2007 California Cropland Data Layer

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: 20080701
Title: 2007 California Cropland Data Layer | NASS/USDA
Edition: 2007 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 <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>. The data is available free for download through CropScape at <https://nassgeodata.gmu.edu/CropScape/>. The data is also available free for download through the Geospatial Data Gateway at <https://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed Geospatial Data Gateway download instructions.

Online_Linkage: <https://nassgeodata.gmu.edu/CropScape/CA>

Description:

Abstract:

The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer with a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Ancillary classification inputs 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 are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. For the 2007 California CDL additional agricultural training data was derived from the USDA, NASS June Area Survey (JAS). The NLCD 2001 is used as non-agricultural training and validation data. 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.

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 <https://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php> to view the original metadata file.

USDA, National Agricultural Statistics Service, 2007 California Cropland Data Layer

CLASSIFICATION INPUTS:
LANDSAT TM DATE 20070413 PATH 39 ROW(S) 35-37
LANDSAT TM DATE 20070416 PATH 44 ROW(S) 31-35
LANDSAT TM DATE 20070423 PATH 45 ROW(S) 31-33
LANDSAT TM DATE 20070427 PATH 41 ROW(S) 34-37
LANDSAT TM DATE 20070430 PATH 46 ROW(S) 31-32
LANDSAT TM DATE 20070506 PATH 40 ROW(S) 35-37
LANDSAT TM DATE 20070508 PATH 38 ROW(S) 36-37
LANDSAT TM DATE 20070511 PATH 43 ROW(S) 32-35
LANDSAT TM DATE 20070617 PATH 46 ROW(S) 31-32
LANDSAT TM DATE 20070621 PATH 42 ROW(S) 33-36
LANDSAT TM DATE 20070626 PATH 45 ROW(S) 31-33
LANDSAT TM DATE 20070630 PATH 41 ROW(S) 34-37
LANDSAT TM DATE 20070707 PATH 42 ROW(S) 33-36
LANDSAT TM DATE 20070709 PATH 40 ROW(S) 35-37
LANDSAT TM DATE 20070711 PATH 38 ROW(S) 36-37
LANDSAT TM DATE 20070718 PATH 39 ROW(S) 35-37
LANDSAT TM DATE 20070721 PATH 44 ROW(S) 31-35
LANDSAT TM DATE 20070728 PATH 45 ROW(S) 31-33
LANDSAT TM DATE 20070730 PATH 43 ROW(S) 32-35
LANDSAT TM DATE 20070808 PATH 42 ROW(S) 33-36
LANDSAT TM DATE 20070810 PATH 40 ROW(S) 35-37
LANDSAT TM DATE 20070812 PATH 38 ROW(S) 36-37
LANDSAT TM DATE 20070813 PATH 45 ROW(S) 31-33
LANDSAT TM DATE 20070815 PATH 43 ROW(S) 32-36
LANDSAT TM DATE 20070817 PATH 41 ROW(S) 34-37
LANDSAT TM DATE 20070822 PATH 44 ROW(S) 31-35
LANDSAT TM DATE 20070904 PATH 39 ROW(S) 35-37
LANDSAT TM DATE 20070905 PATH 46 ROW(S) 31-32
LANDSAT TM DATE 20070913 PATH 38 ROW(S) 36-37

AWIFS DATE 20070401 PATH 246 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20070519 PATH 246 ROW(S)&QUADRANT(S) 40D 45BD
AWIFS DATE 20070520 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070523 PATH 242 ROW(S)&QUADRANT(S) 40B
AWIFS DATE 20070528 PATH 243 ROW(S)&QUADRANT(S) 40D
AWIFS DATE 20070612 PATH 246 ROW(S)&QUADRANT(S) 40D 45BD
AWIFS DATE 20070613 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070626 PATH 244 ROW(S)&QUADRANT(S) 40D
AWIFS DATE 20070710 PATH 242 ROW(S)&QUADRANT(S) 40BD
AWIFS DATE 20070803 PATH 242 ROW(S)&QUADRANT(S) 40BD
AWIFS DATE 20070823 PATH 246 ROW(S)&QUADRANT(S) 40D 45B
AWIFS DATE 20070824 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070827 PATH 242 ROW(S)&QUADRANT(S) 40BD
AWIFS DATE 20070901 PATH 243 ROW(S)&QUADRANT(S) 40D
AWIFS DATE 20070916 PATH 246 ROW(S)&QUADRANT(S) 40BD 45BD
AWIFS DATE 20070920 PATH 242 ROW(S)&QUADRANT(S) 40B

MODIS 16 DAY NDVI COMPOSITE DATE 20061016
MODIS 16 DAY NDVI COMPOSITE DATE 20070202
MODIS 16 DAY NDVI COMPOSITE DATE 20070306

CALIFORNIA DEPARTMENT OF CONSERVATION, 2004 FARMLAND MAPPING AND MONITORING PROGRAM
USGS, NATIONAL ELEVATION DATASET ELEVATION
USGS, NATIONAL LAND COVER DATABASE 2001 TREE CANOPY
USGS, NATIONAL LAND COVER DATABASE 2001 IMPERVIOUSNESS

TRAINING AND VALIDATION:
USDA, FARM SERVICE AGENCY 2007 COMMON LAND UNITS
USDA, NASS 2007 JUNE AREA SURVEY
USGS, NATIONAL LAND COVER DATABASE 2001

NOTE: The final extent of the CDL is clipped to the state boundary
even though the raw input may encompass a larger area.

Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20070930
Ending_Date: 20071230

Currentness_Reference: 2007 growing season

Status:

Progress: Complete
Maintenance_and_Update_Frequency: None planned

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -124.5876
East_Bounding_Coordinate: -114.1885
North_Bounding_Coordinate: 41.9743
South_Bounding_Coordinate: 32.5028

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: farming
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 > California

Place:

Place_Keyword_Thesaurus: None
Place_Keyword: California
Place_Keyword: CA

Temporal:

Temporal_Keyword_Thesaurus: None
Temporal_Keyword: 2007

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 <https://nassgeodata.gmu.edu/CropScape/> or the freeware browser ESRI ArcGIS Explorer <https://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: 1400 Independence Avenue, SW, Room 5029 South Building
City: Washington
State_or_Province: District of Columbia
Postal_Code: 20250-2001
Country: USA

Contact_Voice_Telephone: 800-727-9540
Contact_Facsimile_Telephone: 855-493-0447
Contact_Electronic_Mail_Address: SM.NASS.RDD.GIB@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:

Microsoft Windows XP; Leica Geosystems ERDAS Imagine 9.1 <http://gi.leica-geosystems.com/>; ESRI ArcGIS Version 9.1 and 9.2 with Service Pack 3 <https://www.esri.com/>; Rulequest See5.0 Release 2.04 <http://www.rulequest.com/>; NLCD Mapping Tool <https://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 <https://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php> to view the original metadata file.

USDA, National Agricultural Statistics Service, 2007 California Cropland Data Layer
STATEWIDE AGRICULTURAL ACCURACY REPORT

Crop-specific covers only  *Correct  Accuracy   Error   Kappa
-------------------------   -------  --------   -----   -----
OVERALL ACCURACY             760028    97.22%   2.78%  0.9666


Cover           ***Attribute  *Correct  Producer's  Omission            User's  Commission  Cond'l
Type                    Code    Pixels   Accuracy     Error    Kappa  Accuracy      Error    Kappa
----                    ----    ------   --------     -----    -----  --------      -----    -----
Corn                       1     51891     98.79%     1.21%   0.9877    97.60%      2.40%   0.9757
Cotton                     2     11601     98.78%     1.22%   0.9878    97.75%      2.25%   0.9774
Rice                       3    216403     99.87%     0.13%   0.9986    99.27%      0.73%   0.9922
Sorghum                    4       884     97.36%     2.64%   0.9736    98.77%      1.23%   0.9877
Sunflowers                 6      1124     93.28%     6.72%   0.9328    97.48%      2.52%   0.9748
Sweet Corn                12       217    100.00%     0.00%   1.0000    99.09%      0.91%   0.9909
Pop. or Orn. Corn         13        66     91.67%     8.33%   0.9167   100.00%      0.00%   1.0000
Barley                    21     12981     95.20%     4.80%   0.9518    94.22%      5.78%   0.9420
Durum Wheat               22     12967     98.90%     1.10%   0.9890    99.43%      0.57%   0.9943
Spring Wheat              23      4546     98.44%     1.56%   0.9844    96.33%      3.67%   0.9633
Winter Wheat              24     86324     98.44%     1.56%   0.9839    95.73%      4.27%   0.9562
Rye                       27      4996     93.00%     7.00%   0.9299    95.00%      5.00%   0.9499
Oats                      28     16493     92.81%     7.19%   0.9277    91.48%      8.52%   0.9143
Canola                    31        36     94.74%     5.26%   0.9474   100.00%      0.00%   1.0000
Safflower                 33     10510     97.66%     2.34%   0.9765    97.05%      2.95%   0.9704
Alfalfa                   36    185772     99.35%     0.65%   0.9931    96.91%      3.09%   0.9672
Other Hays                37      3286     94.13%     5.87%   0.9412    96.70%      3.30%   0.9670
Sugarbeets                41       996     97.84%     2.16%   0.9784    99.60%      0.40%   0.9960
Dry Beans                 42      1073     94.45%     5.55%   0.9445    97.99%      2.01%   0.9799
Potatoes                  43        19     95.00%     5.00%   0.9500   100.00%      0.00%   1.0000
Sugarcane                 45        22     64.71%    35.29%   0.6471   100.00%      0.00%   1.0000
Sweet Potatoes            46        28     90.32%     9.68%   0.9032    93.33%      6.67%   0.9333
Misc. Vegs. & Fruits      47       374     91.89%     8.11%   0.9189    90.34%      9.66%   0.9034
Watermelon                48        40     85.11%    14.89%   0.8511    97.56%      2.44%   0.9756
Onions                    49       177     96.72%     3.28%   0.9672    97.25%      2.75%   0.9725
Peas                      53       386     95.54%     4.46%   0.9554    99.23%      0.77%   0.9923
Herbs                     57      1870     98.99%     1.01%   0.9899    97.19%      2.81%   0.9719
Clover/Wildflowers        58      7359     94.50%     5.50%   0.9449    88.95%     11.05%   0.8893
Seed/Sod Grass            59      2374     85.30%    14.70%   0.8529    98.92%      1.08%   0.9892
Fallow/Idle Cropland      61     87836     88.45%    11.55%   0.8812    95.74%      4.26%   0.9561
Peaches                   67       448     73.81%    26.19%   0.7380    96.34%      3.66%   0.9634
Apples                    68        66     82.50%    17.50%   0.8250    89.19%     10.81%   0.8919
Grapes                    69     13572     96.83%     3.17%   0.9681    94.64%      5.36%   0.9462
Christmas Trees           70        12     70.59%    29.41%   0.7059    85.71%     14.29%   0.8571
Other Tree Nuts***        71       134     95.71%     4.29%   0.9571    93.06%      6.94%   0.9306
Citrus                    72       119     77.27%    22.73%   0.7727    85.61%     14.39%   0.8561
Other Tree Fruits***      73       279     85.85%    14.15%   0.8584    95.22%      4.78%   0.9522
Aquaculture               92        28    100.00%     0.00%   1.0000    87.50%     12.50%   0.8750
Almonds                  201     33705     96.89%     3.11%   0.9685    96.19%      3.81%   0.9615
Tomatoes                 202      3167     96.64%     3.36%   0.9664    96.88%      3.12%   0.9688
Walnuts                  203     15579     95.88%     4.12%   0.9586    93.95%      6.05%   0.9392
Pistachios               204      6117     96.86%     3.14%   0.9686    96.80%      3.20%   0.9680
Triticale                205      3837     90.54%     9.46%   0.9053    96.19%      3.81%   0.9618
Carrots                  206       454     99.13%     0.87%   0.9913    98.91%      1.09%   0.9891
Asparagus                207        93     92.08%     7.92%   0.9208    94.90%      5.10%   0.9490
Garlic                   208        94     84.68%    15.32%   0.8468    93.07%      6.93%   0.9307
Cantaloupe               209       369     97.62%     2.38%   0.9762    96.85%      3.15%   0.9685
Prunes                   210      4362     93.95%     6.05%   0.9394    93.36%      6.64%   0.9336
Olives                   211      2718     93.95%     6.05%   0.9395    90.39%      9.61%   0.9038
Oranges                  212       374     89.90%    10.10%   0.8990    84.04%     15.96%   0.8404
Honeydew Melon           213       180     93.75%     6.25%   0.9375    97.83%      2.17%   0.9783
Broccoli                 214        29    100.00%     0.00%   1.0000    87.88%     12.12%   0.8788
Cherry Orchards          215       696     82.96%    17.04%   0.8295    97.07%      2.93%   0.9707
Peppers                  216        63     70.79%    29.21%   0.7079    92.65%      7.35%   0.9265
Pomegranates             217       366     97.08%     2.92%   0.9708    98.39%      1.61%   0.9839
Nectarine                218       166     72.17%    27.83%   0.7217    93.26%      6.74%   0.9326
Greens                   219       119     92.97%     7.03%   0.9297    91.54%      8.46%   0.9154
Plums                    220       158     80.61%    19.39%   0.8061    91.86%      8.14%   0.9186
Strawberries             221       251     88.07%    11.93%   0.8807    81.49%     18.51%   0.8149
Squash                   222        22     95.65%     4.35%   0.9565   100.00%      0.00%   1.0000
Apricots                 223       182     72.22%    27.78%   0.7222    95.79%      4.21%   0.9579
Vetch                    224       279     79.49%    20.51%   0.7949    94.58%      5.42%   0.9458
Dbl. Crop WinWht/Corn    225      1384     90.40%     9.60%   0.9039    96.85%      3.15%   0.9685
Dbl. Crop Oats/Corn      226       406     88.65%    11.35%   0.8864    96.21%      3.79%   0.9621

*NOTE: Correct Pixels represents the total number of independent validation pixels correctly identified in the error matrix.
**NOTE: 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.

***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 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 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 Database 2001 (NLCD 2001). More information about the FSA CLU Program can be found at <https://www.fsa.usda.gov/>. More information about the NLCD 2001 can be found at <https://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 <https://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)

Title: RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS)
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publisher: EOTec (Earth Observation Technologies, LLC)
Publication_Place: Washington, D.C. 20008

Publication_Date: 2007
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 <https://data.gov.in/>. 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 2007 CDL Program, for CDLs produced at a 30 meter spatial resolution 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: 20070925
Ending_Date: 20071230

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: AWiFS
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)

Title:

Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+)

Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publisher: USGS, EROS
Publication_Place: Sioux Falls, South Dakota 57198-001

Publication_Date: 2007
Other_Citation_Details:

The Landsat 5 TM and Landsat 7 ETM+ data is free for download through the following website <https://glovis.usgs.gov/>. Additional information about Landsat data can be obtained at <https://www.usgs.gov/centers/eros>. 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: 20071001
Ending_Date: 20071230

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: Landsat
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)

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:

Publisher: USGS Center for Earth Resources Observation and Sciences (EROS)
Publication_Place: Sioux Falls, South Dakota 57198 USA

Publication_Date: 2007
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: 20071001
Ending_Date: 20070930

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: MODIS
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

Title: The National Elevation Dataset (NED)
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publisher: USGS, EROS Data Center
Publication_Place: Sioux Falls, South Dakota 57198 USA

Publication_Date: 2007
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 <https://www.usgs.gov/core-science-systems/national-geospatial-program/national-map>. 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_Citation_Abbreviation: NED
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

Title: National Land Cover Database 2001 (NLCD 2001)
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publisher: USGS, EROS Data Center
Publication_Place: Sioux Falls, South Dakota 57198 USA

Publication_Date: 2006
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 <https://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_Citation_Abbreviation: NLCD
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)

Title: USDA, FSA Common Land Unit (CLU)
Geospatial_Data_Presentation_Form: vector digital data
Publication_Information:

Publisher: USDA, FSA Aerial Photography Field Office

Publication_Place: Salt Lake City, Utah 84119-2020 USA

Publication_Date: 2007
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 <https://www.fsa.usda.gov/>.

Source_Scale_Denominator: 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_Citation_Abbreviation: FSA CLU
Source_Contribution:

spatial and attribute information used in the spectral signature training and validation of agricultural land cover

Source_Information:

Source_Citation:

Citation_Information:

Originator:

United States Department of Agriculture (USDA), National Agricultural Statistics Service (NASS)

Title: June Area Survey (JAS)
Geospatial_Data_Presentation_Form: paper-based data
Publication_Information:

Publisher: unpublished material

Publication_Place: Washington, D.C. USA

Publication_Date: 2007
Other_Citation_Details:

The survey data collected in the USDA, NASS June Area Survey is confidential and strictly limited to USDA, NASS personnel. For more information about the JAS visit the following website: <https://www.nass.usda.gov/Surveys/June_Area/>.

Source_Scale_Denominator: 4800
Type_of_Source_Media: paper-based
Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 2007

Source_Currentness_Reference: ground condition, updated annually

Source_Citation_Abbreviation: USDA NASS JAS
Source_Contribution:

spatial and attribute information used in the spectral signature training and validation of agricultural land cover

Source_Information:

Source_Citation:

Citation_Information:

Originator:

California Department of Conservation, Division of Land Resource Protection

Title: Farmland Mapping and Monitoring Program (FMMP)
Geospatial_Data_Presentation_Form: vector digital data
Publication_Information:

Publisher:

California Department of Conservation, Division of Land Resource Protection

Publication_Place: Sacramento, California 95814-3528 USA

Publication_Date: 2004
Other_Citation_Details:

The Farmland Mapping and Monitoring Program (FMMP) is a biennial vector digital dataset designed to provide decision makers with a geospatial component for the state's agricultural resources. The 2004 FMMP data was used as an ancillary layer in the decision-tree classifier. Additional information about the FMMP can be found at <http://www.conservation.ca.gov/>.

Source_Scale_Denominator: 24000
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 biennially on even numbered years

Source_Citation_Abbreviation:

California Department of Conservation, Farmland Mapping and Monitoring Program (FMMP)

Source_Contribution:

spatial and attribute information used in the spectral signature training and validation of agricultural land cover

Process_Step:

Process_Description:

SPECIAL PROCESSING NOTES FOR THE 2007 CALIFORNIA CROPLAND DATA LAYER: The processing steps outlined in the following 'Process Description' Section of this metadata file apply to most CDL projects. However, the 2007 California CDL used slightly different processing techniques. Firstly, the 30 meter version used Landsat 5 TM satellite imagery in addition to AWiFS imagery. See the 'Supplemental Information' Section of this metadata file for a full list of inputs. Secondly, additional ground data from the USDA, NASS 2007 June Area Survey (JAS) was used as training and validation in addition to the Farm Service Agency Common Land Unit Program data. For more information about the JAS visit the following website: <https://www.nass.usda.gov/Surveys/June_Area/>. Thirdly, in order to better manage the large amount of input imagery, the state was split into three Analysis Districts (AD) for processing. The North AD was defined by the extents of Landsat paths 45 thru 46, the Central AD was defined by Landsat paths 42 thru 44, and the South AD was defined by Landsat paths 38 thru 41. The three ADs were mosaiced together for the public release. Fourthly, a minimum mapping unit (mmu) was applied to a subset of categories. A MMU of 1 pixel (approximately 0.25 acre) was applied to the following CDL categories: 12, 13, 43, 48, 47, 49, 57, 206, 207, 208, 209, 213, 214, 216, 219, 221, 222, 224; and a MMU of 4 pixels (approximately 1 acre) was applied to the following CDL categories: 67, 68, 69, 70, 71, 72, 73, 201, 203, 204, 210, 211, 212, 215, 217, 218, 220, 223.

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: Leica Geosystems 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 <https://www.fsa.usda.gov/>.

INPUTS: The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. NASS acquires AWiFS imagery for CDL production states from April 1 through September 30 of the current growing season through a cooperative agreement with the USDA, Foreign Agricultural Service (FAS), International Production Assessment (IPA) unit. Ancillary inputs 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.

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.

PUBLIC RELEASE: The USDA, NASS Cropland Data Layer is considered public domain and free to redistribute. The official website is <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>. The data is available free for download through CropScape <https://nassgeodata.gmu.edu/CropScape/> and the Geospatial Data Gateway <https://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:

Contact_Voice_Telephone: 800-727-9540
Contact_Facsimile_Telephone: 855-493-0447
Contact_Electronic_Mail_Address: SM.NASS.RDD.GIB@usda.gov

Cloud_Cover: 0

Spatial_Data_Organization_Information:

Indirect_Spatial_Reference: California
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:

Raster_Object_Type: Pixel
Row_Count: 35841

Column_Count: 29767

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Map_Projection:

Map_Projection_Name:

Albers Conical Equal Area as used by mrlc.gov (NLCD)

FOR GEOSPATIAL DATA GATEWAY USERS: Universal Transverse Mercator (UTM), Spheriod WGS84, Datum WGS84. Due to technical restrictions, the online data available free for download through the Geospatial Data Gateway <https://datagateway.nrcs.usda.gov/> can only be offered in UTM. The UTM Zones are as follows: Zone 11 - California, Idaho, Nevada, Oregon, Washington; Zone 12 - Arizona, Montana, Utah; Zone 13 - Colorado, New Mexico, Wyoming; Zone 14 - Kansas, North Dakota, Nebraska, Oklahoma, South Dakota, Texas; Zone 15 - Arkansas, Iowa, Louisiana, Minnesota, Missouri; Zone 16 - Alabama, Illinois, Indiana, Kentucky, Michigan, Mississippi, Tennessee; Zone 17 - Florida, Georgia, North Carolina, Ohio, South Carolina, Virginia, West Virginia; Zone 18 - Connecticut, Delaware, Maryland, New Jersey, New York, Pennsylvania, Vermont; Zone 19 - Maine, Massachusetts, New Hampshire, Rhode Island. However, the official Cropland Data Layer available at <https://nassgeodata.gmu.edu/CropScape/> includes the data in its native Albers Conical Equal Area coordinate system.

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: 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 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 <https://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php>.

 ***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 <https://www.nass.usda.gov/Research_and_Science/Cropland/sarsfaqs2.php>.


 Data Dictionary: USDA, National Agricultural Statistics Service, 2007 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
         "215"       Avocados
         "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

2007 California Cropland Data Layer | NASS/USDA

Metadata: