USDA, National Agricultural Statistics Service, 2004 Florida Cropland Data Layer

Metadata:


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: 20070314
Title:
USDA, National Agricultural Statistics Service, 2004 Florida Cropland Data Layer
Edition: 2004 Edition
Geospatial_Data_Presentation_Form: raster digital data
Publication_Information:
Publication_Place:
USDA, NASS Marketing and Information Services Office, Washington, D.C.
Publisher: USDA, NASS
Other_Citation_Details:
NASS maintains a Frequently Asked Questions (FAQ's) section on the CDL website at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The data is available free for download through CropScape 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.
Online_Linkage: <http://nassgeodata.gmu.edu/CropScape/FL>
Description:
Abstract:
***2004 Florida Cropland Data Layer specific information*** The processing for the Florida CDL differed from the other 2004 CDLs. Firstly, the Florida CDL used additional citrus training/validation data provided by the Florida NASS Field Office. The Citrus Grove Data Layer is confidential and for internal NASS use only. The second major difference in processing is that special processing was required to properly identify sugarcane. This included photo intrepretation to identify additional sugarcane training data and to limit the spatial extent of the sugarcane area.

The USDA-NASS 2004 Florida 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 Enhanced Thematic Mapper Plus (ETM+) on Landsat 7 (GAP Filled) with the emphasis being agricultural land cover. The imagery was collected between the dates of 04/03/2004 and 11/29/2004. The approximate scale is 1:100,000 with a ground resolution of 30 meters by 30 meters. The Florida Program represents a cooperative venture between three USDA Agencies (headquarters units of NASS, the Foreign Agriculture Service, and the Farm Service Agency) plus an in-state agreement with the Florida Agricultural Statistics Service.
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 Database 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 were derived from the extensive field observations collected during the annual NASS June Agricultural Survey and 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 this internet site <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm> to view the original metadata file.
USDA, National Agricultural Statistics Service 2004 Arkansas Cropland Data Layer

CLASSIFICATION INPUTS BY ANALYSIS DISTRICT (AD):

AD01:     LANDSAT TM/ETM+ Path 16 Row(s) 39 & 40, 04/03/2004 + 05/05/2004
          LANDSAT TM/ETM+ Path 20 Row(s) 39, 04/15/2004 + 07/20/2004
          LANDSAT TM/ETM+ Path 19 Row(s) 39, 04/16/2004 + 07/21/2004
          LANDSAT TM/ETM+ Path 18 Row(s) 39, 04/17/2004 + 09/22/2004
          LANDSAT TM/ETM+ Path 17 Row(s) 39 & 40, 05/04/2004
          LANDSAT TM/ETM+ Path 17 Row(s) 39 & 40, 05/04/2004 + 09/01/2004
          LANDSAT TM/ETM+ Path 16 Row(s) 39 & 40, 05/05/2004

AD02:     LANDSAT TM/ETM+ Path 16 Row(s) 39, 40 & 41, 04/03/2004 + 11/29/2004
          LANDSAT TM/ETM+ Path 15 Row(s) 42 & 43, 04/04/2004
          LANDSAT TM/ETM+ Path 15 Row(s) 41, 04/04/2004 + 04/28/2004
          LANDSAT TM/ETM+ Path 15 Row(s) 42 & 43, 04/04/2004 + 05/30/2004
          LANDSAT TM/ETM+ Path 17 Row(s) 39 & 40, 05/04/2004
          LANDSAT TM/ETM+ Path 15 Row(s) 42 & 43, 05/30/2004
          LANDSAT TM/ETM+ Path 17 Row(s) 41, 09/01/2004

TRAINING AND VALIDATION:
USDA, NASS JUNE AREA SURVEY 2004
USDS, NASS 2004 FLORIDA CITRUS GROVE DATA LAYER
USDA, FARM SERVICE AGENCY 2004 COMMON LAND UNIT DATA
USGS, NATIONAL LAND COVER DATABASE 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: 20040101
Ending_Date: 20041230
Currentness_Reference: 2004 growing season
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -87.6435
East_Bounding_Coordinate: -80.0490
North_Bounding_Coordinate: 30.9950
South_Bounding_Coordinate: 24.5432
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: farming, 001
Theme_Keyword: environment, 007
Theme_Keyword: imageryBaseMapsEarthCover, 010
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:
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
Place:
Place_Keyword_Thesaurus: Global Change Master Directory (GCMD) Location Keywords
Place_Keyword: Continent > North America > United States of America > Florida
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Florida
Place_Keyword: FL

Temporal:
Temporal_Keyword_Thesaurus: None
Temporal_Keyword: 2004
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
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:
The hardware requirements for processing this data set are as follows: for digitizing/ground truth editing, any of the 32 bit Microsoft OS's will work. For computationally intensive jobs including; scene processing, clustering, classification, estimation and mosaicking a batch type system is utilized where jobs can be queued on different devices, and the minimum requirements are NT/2000/XP.Image processing is typically performed using PEDITOR, where PEDITOR utilizes the Windows console along with environmental variables, and neither are available with 95/98. PEDITOR as it is now constituted, will only run under the Microsoft Windows operating systems.The 2004 Florida Cropland Data Layer was created using Rulequest's See5.0 software rather than NASS' Peditor in-house software. All available raw Landsat imagery for the region was used as input along with the non-agricultural portion of the United States Geological Survey's 2001 National Land Cover Data. More information on Rulequest's See5.0 software can be found at <http://www.rulequest.com/>.A Microsoft Visual FoxPro application called the Remote Sensing Project or RSP is used to manage the ground truth collection process, and track each segment to its completion.Commercial off the shelf software XLNT from Advanced Systems Concepts, allows for batch job processing on the NT/2000/XP operating systems. SARS utilizes XLNT to run computationally intensive jobs that are shared across network resources to expedite processing. Additional information about XLNT can be found at <http://www.advsyscon.com/>.In 2005, NASS began testing the use of Rulequest's See5.0 software rather than PEDITOR. Check the "Process_Description" section of this metadata file for more details on which methodology was used for this specific state and year. Additional information on Rulequest's See5.0 software can be found at <http://www.rulequest.com/>.Leica Geosystems ERDAS Imagine and ESRI's ArcGIS are often used in the pre- and post-processing of data. Additional information about Leica Geosystems ERDAS Imagine software can be found at <http://gi.leica-geosystems.com/>. Additional information about ESRI's ArcGIS software can be found at <http://www.esri.com/>.
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.
FLORIDA 2004
CROP TYPE, ACCURACY MATRIX AND KAPPA
Crop        Cover                         Corn    Cotton   Sorghum   Soybeans   Peanuts    WinWheat/Rye   Other Crop,    Sugarcane    Watermelon     Grass     Citrus    Total Pixel  User
Code        Name                                                                           Oats/Millet    Mixed Forage                OtherFruit&Veg Pasture             Count        Accuracies
1           Corn                          41386   21       0         1          14         71             6              0            98             7727      275       49599        83.44
2           Cotton(Upland)                733     96224    0         97         453        598            47             0            13             4733      0         102238       94.12
4           Sorghum                       12      0        2592      0          0          0              0              0            0              21        0         2625         98.74
5           Soybeans                      33      35       0         17624      39         50             6              0            0              155       0         17942        98.23
10          Peanuts                       155     966      1         27         148665     201            135            0            357            3541      123       154171       96.43
24,27,28,29 WW/Rye/Oats/Millet            69      150      9         9          135        69652          3277           0            0              1052      0         74342        93.69
44,62       Other Crop, Mixed forage      14733   0        2618      0          0          0              4313           1            0              1306      26575     36286        11.89
45          Sugarcane                     134     0        0         0          0          0              1474           56013        0              0         4108      61729        90.74
48,47,71,80 Watermelon/Other Fruit & Veg  0       3        0         0          46         50             382            0            6812           43        0         7336         92.86
62          Grass/Pasture/Nonag/Range     696     810      116       296        2356       5528           9713           428          1771           729996    454562    1206272      60.52
72          Citrus                        0       0        0         0          0          0              12             0            3              525       2055068   2055608      99.97
            Sum of Pixels Classified by   44031   98209    5336      18054      151708     76150          19365          56442        9054           749099    2540711   3768159
            Producer Accuracies           93.99   97.98    48.58     97.62      97.99      91.47          22.27          99.24        0.75           97.45     80.89                  0.86
Kappa Statistic = 0.747
NOTE: Accuracy statistics are reported for agricultural areas within the entire state rather than by individual Analysis District. Accuracy statistics for the NLCD categories are not included.
The producer's accuracy relates to the probability that a reference sample will be correctly mapped and measures the errors of omission. In contrast, the user's accuracy indicates the probability
that a sample from a land cover map actually matches what it is from the reference data and measures the error of commission.
***NOTE: The attribute codes above may not necessarily match the most current coding scheme. Please check the Entity_and_Attribute_Detail_Citation Section of this metadata file to verify the current attibute codes and category names.
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 accuracy of the land cover classifications are evaluated using the extensive training data collected in the annual NASS June Area Survey (JAS) and/or the annual Farm Service Agency's (FSA) Common Land Unit (CLU) data. More information about FSA CLUs can be found at <http://www.fsa.usda.gov/> and <http://datagateway.nrcs.usda.gov/>.The June Agricultural Survey is a national survey based on a stratified random sample of land areas selected from each state's area frame. An area frame is a land use stratification based on percent cultivation. Additional information about NASS' June Area Survey can be found at <http://www.nass.usda.gov/Surveys/June_Area/>.Please note that no farmer reported data is derivable from the Cropland Data Layer.
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 Database (NLCD 2001). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover.
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 accuracy of the land cover classifications are evaluated using the extensive training data collected in the annual NASS June Area Survey (JAS) and/or the annual Farm Service Agency's (FSA) Common Land Unit (CLU) data. More information about FSA CLUs can be found at <http://www.fsa.usda.gov/> and <http://datagateway.nrcs.usda.gov/>.The June Agricultural Survey is a national survey based on a stratified random sample of land areas selected from each state's area frame. An area frame is a land use stratification based on percent cultivation. Additional information about NASS' June Area Survey can be found at <http://www.nass.usda.gov/Surveys/June_Area/>.Please note that no farmer reported data is derivable from the Cropland Data Layer. 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 categorized images are co-registered to MDA Federal Inc's ortho-rectified GeoCover Stock Mosaic images using automated block correlation techniques. The block correlation is run against band two of each original raw satellite image and band two of the GeoCover Stock Mosaic. The resulting correlations are applied to each categorized image, and then added to a master image or mosaic using PEDITOR. The MDA Federal Inc images were chosen as they provide the best available large area ortho-rectified images as a basis to register large volume Landsat images with.
Quantitative_Horizontal_Positional_Accuracy_Assessment:
Horizontal_Positional_Accuracy_Value: 50 meters root mean squared error overall
Horizontal_Positional_Accuracy_Explanation:
The MDA Federal Inc's ortho-rectified GeoCover Stock Mosaics are within 50 meters root mean squared error overall.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 7 (GAP Filled)
Publication_Date: 20041001
Title: LANDSAT TM Path 15, Rows 41, 42 and 43
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 15, Rows 41, 42 and 43. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator:
100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 100000, 8000, 100000, 100000, 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20040404
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 15, Row 41
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 15, Row 41. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20040428
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 15, Rows 42 and 43
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 15, Rows 42 and 43. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20040530
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 16, Row 39
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 16, Row 39. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
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Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 16, Row 40
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 16, Row 40. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
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Single_Date/Time:
Calendar_Date: 20041129
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 16, Rows 41 and 42
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 16, Rows 41 and 42. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
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Single_Date/Time:
Calendar_Date: 20041129
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 7 (GAP Filled)
Publication_Date: 20041001
Title: LANDSAT TM Path 17, Rows 39 and 40
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 17, Rows 39 and 40. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
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Calendar_Date: 20040504
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 17, Rows 39 and 40
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 17, Rows 39 and 40. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20040901
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 17, Row 41
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 17, Row 41. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 20040901
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 18, Row 39
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 18, Row 39. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Multiple_Dates/Times:
Single_Date/Time:
Calendar_Date: 20040417
Single_Date/Time:
Calendar_Date: 20040722
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 7 (GAP Filled)
Publication_Date: 20041001
Title: LANDSAT TM Path 19, Row 39
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 17, Row 39. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Multiple_Dates/Times:
Single_Date/Time:
Calendar_Date: 20040416
Single_Date/Time:
Calendar_Date: 20040721
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Landsat 5
Publication_Date: 20041001
Title: LANDSAT TM Path 20, Row 39
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Sioux Falls, South Dakota, USA
Publisher: USGS EROS Data Center
Other_Citation_Details:
LANDSAT TM Path 20, Row 39. 30 meter by 30 meter pixel resolution, EOSAT Fast Format. Additional information about Landsat 5 and Landsat 7 satellite imagery can be obtained from the United States Geological Survey (USGS) EROS Data Center.
Source_Scale_Denominator: 100000
Type_of_Source_Media: CD-ROM
Source_Time_Period_of_Content:
Time_Period_Information:
Multiple_Dates/Times:
Single_Date/Time:
Calendar_Date: 20040415
Single_Date/Time:
Calendar_Date: 20040720
Source_Currentness_Reference: ground condition
Source_Contribution: Raw data used in land cover spectral signature analysis.
Source_Information:
Source_Citation:
Citation_Information:
Originator: National Aerial Photography Program (NAPP)
Publication_Date: variable
Title: NAPP aerial photographs
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:
Publication_Place: Salt Lake City, Utah, USA
Publisher: Aerial Photography Field Office (AFPO)
Other_Citation_Details:
Additional information about NAPP can be obtained from the following internet site: <http://eros.usgs.gov/>
Source_Scale_Denominator: 8000
Type_of_Source_Media: paper
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: variable
Source_Currentness_Reference: ground condition
Source_Contribution: spatial and attribute information
Source_Information:
Source_Citation:
Citation_Information:
Originator:
USDA/NASS, Research and Development Division, Area Frame Section
Publication_Date: 1983
Title: Area Sampling Frame (ASF) of Florida
Geospatial_Data_Presentation_Form: vector digital data
Publication_Information:
Publication_Place: Washington D.C., USA
Publisher: USDA-NASS
Other_Citation_Details:
Additional information about the NASS Area Frame Stratification can be obtained from the following internet site: <http://www.nass.usda.gov/research/stratafront2b.htm>
Source_Scale_Denominator: 100000
Type_of_Source_Media: online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 1983
Source_Currentness_Reference: publication date
Source_Contribution: spatial and attribute information
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Geological Survey EROS Data Center
Publication_Date: 2006
Title: 2001 National Land Cover Data (NLCD) Mapping Zone 55
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 Land Cover Characterization of the 2001 NLCD was used to improve the non-agricultural portion of the Cropland Data Layer. More information on the NLCD can be found at <http://www.mrlc.gov/>.
Source_Scale_Denominator: 100000
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
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Geological Survey EROS Data Center
Publication_Date: 2006
Title: 2001 National Land Cover Data (NLCD) Mapping Zone 56
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 Land Cover Characterization of the 2001 NLCD was used to improve the non-agricultural portion of the Cropland Data Layer. More information on the NLCD can be found at <http://www.mrlc.gov/>.
Source_Scale_Denominator: 100000
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
Process_Step:
Process_Description:
***2004 Florida Cropland Data Layer specific information*** The processing for the Florida CDL differed from the other 2004 CDLs. Firstly, the Florida CDL used additional citrus training/validation data provided by the Florida NASS Field Office. The Citrus Grove Data Layer is confidential and for internal NASS use only. The second major difference in processing is that special processing was required to properly identify sugarcane. This included photo intrepretation to identify additional sugarcane training data and to limit the spatial extent of the sugarcane area.

The Cropland Data Layer (CDL) Program provides the National Agricultural Statistics Service (NASS) with internal proprietary county and state level acreage indications of major crop commodities, and secondarily provides the public with "statewide" (where available) raster, geo-referenced, categorized land cover data products after the public release of county estimates. This project builds upon NASS' traditional crop acreage estimation program, and integrates enumerator collected ground survey data and/or Farm Service Agency field data with satellite imagery to create an unbiased statistical estimator of crop area at the state and county level for internal use. Please note that in no case is farmer reported data revealed or derivable from the public use Cropland Data Layer.The 2004 Florida Cropland Data Layer was developed using Leica Geosystems ERDAS Imagine in tandem with Rulequest See5.0. Both are commercial software packages. ERDAS Imagine, being a comprehensive image processing suite, handled the bulk of the processing steps including preprocessing and managing of the raw imagery and training data, building of the scene classifications, and creation of the final statewide mosaics. See5.0 was solely used to derive the classification rules, based on training data, for which ERDAS Imagine then applies back to the input imagery. Broadly defined, See5.0 is a niche data mining tool that derives decision trees, or a set of if-then rules, to assemble data into categories. It is not a GIS application in itself.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 handling large and complex data sets, 3) able to incorporate missing and non-continuous data, and 4) able to sort out non-linear relationships. These reasons combined usually lead to improved classifications over the maximum likelihood method. Additionally, there are several varieties of decision tree classifiers but See5.0 stands out because it further employs a statistical technique known as "boosting" which has been shown to improve results even further. More information on Rulequest's See5.0 software can be found at <http://www.rulequest.com/>.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. In turn, the classifier can then "learn" how to most reasonably place into a category the rest of the unknown pixels. The best ground truth comes from a statistically representative probability sample that is dense enough to account for the variability of the land cover types that are being mapped. Traditionally, NASS CDLs have utilized ground truth data from the annual June Agricultural Survey (JAS). More information about the JAS can be found at <http://www.nass.usda.gov/Surveys/June_Area/>. To make this survey data available for use within a classification takes a fair amount of labor because the field boundaries and attributes have to be manually digitized into a GIS since natively they are recorded only on paper. More recently, very comprehensive ground truth data has been provided from the Farm Service Agency (FSA) which NASS has begun utilizing as a replacement for the JAS information. The FSA data has the advantage of natively being in a GIS and containing magnitudes more of field level information. Disadvantages include 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/> and <http://datagateway.nrcs.usda.gov/>.All available raw satellite imagery for the region was used as input along with the non-agricultural portion of the United States Geological Survey's (USGS) 2001 National Land Cover Data (NLCD). Additional information on the USGS NLCD can be found at <http://www.mrlc.gov/>.Scene selection begins in early summer, and could run into the late fall depending on image availability. The Cropland Data Layer program primarily uses the Landsat TM or IRS AWIFS platform for acreage estimation. However, other platforms such as Spot or gap-filled Landsat ETM+ are used to fill "data acquisition" holes within a state. A spring and summer date of observation is preferred for maximum crop cover separation for multi-temporal analysis of summer crops. If only one date of observation is available (unitemporal), a mid summer date is preferred. If only an early spring date March-May or a fall date September-October is available (unitemporal) during the growing season, then it is best to not use that scene or analysis district for estimation, as bare soil in the spring and fully senesced crops in the fall will provide erroneous results.For estimation purposes, clouds can be minimized by defining Analysis Districts (AD) along adjacent scene edges, by cutting the Analysis Districts by county boundary, or cutting the clouds out by primary sampling units. Analysis Districts can be individual or multiple scenes footprints that have to be observed on the same date, and analyzed as one. An AD can be comprised of one or more scenes. An AD can be defined by either a scene edge or a county boundary. Multi-temporal AD's are possible as long as both dates in all scenes are the same. A single or multi-scene AD will use all potential training fields for clustering/classification/estimation. Several factors can lead to problems in a classification, some get corrected in early edits and some do not.Several factors can lead to problems in a classification, some get corrected in early edits and some do not: poor imagery dates, with respect to the major crops of interest, incomplete or incorrect the ground truth, irrigation ditches, wooded areas, low spots filled with water, and/or bare soil areas in an otherwise vegetated field. Crops that look alike to the clustering algorithm(s) due to planting/growing cycle: spring wheat and barley at almost any time, crops in senescence, and grassy waste fields and idle cropland. Cover types that are essentially the same but used differently: wooded pasture versus woods or waste fields (only difference may be the presence of livestock), corn for grain versus corn silage, and cover crops such as rye and oats. Cover types that change signatures back and forth during the growing season: alfalfa and other hays before and after cutting, with multiple cuttings per year.Each categorized scene is co-registered to MDA Federal Inc's GeoCover LC imagery (50 meters RMS), and then stitched together using Peditor's Batch program. A block correlation is run between band two from each raw scene, and band two of the ortho-base image. The registration of the GeoCover mosaicked scene and the individual raw input scenes are used to get an approximate correspondence. A correlation procedure is used on the raw scenes and the mosaicked scene to get an exact mapping of each pixel from the input scenes to the mosaicked scene. The results of the correlation are used to remap the pixels from the individual input scenes into the coordinate system of the mosaicked scene. The mosaic process now performs: 1) Precision registration of images automatically, 2) Converts each categorized image and associated statistics file to a set standard automatically (recode), 3) Specify overlap priority by scene or county, 4) Filters out clouds when possible. The scenes are stitched together using the priorities previously assigned from the scene observation dates/analysis districts map. Scenes/analysis districts with better quality observation dates are assigned a higher priority when stitching the images together. Clouds are assigned a null value on all scenes, and scenes of lower priority that are cloud free, take precedence over clouded higher priority images. Once cloud cover is established throughout the mosaic the clouds are assigned a digital value.The Cropland Data Layer products contain imagery in GEOTIFF image file format.All CDL distribution for the previous crop year is held until the release of the official NASS county estimates for the major commodities grown within a given state. Corn and Soybeans are released in March for the previous crop year - Midwestern States. Rice and Cotton are released in June for the previous crop year - Delta States. Small grains are released in March for the Great Plains States.NASS publishes all available accuracy statistics for end-user viewing. The Percent Correct is calculated for each cover type in the ground truth, it shows how many of the total pixels were correctly classified (i.e. across all cover types). 'Commission Error' is the calculated percentage of all pixels categorized to a specific cover type that were not of that cover type in the ground truth (i.e. incorrectly categorized). CAUTION: a quoted Percent Correct for a specific cover type is worthless unless accompanied by its respective Commission Error. Example: if you classify every pixel in a scene to 'wheat', then you have a 100% correct wheat classifier (however its Commission Error is also almost 100%). The 'Kappa Statistic' is an attempt to adjust the Percent Correct using information gained from the confusion matrix for that cover type.The NASS CDL Program is continuing efforts to reduce end-user burden, increase functionality, and take advantage of enhancements in computer technology.
PUBLIC RELEASE: The USDA, NASS Cropland Data Layer is considered public domain and free to redistribute. The official website is <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The data is available free for download through CropScape <http://nassgeodata.gmu.edu/CropScape/> and the Geospatial Data Gateway <http://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed download instructions. Please note that in no case are farmer reported data revealed or derivable from the public use Cropland Data Layer.
Process_Date: 2007
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 address
Address: 3251 Old Lee Highway, Rm 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_OD@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:
Indirect_Spatial_Reference: Florida
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Pixel
Row_Count: 24446

Column_Count: 24376


Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Planar:
Grid_Coordinate_System:
Grid_Coordinate_System_Name:
FOR GEOSPATIAL DATA GATEWAY USERS: Universal Transverse Mercator (UTM) Due to technical restrictions, the online data available free for download through the Geospatial Data Gateway <http://datagateway.nrcs.usda.gov/> can only be offered in UTM. However, the official Cropland Data Layer available at <http://nassgeodata.gmu.edu/CropScape/> includes the data in its native Albers Conical Equal Area coordinate system.

FOR CROPSCAPE USERS: Albers Conical Equal Area is the native projection used in the production of the Cropland Data Layer. The projection parameters for the Albers projection are as follows:
Map_Projection_Name: Albers Conical Equal Area
Albers_Conical_Equal_Area:
Standard_Parallel: 29.500000
Standard_Parallel: 45.500000
Longitude_of_Central_Meridian: -96.000000
Latitude_of_Projection_Origin: 23.000000
False_Easting: 0.000000
False_Northing: 0.000000
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 30
Ordinate_Resolution: 30
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257223563
Universal_Transverse_Mercator:
UTM_Zone_Number: 17 North
Transverse_Mercator:
Scale_Factor_at_Central_Meridian: 0.9996
Longitude_of_Central_Meridian: -81
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 annual NASS June Area Survey (JAS) and/or the annual Farm Service Agency's (FSA) Common Land Unit (CLU) data and non-agricultural training data from the United States Geological Survey (USGS) National Land Cover Database 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>.
 ***NOTE: The 1997-2013 CDLs were recoded and re-released in January 2014 to better represent pasture and grass-related categories. A new
 category named Grass/Pasture (code 176) collapses the following historical CDL categories: Pasture/Grass (code 62), Grassland Herbaceous
 (code 171), and Pasture/Hay (code 181). This was done to eliminate confusion among these similar land cover types which were not always
 classified definitionally consistent from state to state or year to year and frequently had poor classification accuracies. This follows
 the recoding of the entire CDL archive in January 2012 to better align the historical CDLs with the current product. For a detailed list
 of the category name and code changes, please visit the Frequently Asked Questions (FAQ's) section at <http://www.nass.usda.gov/research/Cropland/sarsfaqs2>.

 Data Dictionary: USDA, National Agricultural Statistics Service, 2004 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/Soybeans
          "27"       Rye
          "28"       Oats
          "29"       Millet
          "30"       Speltz
          "31"       Canola
          "32"       Flaxseed
          "33"       Safflower
          "34"       Rape Seed
          "35"       Mustard
          "36"       Alfalfa
          "37"       Other Hay/Non Alfalfa
          "38"       Camelina
          "39"       Buckwheat

 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"       Cucumbers
          "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
          "63"       Forest
          "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 Crops
          "72"       Citrus
          "74"       Pecans
          "75"       Almonds
          "76"       Walnuts
          "77"       Pears

 Raster
 Attribute Domain Values and Definitions: OTHER 81-109

 Categorization Code   Land Cover
          "81"       Clouds/No Data
          "82"       Developed
          "83"       Water
          "87"       Wetlands
          "88"       Nonag/Undefined
          "92"       Aquaculture

 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/Med Intensity
         "124"       Developed/High Intensity
         "131"       Barren
         "141"       Deciduous Forest
         "142"       Evergreen Forest
         "143"       Mixed Forest
         "152"       Shrubland
         "176"       Grass/Pasture
         "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
         "229"       Pumpkins
         "230"       Dbl Crop Lettuce/Durum Wht
         "231"       Dbl Crop Lettuce/Cantaloupe
         "232"       Dbl Crop Lettuce/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: 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:
Please visit the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> for distribution details. The Cropland Data Layer is available free for download at <http://nassgeodata.gmu.edu/CropScape/> and <http://datagateway.nrcs.usda.gov/>. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540.
Resource_Description: Cropland Data Layer - Florida 2004
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: Florida 2004
Format_Information_Content: GEOTIFF
Transfer_Size:
The image file size will vary depending on the state and completeness of coverage. 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/>. 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.
Fees:
Please visit the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> for distribution details. The Cropland Data Layer is available free for download at <http://nassgeodata.gmu.edu/CropScape/> and <http://datagateway.nrcs.usda.gov/>. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540.
Ordering_Instructions:
The CDL is available online and free for download from the Cropscape website <http://nassgeodata.gmu.edu/CropScape/>. 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'

Select a state from the dropdown menu

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.
Custom_Order_Process:
For a list of other states and years of available data please visit: <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The Cropland Data Layer is available free for download at <http://nassgeodata.gmu.edu/CropScape/> and <http://datagateway.nrcs.usda.gov/>. 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: 20120131
Metadata_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
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
Metadata_Access_Constraints: No restrictions on the distribution or use of the metadata file
Metadata_Use_Constraints: No restrictions on the distribution or use of the metadata file

Generated by mp version 2.9.12 on Fri Jan 27 20:45:12 2012