2011 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: 20120709
Title: 2011 California Cropland Data Layer | NASS/USDA
Edition:

2011 Edition (this updated version replaces the original published 20120131)

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.

***2011 California Cropland Data Layer specific information*** This version of the 2011 California CDL improves the identification of tomatoes. There was also an improved processing technique used to increase the amount of FSA training data. The original was published 20120131 and this new version was published 20120709.

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. The 2011 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, the Spanish DEIMOS-1 sensor, the British UK-DMC 2 sensor, and the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season.

Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from the USGS National Land Cover Database 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites.

Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. The NLCD 2006 is used as non-agricultural training and validation data.

Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery, ancillary data, and training/validation data used to generate this state's CDL.

The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.

Purpose:

The purpose of the Cropland Data Layer Program is to use satellite imagery to (1) provide acreage estimates to the Agricultural Statistics Board for the state's major commodities and (2) produce digital, crop-specific, categorized geo-referenced output products.

Supplemental_Information:

If the following table does not display properly, then please visit the following website to view the original metadata file <https://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php>.

USDA, National Agricultural Statistics Service 2011 California Cropland Data Layer

CLASSIFICATION INPUTS:
AWIFS DATE 20100915 PATH 249 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20100919 PATH 245 ROW(S)&QUADRANT(S) 45B

DEIMOS-1 DATE 20110405 PATH/ROW B61
DEIMOS-1 DATE 20110411 PATH/ROW B9C
DEIMOS-1 DATE 20110412 PATH/ROW BA6
DEIMOS-1 DATE 20110415 PATH/ROW BC5
DEIMOS-1 DATE 20110501 PATH/ROW C53
DEIMOS-1 DATE 20110504 PATH/ROW C64
DEIMOS-1 DATE 20110507 PATH/ROW C87
DEIMOS-1 DATE 20110520 PATH/ROW D4E
DEIMOS-1 DATE 20110520 PATH/ROW D4F
DEIMOS-1 DATE 20110523 PATH/ROW D77
DEIMOS-1 DATE 20110602 PATH/ROW DEC
DEIMOS-1 DATE 20110608 PATH/ROW E2D
DEIMOS-1 DATE 20110608 PATH/ROW E2E
DEIMOS-1 DATE 20110612 PATH/ROW E66
DEIMOS-1 DATE 20110615 PATH/ROW E96
DEIMOS-1 DATE 20110621 PATH/ROW EE6
DEIMOS-1 DATE 20110624 PATH/ROW F15
DEIMOS-1 DATE 20110701 PATH/ROW F7C
DEIMOS-1 DATE 20110704 PATH/ROW FA4
DEIMOS-1 DATE 20110707 PATH/ROW FD1
DEIMOS-1 DATE 20110710 PATH/ROW 000
DEIMOS-1 DATE 20110713 PATH/ROW 033
DEIMOS-1 DATE 20110716 PATH/ROW 05F
DEIMOS-1 DATE 20110720 PATH/ROW 097
DEIMOS-1 DATE 20110726 PATH/ROW 0E3
DEIMOS-1 DATE 20110801 PATH/ROW 14F
DEIMOS-1 DATE 20110918 PATH/ROW 47C

LANDSAT 5 TM DATE 20100924 PATH 043 ROW(S) 27-36
LANDSAT 5 TM DATE 20110513 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20110517 PATH 040 ROW(S) 26-30 33-36
LANDSAT 5 TM DATE 20110520 PATH 045 ROW(S) 26-34
LANDSAT 5 TM DATE 20110522 PATH 043 ROW(S) 28-36
LANDSAT 5 TM DATE 20110524 PATH 041 ROW(S) 30-37
LANDSAT 5 TM DATE 20110526 PATH 039 ROW(S) 30 33-38
LANDSAT 5 TM DATE 20110529 PATH 044 ROW(S) 26-28 31-35
LANDSAT 5 TM DATE 20110531 PATH 042 ROW(S) 26 29-36
LANDSAT 5 TM DATE 20110602 PATH 040 ROW(S) 28 31-37
LANDSAT 5 TM DATE 20110607 PATH 043 ROW(S) 28-36
LANDSAT 5 TM DATE 20110611 PATH 039 ROW(S) 26-38
LANDSAT 5 TM DATE 20110616 PATH 042 ROW(S) 29-36
LANDSAT 5 TM DATE 20110618 PATH 040 ROW(S) 26-28 31-37
LANDSAT 5 TM DATE 20110621 PATH 045 ROW(S) 26-34
LANDSAT 5 TM DATE 20110623 PATH 043 ROW(S) 26-36
LANDSAT 5 TM DATE 20110625 PATH 041 ROW(S) 26-37
LANDSAT 5 TM DATE 20110627 PATH 039 ROW(S) 26-38
LANDSAT 5 TM DATE 20110630 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20110702 PATH 042 ROW(S) 26-36
LANDSAT 5 TM DATE 20110711 PATH 041 ROW(S) 26-36
LANDSAT 5 TM DATE 20110716 PATH 044 ROW(S) 26 28-35
LANDSAT 5 TM DATE 20110718 PATH 042 ROW(S) 26-36
LANDSAT 5 TM DATE 20110720 PATH 040 ROW(S) 28-37
LANDSAT 5 TM DATE 20110725 PATH 043 ROW(S) 26-34
LANDSAT 5 TM DATE 20110729 PATH 039 ROW(S) 26-38
LANDSAT 5 TM DATE 20110801 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20110803 PATH 042 ROW(S) 30-36
LANDSAT 5 TM DATE 20110810 PATH 043 ROW(S) 26-36
LANDSAT 5 TM DATE 20110814 PATH 039 ROW(S) 26-37
LANDSAT 5 TM DATE 20110817 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20110819 PATH 042 ROW(S) 26-36
LANDSAT 5 TM DATE 20110830 PATH 039 ROW(S) 26-37
LANDSAT 5 TM DATE 20110904 PATH 042 ROW(S) 26-36
LANDSAT 5 TM DATE 20110915 PATH 039 ROW(S) 26-37
LANDSAT 5 TM DATE 20110918 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20110920 PATH 042 ROW(S) 26-36

USGS, NATIONAL ELEVATION DATASET
USGS, NATIONAL LAND COVER DATASET 2006 IMPERVIOUSNESS
USGS, NATIONAL LAND COVER DATASET 2001 TREE CANOPY

UK-DMC-2 DATE 20110521 PATH/ROW D80
UK-DMC-2 DATE 20110616 PATH/ROW E68
UK-DMC-2 DATE 20110717 PATH/ROW F86
UK-DMC-2 DATE 20110721 PATH/ROW FC0
UK-DMC-2 DATE 20110802 PATH/ROW 03A
UK-DMC-2 DATE 20110803 PATH/ROW 047
UK-DMC-2 DATE 20110818 PATH/ROW 0ED
UK-DMC-2 DATE 20110822 PATH/ROW 13E

TRAINING AND VALIDATION:
USDA, FARM SERVICE AGENCY 2011 COMMON LAND UNIT DATA
USGS, NATIONAL LAND COVER DATASET 2006
US BUREAU OF RECLAMATION, LOWER COLORADO RIVER ACCOUNTING SYSTEM 2011 CROP CLASSIFICATIONS

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: 20100925
Ending_Date: 20111230

Currentness_Reference: 2011 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: DEIMOS-1
Theme_Keyword: UK-DMC 2
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: 2011

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; ERDAS Imagine Versions 9.1, 9.2 and 9.3 <https://www.hexagongeospatial.com/>; ESRI ArcGIS Version 9.3 <https://www.esri.com/>; Rulequest See5.0 Release 2.07 <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:

***2011 California Cropland Data Layer specific information*** This new version of the 2011 California CDL improves the identification of grapes and vineyards, as well as improving the overall crop identification.

2011 California Cropland Data Layer
STATEWIDE AGRICULTURAL ACCURACY REPORT

Crop-specific covers only  *Correct  Accuracy   Error   Kappa
-------------------------   -------  --------  ------   -----
OVERALL ACCURACY**          2745701    79.33%  20.67%  0.7743


Cover                       ***Attribute  *Correct  Producer's  Omission            User's  Commission  Cond'l
Type                                Code    Pixels   Accuracy     Error   Kappa   Accuracy      Error    Kappa
----                                ----    ------   --------     -----   -----   --------      -----    -----
Corn                                   1    142001     87.29%    12.71%   0.871     86.34%     13.66%    0.861
Cotton                                 2    357961     98.42%     1.58%   0.984     94.67%      5.33%    0.945
Rice                                   3    470067     99.25%     0.75%   0.992     99.50%      0.50%    0.995
Sorghum                                4      2463     36.66%    63.34%   0.366     78.46%     21.54%    0.784
Soybeans                               5         0       n/a       n/a     n/a       0.00%    100.00%    0.000
Sunflower                              6     22492     82.65%    17.35%   0.826     90.22%      9.78%    0.902
Sweet Corn                            12      1879     32.09%    67.91%   0.321     79.42%     20.58%    0.794
Pop or Orn Corn                       13         0       n/a       n/a     n/a       0.00%    100.00%    0.000
Mint                                  14       714     64.32%    35.68%   0.643     98.08%      1.92%    0.981
Barley                                21     39750     72.24%    27.76%   0.721     81.01%     18.99%    0.809
Durum Wheat                           22     46472     77.43%    22.57%   0.773     91.94%      8.06%    0.919
Spring Wheat                          23     10321     77.66%    22.34%   0.776     81.35%     18.65%    0.813
Winter Wheat                          24    236323     78.88%    21.12%   0.782     79.43%     20.57%    0.788
Rye                                   27      5101     51.58%    48.42%   0.515     64.25%     35.75%    0.642
Oats                                  28     34909     49.09%    50.91%   0.488     65.03%     34.97%    0.648
Millet                                29         0       n/a       n/a     n/a       0.00%    100.00%    0.000
Safflower                             33     33807     78.08%    21.92%   0.780     91.72%      8.28%    0.917
Mustard                               35         0      0.00%   100.00%   0.000       n/a        n/a      n/a
Alfalfa                               36    534137     93.50%     6.50%   0.930     86.68%     13.32%    0.858
Other Hay/Non Alfalfa                 37     93350     67.42%    32.58%   0.669     63.98%     36.02%    0.634
Sugarbeets                            41     17894     89.19%    10.81%   0.892     83.61%     16.39%    0.836
Dry Beans                             42      5808     57.44%    42.56%   0.574     77.81%     22.19%    0.778
Potatoes                              43      7462     83.35%    16.65%   0.833     86.61%     13.39%    0.866
Other Crops                           44      1265     31.98%    68.02%   0.320     87.85%     12.15%    0.878
Sugarcane                             45         0      0.00%   100.00%   0.000       n/a        n/a      n/a
Sweet Potatoes                        46       329     55.57%    44.43%   0.556     96.20%      3.80%    0.962
Misc Vegs & Fruits                    47       381     22.16%    77.84%   0.222     31.51%     68.49%    0.315
Watermelons                           48      1476     48.14%    51.86%   0.481     45.19%     54.81%    0.452
Onions                                49     18942     79.03%    20.97%   0.790     88.63%     11.37%    0.886
Cucumbers                             50         0       n/a       n/a     n/a       0.00%    100.00%    0.000
Peas                                  53      1722     55.49%    44.51%   0.555     83.31%     16.69%    0.833
Tomatoes                              54    160322     93.49%     6.51%   0.934     90.63%      9.37%    0.905
Caneberries                           55         0      0.00%   100.00%   0.000       n/a        n/a      n/a
Herbs                                 57      1369     52.43%    47.57%   0.524     71.98%     28.02%    0.720
Clover/Wildflowers                    58     21211     87.65%    12.35%   0.876     67.51%     32.49%    0.674
Sod/Grass Seed                        59       804     34.85%    65.15%   0.348     79.53%     20.47%    0.795
Fallow/Idle Cropland                  61    193538     79.64%    20.36%   0.788     51.08%     48.92%    0.498
Cherries                              66      1266     29.18%    70.82%   0.292     69.41%     30.59%    0.694
Peaches                               67       561     22.56%    77.44%   0.225     62.54%     37.46%    0.625
Apples                                68       656     50.27%    49.73%   0.503     81.19%     18.81%    0.812
Grapes                                69     48168     84.07%    15.93%   0.840     86.63%     13.37%    0.865
Other Tree Crops                      71       675     57.69%    42.31%   0.577     88.82%     11.18%    0.888
Citrus                                72       756     41.65%    58.35%   0.416     66.73%     33.27%    0.667
Pecans                                74        30      4.89%    95.11%   0.049     50.00%     50.00%    0.500
Almonds                               75    190568     90.73%     9.27%   0.905     89.75%     10.25%    0.895
Walnuts                               76     39805     75.65%    24.35%   0.755     79.52%     20.48%    0.794
Pears                                 77      1041     73.36%    26.64%   0.734     79.83%     20.17%    0.798
Pistachios                           204     52558     84.57%    15.43%   0.845     92.14%      7.86%    0.921
Triticale                            205      6985     35.62%    64.38%   0.356     71.02%     28.98%    0.710
Carrots                              206      6626     55.45%    44.55%   0.554     72.63%     27.37%    0.726
Asparagus                            207       864     57.60%    42.40%   0.576     85.63%     14.37%    0.856
Garlic                               208      9569     85.84%    14.16%   0.858     90.68%      9.32%    0.907
Cantaloupes                          209      3771     60.01%    39.99%   0.600     65.48%     34.52%    0.655
Olives                               211     13459     72.33%    27.67%   0.723     84.92%     15.08%    0.849
Oranges                              212      8997     76.61%    23.39%   0.766     77.77%     22.23%    0.777
Honeydew Melons                      213       672     28.72%    71.28%   0.287     48.98%     51.02%    0.490
Broccoli                             214       296     15.01%    84.99%   0.150     35.71%     64.29%    0.357
Peppers                              216      1092     46.53%    53.47%   0.465     71.42%     28.58%    0.714
Pomegranates                         217     10635     80.04%    19.96%   0.800     86.93%     13.07%    0.869
Nectarines                           218       174     30.10%    69.90%   0.301     51.79%     48.21%    0.518
Greens                               219      3322     72.17%    27.83%   0.722     72.41%     27.59%    0.724
Plums                                220      3272     39.49%    60.51%   0.395     59.50%     40.50%    0.595
Strawberries                         221       303     46.90%    53.10%   0.469     30.98%     69.02%    0.310
Squash                               222         0      0.00%   100.00%   0.000      0.00%    100.00%    0.000
Apricots                             223        57     18.51%    81.49%   0.185     27.80%     72.20%    0.278
Vetch                                224       919     42.74%    57.26%   0.427     66.07%     33.93%    0.661
Dbl Crop WinWht/Corn                 225    108134     82.80%    17.20%   0.825     75.66%     24.34%    0.753
Dbl Crop Oats/Corn                   226     39159     75.25%    24.75%   0.751     67.15%     32.85%    0.670
Lettuce                              227      2230     33.67%    66.33%   0.336     55.05%     44.95%    0.550
Pumpkins                             229       191     30.37%    69.63%   0.304     92.72%      7.28%    0.927
Dbl Crop Lettuce/Durum Wht           230      1509     38.80%    61.20%   0.388     70.68%     29.32%    0.707
Dbl Crop Lettuce/Cantaloup           231       446     44.60%    55.40%   0.446     39.30%     60.70%    0.393
Dbl Crop Lettuce/Cotton              232       187     30.91%    69.09%   0.309     40.56%     59.44%    0.406
Dbl Crop Barley/Sorghum              235         0       n/a       n/a     n/a       0.00%    100.00%    0.000
Dbl Crop WinWht/Sorghum              236      5222     49.43%    50.57%   0.494     60.35%     39.65%    0.603
Dbl Crop Barley/Corn                 237         5      1.09%    98.91%   0.011      1.53%     98.47%    0.015
Dbl Crop WinWht/Cotton               238       327     15.68%    84.32%   0.157     73.15%     26.85%    0.731
Blueberries                          242        14     16.09%    83.91%   0.161     28.00%     72.00%    0.280
Cabbage                              243       187     42.31%    57.69%   0.423     50.95%     49.05%    0.510
Cauliflower                          244       249     62.72%    37.28%   0.627     78.55%     21.45%    0.785
Celery                               245         0      0.00%   100.00%   0.000      0.00%    100.00%    0.000
Turnips                              247         0       n/a       n/a     n/a       0.00%    100.00%    0.000
Cranberries                          250         0      0.00%   100.00%   0.000       n/a        n/a      n/a

*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 1-61,66-80 and 200-255).
FSA-sampled grass and pasture, aquaculture, and all NLCD-sampled categories (codes 62-65 and 81-199) are not included in
the Overall Accuracy.

The accuracy of the non-agricultural land cover classes within the Cropland Data Layer is entirely dependent upon the USGS, National Land Cover Database (NLCD 2006). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover. For more information on the accuracy of the NLCD please reference <https://www.mrlc.gov/>. ***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 2006). 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 2006 (NLCD 2006). More information about the FSA CLU Program can be found at <https://www.fsa.usda.gov/>. More information about the NLCD 2006 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. The DEIMOS-1 and DMC-UK 2 imagery used in the production of the Cropland Data Layer is orthorectified to a radial root mean square error (RMSE) of approximately 10 meters.

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: 2011
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 2011 CDL Program, the AWiFS imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used bilinear interpolation, rigorous transformation.

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: 20100925
Ending_Date: 20111230

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: Elecnor Deimos Imaging
Title: DEIMOS-1
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publisher: Astrium GEO Information Services
Publication_Place: Elecnor Deimos Imaging, Valladolid, Spain

Publication_Date: 2011
Other_Citation_Details:

The DEIMOS-1 satellite sensor operates in three spectral bands at a spatial resolution of 22 meters. Additional information about DEIMOS-1 data can be obtained at <https://www.deimos-imaging.com/>. Refer to the 'Supplemental Information' Section of this metadata file for specific scene date, path, row and quadrants used as classification inputs.

For the 2011 CDL Program, the DEIMOS-1 imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used cubic convolution, rigorous transformation.

Source_Scale_Denominator: 22 meter
Type_of_Source_Media: online download
Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20101001
Ending_Date: 20111231

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: Deimos-1
Source_Contribution: Raw data used in land cover spectral signature analysis

Source_Information:

Source_Citation:

Citation_Information:

Originator: DMC International Imaging
Title: UK-DMC 2
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publisher: Astrium GEO Information Services
Publication_Place: DMC International Imaging, Guildford, Surrey UK

Publication_Date: 2011
Other_Citation_Details:

The UK-DMC 2 satellite sensor operates in three spectral bands at a spatial resolution of 22 meters. Additional information about UK-DMC 2 data can be obtained at <http://www.dmcii.com/>. Refer to the 'Supplemental Information' Section of this metadata file for specific scene date, path, row and quadrants used as classification inputs.

For the 2011 CDL Program, the UK-DMC 2 imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used cubic convolution, rigorous transformation.

Source_Scale_Denominator: 22 meter
Type_of_Source_Media: online download
Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20101001
Ending_Date: 20111231

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: UK-DMC2
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: 2011
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: 20101001
Ending_Date: 20111230

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: 2011
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: 20101001
Ending_Date: 20110930

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: 2009
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 2006)
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 2006 was used as ground training and validation for non-agricultural categories. Additionally, the USGS NLCD 2006 Imperviousness and NLCD 2001 Tree Canopy layers were used as ancillary data sources in the Cropland Data Layer classification process. More information on the NLCD 2006 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. Preferred NLCD2006 citation: "Fry, J., Xian, G., Jin, S., Dewitz, J., Homer, C., Yang, L., Barnes, C., Herold, N., and Wickham, J., 2011. Completion of the 2006 National Land Cover Database for the Conterminous United States, PE&RS, Vol. 77(9):858-864."

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: 2011
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 Interior, Bureau of Reclamation, Lower Colorado Region

Title:

Lower Colorado River Water Accounting System (LCRAS) GIS data layer

Geospatial_Data_Presentation_Form: vector digital data
Publication_Information:

Publisher:

United States Department of Interior, Bureau of Reclamation, Lower Colorado Region

Publication_Place: Boulder City, NV 89006-1470, USA

Publication_Date: 2011
Other_Citation_Details:

The Lower Colorado River Water Accounting System (LCRAS) GIS data layer contains an annually updated record of crop types that was used to supplement the training and validation of the Cropland Data Layer. The area covered is Southern California and Southwest Arizona. For more details please reference the Bureau of Reclamation website <https://www.usbr.gov/lc/>.

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: BLM LCRAS GIS Data Layer
Source_Contribution:

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

Process_Step:

Process_Description:

OVERVIEW: The United States Department of Agriculture (USDA), National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) Program is a unique agricultural-specific land cover geospatial product that is reproduced annually in participating states. The CDL Program builds upon NASS' traditional crop acreage estimation program and integrates Farm Service Agency (FSA) grower-reported field data with satellite imagery to create an unbiased statistical estimator of crop area at the state and county level for internal use. It is important to note that the internal acreage estimates produced using the CDL are not simple pixel counting. It is more of an 'Adjusted Census by Satellite.'

SOFTWARE: ERDAS Imagine is used in the pre- and post- processing of all raster-based data. ESRI ArcGIS is used to prepare the vector-based training and validation data. Rulequest See5.0 is used to create a decision tree based classifier. The NLCD Mapping Tool is used to apply the See5.0 decision-tree via ERDAS Imagine.

DECISION TREE CLASSIFIER: This Cropland Data Layer used the decision tree classifier approach. Using a decision tree classifier is a departure from older versions of the CDL which were created using in-house software (Peditor) based upon a maximum likelihood classifier approach. Check the 'Process Description' section of the specific state and year metadata file to verify the methodology used. Decision trees offer several advantages over the more traditional maximum likelihood classification method. The advantages include being: 1) non-parametric by nature and thus not reliant on the assumption of the input data being normally distributed, 2) efficient to construct and thus capable of handling large and complex data sets, 3) able to incorporate missing and non-continuous data, and 4) able to sort out non-linear relationships.

GROUND TRUTH: As with the maximum likelihood method, decision tree analysis is a supervised classification technique. Thus, it relies on having a sample of known ground truth areas in which to train the classifier. Older versions of the CDL (prior to 2006) utilized ground truth data from the annual June Agricultural Survey (JAS). Beginning in 2006, the CDL utilizes the very comprehensive ground truth data provided from the FSA Common Land Unit (CLU) Program as a replacement for the JAS data. The FSA CLU data have the advantage of natively being in a GIS and containing magnitudes more of field level information. Disadvantages include that it is not truly a probability sample of land cover and has bias toward subsidized program crops. Additional information about the FSA data can be found at <https://www.fsa.usda.gov/>.

INPUTS: The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, and the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. For the 2011 CDL Program, the AWiFS imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used bilinear interpolation, rigorous transformation. 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 2006 (NLCD 2006), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery and ancillary data used to generate this state's CDL.

ACCURACY: The accuracy of the land cover classifications are evaluated using independent validations data sets generated from the FSA CLU data (agricultural categories) and the NLCD 2006 (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: 2012
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 2006 (NLCD 2006). 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:

 ***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, 2011 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

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: 855-493-0447
Contact_Electronic_Mail_Address: SM.NASS.RDD.GIB@usda.gov
Contact_Instructions:

Please visit the official website <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php> for distribution details. The Cropland Data Layer is available free for download at <https://nassgeodata.gmu.edu/CropScape/> and <https://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 - California 2011
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 (SM.NASS.RDD.GIB@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 <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>.

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information:

Format_Name: GEOTIFF
Format_Version_Date: 2011
Format_Information_Content: GEOTIFF

Digital_Transfer_Option:

Online_Option:

Computer_Contact_Information:

Network_Address:

Network_Resource_Name: <https://nassgeodata.gmu.edu/CropScape/>

Access_Instructions:

The CDL is available online and free for download from the Cropscape website <https://nassgeodata.gmu.edu/CropScape/>. It is also available free for download from the Geospatial Data Gateway website <https://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed Geospatial Data Gateway download instructions.

Fees:

Ordering_Instructions:

The CDL is available online and free for download from the Cropscape website <https://nassgeodata.gmu.edu/CropScape/>. The Cropland Data Layer is also available free for download from the NRCS Geospatial Data Gateway at <https://datagateway.nrcs.usda.gov/>. If you experience problems downloading all years of CDL data through the Geospatial Data Gateway then you can try to use the 'Direct Data Download' link in the lower right-hand corner of their webpage.

Custom_Order_Process:

For a list of other states and years of available data please visit: <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>. The Cropland Data Layer is available free for download at <https://nassgeodata.gmu.edu/CropScape/> and <https://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 a GEOTIF (.tif) file format then we suggest using the Cropscape website <https://nassgeodata.gmu.edu/CropScape/> or using the freeware browser ESRI ArcGIS Explorer <https://www.esri.com/>.

Metadata_Reference_Information:

Metadata_Date: 20120709
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:

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

2011 California Cropland Data Layer | NASS/USDA

Metadata: