2010 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: 20110110
Title: 2010 California Cropland Data Layer | NASS/USDA
Edition: 2010 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. The 2010 CDL has a ground resolution of 30 meters. The CDL is produced using satellite imagery from the Landsat 5 TM sensor, Landsat 7 ETM+ sensor, and the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season.

Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the imperviousness and canopy data layers from 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. The NLCD 2001 is used as non-agricultural training and validation data.

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

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

Purpose:

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

Supplemental_Information:

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

USDA, National Agricultural Statistics Service, 2010 California Cropland Data Layer

CLASSIFICATION INPUTS:
AWIFS DATE 20100423 PATH 244 ROW(S)&QUADRANT(S) 35BD 40BD 45B
AWIFS DATE 20100424 PATH 249 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20100429 PATH 250 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20100503 PATH 246 ROW(S)&QUADRANT(S) 45B
AWIFS DATE 20100610 PATH 244 ROW(S)&QUADRANT(S) 45B
AWIFS DATE 20100615 PATH 245 ROW(S)&QUADRANT(S) 40CD 45AB
AWIFS DATE 20100616 PATH 250 ROW(S)&QUADRANT(S) 40C 45CD
AWIFS DATE 20100617 PATH 255 ROW(S)&QUADRANT(S) 45ABCD
AWIFS DATE 20100620 PATH 246 ROW(S)&QUADRANT(S) 45B
AWIFS DATE 20100621 PATH 251 ROW(S)&QUADRANT(S) 45AB
AWIFS DATE 20100625 PATH 247 ROW(S)&QUADRANT(S) 40C
AWIFS DATE 20100626 PATH 252 ROW(S)&QUADRANT(S) 35ABC 40ABCD 45ABCD
AWIFS DATE 20100705 PATH 249 ROW(S)&QUADRANT(S) 36C 41A 45BD
AWIFS DATE 20100714 PATH 246 ROW(S)&QUADRANT(S) 35B 40B 45B
AWIFS DATE 20100728 PATH 244 ROW(S)&QUADRANT(S) 35B 40BD 45B
AWIFS DATE 20100729 PATH 249 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20100802 PATH 245 ROW(S)&QUADRANT(S) 40D 45B
AWIFS DATE 20100803 PATH 250 ROW(S)&QUADRANT(S) 35D 40BD 45D
AWIFS DATE 20100807 PATH 246 ROW(S)&QUADRANT(S) 35D 40B 45B
AWIFS DATE 20100821 PATH 244 ROW(S)&QUADRANT(S) 35D 40BD
AWIFS DATE 20100822 PATH 249 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20100914 PATH 244 ROW(S)&QUADRANT(S) 35BD 40BD 45B
AWIFS DATE 20100919 PATH 245 ROW(S)&QUADRANT(S) 45B

LANDSAT 5 TM DATE 20100421 PATH 039 ROW(S) 26-30 34-38
LANDSAT 5 TM DATE 20100507 PATH 039 ROW(S) 28-38
LANDSAT 5 TM DATE 20100512 PATH 042 ROW(S) 26-36
LANDSAT 5 TM DATE 20100530 PATH 040 ROW(S) 26-37
LANDSAT 5 TM DATE 20100608 PATH 039 ROW(S) 27-38
LANDSAT 5 TM DATE 20100611 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20100620 PATH 043 ROW(S) 26 31-36
LANDSAT 5 TM DATE 20100622 PATH 041 ROW(S) 26-37
LANDSAT 5 TM DATE 20100624 PATH 039 ROW(S) 26-38
LANDSAT 5 TM DATE 20100627 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20100701 PATH 040 ROW(S) 26-37
LANDSAT 5 TM DATE 20100710 PATH 039 ROW(S) 26-37
LANDSAT 5 TM DATE 20100715 PATH 042 ROW(S) 26-36
LANDSAT 5 TM DATE 20100717 PATH 040 ROW(S) 26-37
LANDSAT 5 TM DATE 20100719 PATH 038 ROW(S) 27-38
LANDSAT 5 TM DATE 20100729 PATH 044 ROW(S) 26-35
LANDSAT 5 TM DATE 20100811 PATH 039 ROW(S) 26-38
LANDSAT 5 TM DATE 20100823 PATH 043 ROW(S) 26-36
LANDSAT 5 TM DATE 20100827 PATH 039 ROW(S) 26-38
LANDSAT 5 TM DATE 20100830 PATH 044 ROW(S) 26-27 29 32-35
LANDSAT 5 TM DATE 20100901 PATH 042 ROW(S) 26 30-36
LANDSAT 5 TM DATE 20100910 PATH 041 ROW(S) 26 30-37
LANDSAT 5 TM DATE 20100912 PATH 039 ROW(S) 26-38

