attribute information used in the spectral signature training and validation of agricultural land cover
Process_Step:
Process_Description: OVERVIEW: The United States Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) Program is a unique agricultural-specific land cover geospatial product that is reproduced annually in participating states. The CDL Program builds upon NASS' traditional crop acreage estimation program and integrates Farm Service Agency (FSA) grower-reported field data with satellite imagery to create an unbiased statistical estimator of crop area at the state and county level for internal use. It is important to note that the internal acreage estimates produced using the CDL are not simple pixel counting. It is more of an 'Adjusted Census by Satellite.' SOFTWARE: ERDAS Imagine is used in the pre- and post- processing of all raster-based data. ESRI ArcGIS is used to prepare the vector-based training and validation data. Rulequest See5.0 is used to create a decision tree based classifier. The NLCD Mapping Tool is used to apply the See5.0 decision-tree via ERDAS Imagine. DECISION TREE CLASSIFIER: This Cropland Data Layer used the decision tree classifier approach. Using a decision tree classifier is a departure from older versions of the CDL which were created using in-house software (Peditor) based upon a maximum likelihood classifier approach. Check the 'Process Description' section of the specific state and year metadata file to verify the methodology used. Decision trees offer several advantages over the more traditional maximum likelihood classification method. The advantages include being: 1) non-parametric by nature and thus not reliant on the assumption of the input data being normally distributed, 2) efficient to construct and thus capable of handling large and complex data sets, 3) able to incorporate missing and non-continuous data, and 4) able to sort out non-linear relationships. GROUND TRUTH: As with the maximum likelihood method, decision tree analysis is a supervised classification technique. Thus, it relies on having a sample of known ground truth areas in which to train the classifier. Older versions of the CDL (prior to 2006) utilized ground truth data from the annual June Agricultural Survey (JAS). Beginning in 2006, the CDL utilizes the very comprehensive ground truth data provided from the FSA Common Land Unit (CLU) Program as a replacement for the JAS data. The FSA CLU data have the advantage of natively being in a GIS and containing magnitudes more of field level information. Disadvantages include that it is not truly a probability sample of land cover and has bias toward subsidized program crops. Additional information about the FSA data can be found at <http://www.fsa.usda.gov/>. INPUTS: The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, and the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. For the 2010 CDL Program, the AWiFS imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used bilinear interpolation, polynomial approximation, polynomial order of 3. 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 USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery and ancillary data used to generate this state's CDL. ACCURACY: The accuracy of the land cover classifications are evaluated using independent validations data sets generated from the FSA CLU data (agricultural categories) and the NLCD 2001 (non-agricultural categories). The Producer's Accuracy is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the full accuracy report. The official DVD contains additional accuracy assessment information that is not available through the Geospatial Data Gateway in the form of an associated confidence layer. See the 'Attribute Accuracy Explanation' Section of this metadata file for more information on the confidence layer. PUBLIC RELEASE: The USDA, NASS Cropland Data Layer is considered public domain and free to redistribute. The data is available on DVD for the cost of reproduction through the official website at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The most current year of data is available free for download for a limited time at the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The data is also available free for download through the CropScape - Cropland Data Layer website at <http://nassgeodata.gmu.edu/CropScape/>. The data is also available free for download through the Geospatial Data Gateway at <http://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed Geospatial Data Gateway download instructions. Please note that in no case are farmer reported data revealed or derivable from the public use Cropland Data Layer.
Process_Date: 2010
Process_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA, NASS, Spatial Analysis Research Section
Contact_Person: USDA, NASS, Spatial Analysis Research Section staff
Contact_Address:
Address_Type: mailing and physical address
Address: 3251 Old Lee Highway, Room 305
City: Fairfax
State_or_Province: Virginia
Postal_Code: 22030-1504
Country: USA
Contact_Voice_Telephone: 703-877-8000
Contact_Facsimile_Telephone: 703-877-8044
Contact_Electronic_Mail_Address: HQ_RDD_GIB@nass.usda.gov
Cloud_Cover: Generally, there is enough cloud-free satellite imagery available during the growing season that there will be no cloud cover in the published CDL. Older versions of the CDL (prior to 2006) may contain significant cloud cover due to available imagery and processing limitations, which have since been overcome. Reference the attribute information within the specific CDL state and year image file to verify the extent of cloud cover.

Spatial_Data_Organization_Information

Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 16925
Column_Count: 22229

Spatial_Reference_Information

Horizontal_Coordinate_System_Definition:
Planar:
Grid_Coordinate_System:
Grid_Coordinate_System_Name: Universal Transverse Mercator (UTM)
Universal_Transverse_Mercator:
UTM_Zone_Number: 18 North
Transverse_Mercator:
Scale_Factor_at_Central_Meridian: 0.9996
Longitude_of_Central_Meridian: -75
Latitude_of_Projection_Origin: 0
False_Easting: 500000
False_Northing: 0
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: coordinate pair
Coordinate_Representation:
Abscissa_Resolution: 30
Ordinate_Resolution: 30
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: WGS84
Ellipsoid_Name: WGS84
Semi-major_Axis: 6378137.00
Denominator_of_Flattening_Ratio: 298.257223563

Entity_and_Attribute_Information

Overview_Description:
Entity_and_Attribute_Overview: The Cropland Data Layer (CDL) is produced using agricultural training data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program and non-agricultural training data from the United States Geological Survey (USGS) National Land Cover Dataset 2001 (NLCD 2001). The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes are entirely dependent upon the NLCD. Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover.
Entity_and_Attribute_Detail_Citation: If the following table does not display properly, then please visit the following website to view the original metadata file <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm>. Data Dictionary: USDA, National Agricultural Statistics Service, 2010 Cropland Data Layer Source: USDA, National Agricultural Statistics Service The following is a cross reference list of the categorization codes and land covers. Note that not all land cover categories listed below will appear in an individual state. Raster Attribute Domain Values and Definitions: NO DATA, BACKGROUND 0 Categorization Code Land Cover "0" Background Raster Attribute Domain Values and Definitions: CROPS 1-20 Categorization Code Land Cover "1" Corn "2" Cotton "3" Rice "4" Sorghum "5" Soybeans "6" Sunflower "10" Peanuts "11" Tobacco "12" Sweet Corn "13" Pop. or Orn. Corn "14" Mint Raster Attribute Domain Values and Definitions: GRAINS,HAY,SEEDS 21-40 Categorization Code Land Cover "21" Barley "22" Durum Wheat "23" Spring Wheat "24" Winter Wheat "25" Other Small Grains "26" Dbl. Crop WinWht/Soy "27" Rye "28" Oats "29" Millet "30" Speltz "31" Canola "32" Flaxseed "33" Safflower "34" Rape Seed "35" Mustard "36" Alfalfa "37" Other Hay "38" Camelina Raster Attribute Domain Values and Definitions: CROPS 41-60 Categorization Code Land Cover "41" Sugarbeets "42" Dry Beans "43" Potatoes "44" Other Crops "45" Sugarcane "46" Sweet Potatoes "47" Misc. Vegs. & Fruits "48" Watermelons "49" Onions "50" Pickles "51" Chick Peas "52" Lentils "53" Peas "54" Tomatoes "55" Caneberries "56" Hops "57" Herbs "58" Clover/Wildflowers "59" Sod/Grass Seed "60" Switchgrass Raster Attribute Domain Values and Definitions: NON-CROP 61-65 Categorization Code Land Cover "61" Fallow/Idle Cropland "62" Pasture/Grass "63" Woodland "64" Shrubland "65" Barren Raster Attribute Domain Values and Definitions: CROPS 66-80 Categorization Code Land Cover "66" Cherries "67" Peaches "68" Apples "69" Grapes "70" Christmas Trees "71" Other Tree Nuts "72" Citrus "73" Other Tree Fruits "74" Pecans "75" Almonds "76" Walnuts "77" Pears "80" Other Non-Tree Fruit Raster Attribute Domain Values and Definitions: OTHER 81-109 Categorization Code Land Cover "81" Clouds "82" Urban/Developed "83" Water "84" Roads/Railroads "85" Waterways/Ditches "86" Buildings/Residential Areas "87" Wetlands "88" Nonag/Undefined "90" Mixed Water/Crops "91" Mixed Water/Clouds "92" Aquaculture "96" Fallow Sugarcane (FL04 only) "97" Scrub/Shrub Wetlands (FL04 only) "98" Aquatic Beds (FL04 only) "99" Unconsolidated Shore (FL04 only) Raster Attribute Domain Values and Definitions: NLCD-DERIVED CLASSES 110-195 Categorization Code Land Cover "111" Open Water "112" Perennial Ice/Snow "121" Developed/Open Space "122" Developed/Low Intensity "123" Developed/Medium Intensity "124" Developed/High Intensity "131" Barren "141" Deciduous Forest "142" Evergreen Forest "143" Mixed Forest "152" Shrubland "171" Grassland Herbaceous "181" Pasture/Hay "182" Cultivated Crop "190" Woody Wetlands "195" Herbaceous Wetlands Raster Attribute Domain Values and Definitions: CROPS 195-255 Categorization Code Land Cover "204" Pistachios "205" Triticale "206" Carrots "207" Asparagus "208" Garlic "209" Cantaloupes "210" Prunes "211" Olives "212" Oranges "213" Honeydew Melons "214" Broccoli "216" Peppers "217" Pomegranates "218" Nectarines "219" Greens "220" Plums "221" Strawberries "222" Squash "223" Apricots "224" Vetch "225" Dbl. Crop WinWht/Corn "226" Dbl. Crop Oats/Corn "227" Lettuce "228" Cucumbers "229" Pumpkins "230" Dbl. Crop Lettuce/Durum Wht "231" Dbl. Crop Lettuce/Cantaloupe "232" Dbl. Crop Lettuce/Upland Cotton "233" Dbl. Crop Lettuce/Barley "234" Dbl. Crop Durum Wht/Sorghum "235" Dbl. Crop Barley/Sorghum "236" Dbl. Crop WinWht/Sorghum "237" Dbl. Crop Barley/Corn "238" Dbl. Crop WinWht/Cotton "239" Dbl. Crop Soybeans/Cotton "240" Dbl. Crop Soybeans/Oats "241" Dbl. Crop Corn/Soybeans "242" Blueberries "243" Cabbage "244" Cauliflower "245" Celery "246" Radishes "247" Turnips "248" Eggplants "249" Gourds "250" Cranberries "254" Dbl. Crop Barley/Soybeans

Distribution_Information

Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: Albert R. Mann Library
Contact_Address:
Address_Type: mailing and physical
Address: Cornell University
City: Ithaca
State_or_Province: New York
Postal_Code: 14853
Contact_Voice_Telephone: 607-255-5406
Contact_Electronic_Mail_Address: mann-ref@cornell.edu
Distribution_Liability: Cornell University provides these geographic data "as is". Cornell University makes no guarantee or warranty concerning the accuracy of information contained in the geographic data. Cornell University further makes no warranty either expressed or implied, regarding the condition of the product or its fitness for any particular purpose. The burden for determining fitness for use lies entirely with the user. Although these files have been processed successfully on computers at Cornell University, no warranty is made by Cornell University regarding the use of these data on any other system, nor does the fact of distribution constitute or imply any such warranty.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: GeoTIFF
Format_Information_Content: zipped geotiff
File_Decompression_Technique: zip
Transfer_Size: 37.08
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Digital_Form:
Digital_Transfer_Information:
Format_Name: metadata
Format_Information_Content: FGDC XML metadata
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Digital_Form:
Digital_Transfer_Information:
Format_Name: HTML metadata
Format_Information_Content: FGDC HTML metadata
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Digital_Form:
Digital_Transfer_Information:
Format_Name: OGC:WMS
Format_Information_Content: WMS, from GeoServer
Digital_Transfer_Option:
Online_Option:
Fees: None

Distribution_Information

Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA, NASS Customer Service
Contact_Person: USDA, NASS Customer Service Staff
Contact_Address:
Address_Type: mailing and physical address
Address: 1400 Independence Avenue, SW, Room 5038-S
City: Washington
State_or_Province: District of Columbia
Postal_Code: 20250-9410
Country: USA
Contact_Voice_Telephone: 800-727-9540
Contact_Facsimile_Telephone: 703-877-8044
Contact_Electronic_Mail_Address: HQ_RDD_GIB@nass.usda.gov
Contact_Instructions: The Cropland Data Layer is available free for download at <http://datagateway.nrcs.usda.gov/>. The most current year of data is available free for download for a limited time at the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. To order a CD-ROM or DVD fill out the order form at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> and submit it either electronically (invoice will follow with the delivery) or mail the completed form with your check to: USDA/NASS Customer Service, 1400 Independence Avenue, SW, Room 5829-S, Washington DC 20250-9410. Please note 'Cropland Data Layer - (State and Year)' in the 'Memo' of your check. Checks should be made out to 'USDA, NASS'. Allow 1 week for delivery.
Resource_Description: Cropland Data Layer - New York 2010
Distribution_Liability: Disclaimer: Users of the Cropland Data Layer (CDL) are solely responsible for interpretations made from these products. The CDL is provided 'as is' and the USDA, NASS does not warrant results you may obtain using the Cropland Data Layer. Contact our staff at (HQ_RDD_GIB@nass.usda.gov) if technical questions arise in the use of the CDL. NASS does maintain a Frequently Asked Questions (FAQ's) section on the CDL website at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: GEOTIFF
Format_Version_Date: New York 2010
Format_Information_Content: GEOTIFF
Transfer_Size: The image file size will vary depending on the state and completeness of coverage. The CD-ROM and/or DVD obtained through the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> contains data for a single year. The user can specify the state, or a user-defined area of interest, and year(s) of CDL data to download at the Cropscape website <http://nassgeodata.gmu.edu/CropScape/>. When downloading the data through the Geospatial Data Gateway <http://datagateway.nrcs.usda.gov/> all available years of CDL production for the requested state are included in one compressed file. Technical restrictions do not allow us to offer the CDL by individual state/year through the Geospatial Data Gateway. See the 'Ordering Instructions' section of this metadata file for additional information.
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: http://nassgeodata.gmu.edu/CropScape/
Access_Instructions: The CDL is available online and free for download from the Cropscape website <http://nassgeodata.gmu.edu/CropScape/>. The most current year of data is available free for download for a limited time at the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. It is also available free for download from the Geospatial Data Gateway website <http://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed Geospatial Data Gateway download instructions.
Offline_Option:
Offline_Media: CD-ROM or DVD
Recording_Format: DOS-COPY
Fees: The USDA, NASS charges a nominal fee to cover the cost of CD-ROM and DVD production and shipping costs. Please visit the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> for prices. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540. The Cropland Data Layer is also available free for download at <http://nassgeodata.gmu.edu/CropScape/> and <http://datagateway.nrcs.usda.gov/>.
Ordering_Instructions: To order a CD-ROM or DVD fill out the order form at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> and submit it either electronically (invoice will follow with the delivery) or mail the completed form with your check to: USDA, NASS Customer Service, 1400 Independence Avenue, SW, Room 5829-S, Washington DC 20250-9410. Please note 'Cropland Data Layer - (State and Year)' in the 'Memo' part of your check. Checks should be made out to 'USDA, NASS'. Allow 1 week for delivery. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540. The CDL is available online and free for download from the Cropscape website <http://nassgeodata.gmu.edu/CropScape/>. The most current year of data is available free for download for a limited time at the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The Cropland Data Layer is also available free for download from the NRCS Geospatial Data Gateway at <http://datagateway.nrcs.usda.gov/>. IMPORTANT NOTE: When downloading the CDL using the NRCS Geospatial Data Gateway all available years of CDL production for the requested state are included in a single compressed file. Geospatial Data Gateway technical restrictions do not allow us to offer the CDL by individual state/year. We are working on offering this option in the future. Instructions for downloading from the NRCS Geospatial Data Gateway: Start by clicking on 'Get Data' Then click on 'Quick State' Scroll down to choose your state and click 'Continue' Choose 'Land_use_land_cover' and select 'Cropland Data Layer by State' and 'Continue to Step3' Choose 'Continue' to Step4 Lastly, you are given the option to download the data for free or to order the official DVD/CD for the cost of the reproduction.
Turnaround: Allow 1 week for delivery for CD-ROM and/or DVD.
Custom_Order_Process: For a list of other states and years of available CDL data please visit <http://nassgeodata.gmu.edu/CropScape/> or <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540.
Technical_Prerequisites: If the user does not have software capable of viewing GEOTIF (.tif) or ERDAS Imagine (.img) file formats then we suggest using the Cropscape website <http://nassgeodata.gmu.edu/CropScape/> or using the freeware browser ESRI ArcGIS Explorer <http://www.esri.com/>.

Metadata_Reference_Information

Metadata_Date: 20190604
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: Albert R. Mann Library
Contact_Address:
Address_Type: mailing and physical
Address: Albert R. Mann Library
City: Ithaca
State_or_Province: New York
Postal_Code: 14853
Country: USA
Contact_Voice_Telephone: 607-255-5406
Contact_Electronic_Mail_Address: mann-ref@cornell.edu
Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Time_Convention: local time