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 2010 COMMON LAND UNIT DATA
USGS, NATIONAL LAND COVER DATABASE 2001

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

Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20090925
Ending_Date: 20101230

Currentness_Reference: 2010 growing season

Status:

Progress: Complete
Maintenance_and_Update_Frequency: None planned

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -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: 2010

Access_Constraints: None
Use_Constraints:

The USDA, NASS Cropland Data Layer is provided to the public as is and is considered public domain and free to redistribute. The USDA, NASS does not warrant any conclusions drawn from these data. If the user does not have software capable of viewing GEOTIF (.tif) file formats then we suggest using the Cropscape website <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:

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.

2010 California Cropland Data Layer
STATEWIDE AGRICULTURAL ACCURACY REPORT

Crop-specific covers only  *Correct  Accuracy   Error   Kappa
-------------------------   -------  --------  ------   -----
OVERALL ACCURACY**          1449683    74.65%  25.35%  0.7132


Cover                  ***Attribute  *Correct  Producer's  Omission            User's  Commission  Cond'l
Type                           Code    Pixels   Accuracy     Error    Kappa  Accuracy      Error    Kappa
----                           ----    ------   --------     -----    -----  --------      -----    -----
Corn                              1    100317     90.26%     9.74%   0.9009    84.16%     15.84%   0.8389
Cotton                            2     71319     96.49%     3.51%   0.9645    91.58%      8.42%   0.9149
Rice                              3    421858     99.28%     0.72%   0.9923    98.86%      1.14%   0.9879
Sorghum                           4       752     52.33%    47.67%   0.5232    55.38%     44.62%   0.5537
Sunflower                         6      2265     72.39%    27.61%   0.7237    64.60%     35.40%   0.6459
Sweet Corn                       12         0       n/a       n/a      n/a      0.00%    100.00%        0
Pop. or Orn. Corn                13         0      0.00%   100.00%        0      n/a        n/a      n/a
Mint                             14      1586     86.71%    13.29%   0.8671    74.60%     25.40%   0.7459
Barley                           21     32567     73.19%    26.81%   0.7301    73.59%     26.41%   0.7341
Durum Wheat                      22     14473     79.30%    20.70%   0.7925    86.56%     13.44%   0.8653
Spring Wheat                     23      4181     65.36%    34.64%   0.6532    60.26%     39.74%   0.6023
Winter Wheat                     24    139281     78.43%    21.57%   0.7784    77.17%     22.83%   0.7656
Rye                              27      4787     61.19%    38.81%   0.6115    65.89%     34.11%   0.6585
Oats                             28     18647     38.12%    61.88%   0.3776    46.98%     53.02%    0.466
Canola                           31         0      0.00%   100.00%        0      n/a        n/a      n/a
Safflower                        33      9817     70.64%    29.36%   0.7058    68.65%     31.35%   0.6859
Alfalfa                          36    315012     90.61%     9.39%   0.9006    83.38%     16.62%   0.8249
Other Hay                        37     46411     42.91%    57.09%   0.4224    57.79%     42.21%   0.5712
Sugarbeets                       41         0      0.00%   100.00%        0      n/a        n/a      n/a
Dry Beans                        42      1705     56.72%    43.28%    0.567    63.41%     36.59%   0.6339
Potatoes                         43      4701     84.76%    15.24%   0.8475    84.19%     15.81%   0.8417
Other Crops                      44       330     18.47%    81.53%   0.1846    52.55%     47.45%   0.5254
Sugarcane                        45         0      0.00%   100.00%        0      n/a        n/a      n/a
Sweet Potatoes                   46      1101     80.60%    19.40%    0.806    67.80%     32.20%   0.6779
Misc. Vegs. & Fruits             47        67     13.16%    86.84%   0.1316    36.41%     63.59%   0.3641
Watermelons                      48       183     40.13%    59.87%   0.4013    91.50%      8.50%    0.915
Onions                           49         0      0.00%   100.00%        0     0.00%    100.00%        0
Peas                             53       191     15.67%    84.33%   0.1566    45.26%     54.74%   0.4525
Tomatoes                         54      9276     70.12%    29.88%   0.7007    80.88%     19.12%   0.8084
Herbs                            57       143     19.75%    80.25%   0.1975    60.08%     39.92%   0.6008
Clover/Wildflowers               58     19137     76.32%    23.68%   0.7623    75.83%     24.17%   0.7574
Sod/Grass Seed                   59      1202     48.18%    51.82%   0.4816    56.09%     43.91%   0.5607
Fallow/Idle Cropland             61    155312     70.13%    29.87%   0.6906    65.44%     34.56%   0.6429
Pasture/Grass                    62   1912224     54.61%    45.39%   0.3494    92.24%      7.76%   0.8414
Woodland                         63         1      0.50%    99.50%    0.005     4.17%     95.83%   0.0416
Cherries                         66      1424     40.86%    59.14%   0.4084    64.00%     36.00%   0.6398
Peaches                          67       715     29.92%    70.08%    0.299    55.86%     44.14%   0.5584
Apples                           68         0      0.00%   100.00%        0     0.00%    100.00%        0
Grapes                           69     18053     75.31%    24.69%   0.7523    78.19%     21.81%   0.7811
Citrus                           72       150     24.31%    75.69%   0.2431    40.32%     59.68%   0.4032
Other Tree Fruits***             73      1057     53.41%    46.59%    0.534    56.40%     43.60%   0.5639
Pecans                           74         0      0.00%   100.00%        0     0.00%    100.00%  -0.0001
Almonds                          75     65882     82.14%    17.86%   0.8191    78.03%     21.97%   0.7777
Walnuts                          76     31388     68.43%    31.57%   0.6822    68.06%     31.94%   0.6785
Wetlands                         87       474      3.95%    96.05%   0.0394    64.31%     35.69%   0.6425
Aquaculture                      92        36     17.56%    82.44%   0.1756   100.00%      0.00%        1
Pistachios                      204     11761     65.05%    34.95%   0.6497    73.26%     26.74%   0.7319
Triticale                       205      4485     37.64%    62.36%   0.3758    65.01%     34.99%   0.6495
Carrots                         206       240     83.33%    16.67%   0.8333    70.80%     29.20%    0.708
Asparagus                       207       123     46.95%    53.05%   0.4695    95.35%      4.65%   0.9535
Garlic                          208        92     72.44%    27.56%   0.7244    96.84%      3.16%   0.9684
Cantaloupes                     209      2140     61.42%    38.58%   0.6141    79.38%     20.62%   0.7937
Prunes                          210      4053     36.33%    63.67%   0.3627    57.83%     42.17%   0.5776
Olives                          211      7250     70.19%    29.81%   0.7014    66.82%     33.18%   0.6677
Oranges                         212      1314     56.78%    43.22%   0.5677    57.35%     42.65%   0.5734
Honeydew Melons                 213         0      0.00%   100.00%        0      n/a        n/a      n/a
Broccoli                        214         0      0.00%   100.00%        0      n/a        n/a      n/a
Peppers                         216         0      0.00%   100.00%        0     0.00%    100.00%        0
Pomegranates                    217       770     55.00%    45.00%   0.5499    69.62%     30.38%   0.6961
Nectarines                      218       233     51.78%    48.22%   0.5178    84.12%     15.88%   0.8411
Plums                           220       235     36.66%    63.34%   0.3666    47.00%     53.00%     0.47
Strawberries                    221      1001     45.50%    54.50%   0.4549    82.39%     17.61%   0.8238
Squash                          222         0      0.00%   100.00%        0     0.00%    100.00%  -0.0001
Apricots                        223       107     11.59%    88.41%   0.1159    58.79%     41.21%   0.5879
Vetch                           224       407     18.58%    81.42%   0.1858    52.86%     47.14%   0.5284
Dbl. Crop WinWht/Corn           225     13428     59.20%    40.80%   0.5908    66.59%     33.41%   0.6648
Dbl. Crop Oats/Corn             226     23956     78.57%    21.43%   0.7846    65.96%     34.04%   0.6581
Lettuce                         227      1202     24.29%    75.71%   0.2426    50.44%     49.56%    0.504
Pumpkins                        229         0       n/a       n/a      n/a      0.00%    100.00%        0
Dbl. Crop Lettuce/Durum Wht     230       222     31.36%    68.64%   0.3135    92.50%      7.50%    0.925
Dbl. Crop Lettuce/Cantaloupe    231         0      0.00%   100.00%        0      n/a        n/a      n/a
Dbl. Crop Lettuce/Upland Cotton 232        42     84.00%    16.00%     0.84   100.00%      0.00%        1
Dbl. Crop Barley/Sorghum        235         0      0.00%   100.00%        0     0.00%    100.00%        0
Dbl. Crop WinWht/Sorghum        236         0      0.00%   100.00%        0     0.00%    100.00%        0
Dbl. Crop Barley/Corn           237         0       n/a       n/a      n/a      0.00%    100.00%        0
Blueberries                     242         1      1.03%    98.97%   0.0103     3.23%     96.77%   0.0322
Cauliflower                     244         0       n/a       n/a      n/a      0.00%    100.00%        0
Cranberries                     250         0      0.00%   100.00%        0      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 and 200-255).
FSA-sampled tree and shrub crops, aquaculture, and all NLCD-sampled categories (codes 62-199) are not included in
the Overall Accuracy.

The accuracy of the non-agricultural land cover classes within the Cropland Data Layer is entirely dependent upon the USGS, National Land Cover Database (NLCD 2001). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover. For more information on the accuracy of the NLCD please reference <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 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: 2010
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 2010 CDL Program, the AWiFS imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used bilinear interpolation, polynomial approximation, polynomial order of 3.

Source_Scale_Denominator: 56 meter
Type_of_Source_Media: CD-ROM and/or DVD
Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20090925
Ending_Date: 20101230

Source_Currentness_Reference: ground condition

Source_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: 2010
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: 20091001
Ending_Date: 20101230

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: 2010
Other_Citation_Details:

The Moderate Resolution Imaging Spectroradiometer (MODIS), 250 meter resolution 16-day composite Normalized Difference Vegetation Index (NDVI) data products from the Terra satellite (MOD13Q1v4) are downloaded from <https://lpdaac.usgs.gov/>. Often late-season MODIS NDVI data are used from the previous growing season in an effort to improve winter wheat detection. Refer to the 'Supplemental Information' Section of this metadata file for specific dates used as classification inputs.

Source_Scale_Denominator: 250 meter
Type_of_Source_Media: online download
Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20091001
Ending_Date: 20100930

Source_Currentness_Reference: ground condition

Source_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 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: 2010
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

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 2010 CDL Program, the AWiFS imagery was resampled to 30 meters to match the Landsat spatial resolution. The resample used bilinear interpolation, polynomial approximation, polynomial order of 3. Some CDL states used additional satellite imagery and ancillary inputs to supplement and improve the classification. These additional sources can include the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover 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. Please refer to the 'Supplemental_Information' Section of this metadata file for a complete list of all imagery and ancillary data used to generate this state's CDL.

ACCURACY: The accuracy of the land cover classifications are evaluated using independent validations data sets generated from the FSA CLU data (agricultural categories) and the NLCD 2001 (non-agricultural categories). The Producer's Accuracy is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the full accuracy report.

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: 2010
Process_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: USDA, NASS, Spatial Analysis Research Section
Contact_Person: USDA, NASS, Spatial Analysis Research Section staff

Contact_Address:

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:

 ***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, 2010 Cropland Data Layer

 Source: USDA, National Agricultural Statistics Service

 The following is a cross reference list of the categorization codes and land covers.
 Note that not all land cover categories listed below will appear in an individual state.

 Raster
 Attribute Domain Values and Definitions: NO DATA, BACKGROUND 0

 Categorization Code   Land Cover
           "0"       Background

 Raster
 Attribute Domain Values and Definitions: CROPS 1-20

 Categorization Code   Land Cover
           "1"       Corn
           "2"       Cotton
           "3"       Rice
           "4"       Sorghum
           "5"       Soybeans
           "6"       Sunflower
          "10"       Peanuts
          "11"       Tobacco
          "12"       Sweet Corn
          "13"       Pop or Orn Corn
          "14"       Mint

 Raster
 Attribute Domain Values and Definitions: GRAINS,HAY,SEEDS 21-40

 Categorization Code   Land Cover
          "21"       Barley
          "22"       Durum Wheat
          "23"       Spring Wheat
          "24"       Winter Wheat
          "25"       Other Small Grains
          "26"       Dbl Crop WinWht/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

2010 California Cropland Data Layer | NASS/USDA

Metadata: