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

Metadata:

• Identification_Information
• Data_Quality_Information
• Spatial_Data_Organization_Information
• Spatial_Reference_Information
• Entity_and_Attribute_Information
• Distribution_Information
• Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator:

United States Department of Agriculture (USDA), National Agricultural Statistics Service (NASS), Research and Development Division (RDD), Geospatial Information Branch (GIB), Spatial Analysis Research Section (SARS)

Publication_Date: 20080701

Title:

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

Edition: 2007 Edition

Geospatial_Data_Presentation_Form: raster digital data

Publication_Information:

Publication_Place:

USDA, NASS Marketing and Information Services Office, Washington, D.C.

Publisher: USDA, NASS

Other_Citation_Details:

SPECIAL NOTE FOR THE 2007 CALIFORNIA CROPLAND DATA LAYER: The 2007 California CDL is a special one-time project created at the internal request of the USDA, NASS Area Frame Section. No future California CDLs are planned at this time. For a list of other states and years of available CDL data please visit <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>.

Available on DVD through the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The data is also available free for download through the Geospatial Data Gateway at <http://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed download instructions.

The official DVD contains additional accuracy assessment information that is not available through the Geospatial Data Gateway in the form of an associated confidence layer. The following description of the confidence layer is taken from the document entitled 'MDA_NLCD_User_Guide.doc' which is available free for download with the NLCD Mapping Tool at <http://www.mrlc.gov/>. The Confidence Layer "spatially represents the predicted confidence that is associated with that output pixel, based upon the rule(s) that were used to classify it. This is useful in that the user can see the spatial representation of distribution and magnitude of error or confidence for a given classification... This error layer represents a percent confidence associated with each rule and output categorical, classified value. It is expressed as a percentage of confidence. A value of zero would therefore have a low confidence (always wrong), while a value of 100 would have a very high confidence (always right)." For more information on the use of confidence layers please refer to the following paper: Liu, Weiguo, Sucharita Gopal and Curtis E. Woodcock, 2004. Uncertainty and confidence in land cover classification using a hybrid classifier approach, Photogrammetric Engineering & Remote Sensing, 70(8):963-971. Ultimately, however, the confidence value is not a measure of accuracy for a given pixel but rather a how well it fit within the decision tree ruleset.

Online_Linkage: <http://datagateway.nrcs.usda.gov/>

Description:

Abstract:

The USDA, NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer with a ground resolution of 56 meters. The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. Ancillary classification inputs include: the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. For the 2007 California CDL additional agricultural training data was derived from the USDA, NASS June Area Survey (JAS). The NLCD 2001 is used as non-agricultural training and validation data. The strength and emphasis of the CDL is agricultural land cover. Please note that no farmer reported data are derivable from the Cropland Data Layer.
SPECIAL NOTE FOR THE 2007 CALIFORNIA CROPLAND DATA LAYER: The 2007 California CDL is a special one-time project created at the internal request of the USDA, NASS Area Frame Section. No future California CDLs are planned at this time. For a list of other states and years of available CDL data please visit <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. It should be noted that there are two versions of the 2007 California Cropland Data Layer. One is a 56 meter pixel resolution product based on AWiFS satellite imagery. The files are named with the following prefix - cdl_awifs_r_ca_2007. The second is a 30 meter pixel resolution product that used Landsat TM imagery in additon to the AWiFS imagery. The files are named with the following prefix - cdl_tm_r_ca_2007. These two land cover products were created independent from one another by different analysts, using different dates of imagery and different spatial resolutions. The user should be aware that the categorization of these two land cover products will be different. See the 'Process Description' Section of this metadata file for more details on how the two versions of the 2007 California CDL differ.

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:

SPECIAL NOTE FOR THE 2007 CALIFORNIA CROPLAND DATA LAYER: There are two versions of the 2007 California Cropland Data Layer. One is a 56 meter pixel resolution product based on AWiFS satellite imagery. The files are named with the following prefix - cdl_awifs_r_ca_2007. The second is a 30 meter pixel resolution product that used Landsat TM imagery in additon to the AWiFS imagery. The files are named with the following prefix - cdl_tm_r_ca_2007. These two land cover products were created independent from one another by different analysts, using different dates of imagery and different spatial resolutions. The user should be aware that the categorization of these two land cover products will be different. See the 'Process Description' Section of this metadata file for more details on how the two versions of the 2007 California CDL differ.

If the following table does not display properly, then please visit this internet site <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm> to view the original metadata file.

USDA, National Agricultural Statistics Service 2007 California Cropland Data Layer - 30 METER VERSION

30 METER VERSION

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

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

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

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

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

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

If the following table does not display properly, then please visit this internet site <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm> to view the original metadata file.

USDA, National Agricultural Statistics Service 2007 California Cropland Data Layer - 56 METER VERSION

56 METER VERSION

CLASSIFICATION INPUTS:
AWIFS DATE 20070401 PATH 246 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20070405 PATH 242 ROW(S)&QUADRANT(S) 40B
AWIFS DATE 20070425 PATH 246 ROW(S)&QUADRANT(S) 40D 45BD
AWIFS DATE 20070426 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070510 PATH 249 ROW(S)&QUADRANT(S) 45B
AWIFS DATE 20070519 PATH 246 ROW(S)&QUADRANT(S) 40D 45BD
AWIFS DATE 20070520 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070523 PATH 242 ROW(S)&QUADRANT(S) 40B
AWIFS DATE 20070528 PATH 243 ROW(S)&QUADRANT(S) 40D
AWIFS DATE 20070529 PATH 248 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20070607 PATH 245 ROW(S)&QUADRANT(S) 45B
AWIFS DATE 20070612 PATH 246 ROW(S)&QUADRANT(S) 40D 45BD
AWIFS DATE 20070613 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070622 PATH 248 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20070626 PATH 244 ROW(S)&QUADRANT(S) 40D
AWIFS DATE 20070627 PATH 249 ROW(S)&QUADRANT(S) 45B
AWIFS DATE 20070701 PATH 245 ROW(S)&QUADRANT(S) 45B
AWIFS DATE 20070707 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070710 PATH 242 ROW(S)&QUADRANT(S) 40BD
AWIFS DATE 20070715 PATH 243 ROW(S)&QUADRANT(S) 40D
AWIFS DATE 20070716 PATH 248 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20070730 PATH 246 ROW(S)&QUADRANT(S) 40D 45B
AWIFS DATE 20070803 PATH 242 ROW(S)&QUADRANT(S) 40BD
AWIFS DATE 20070809 PATH 248 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20070823 PATH 246 ROW(S)&QUADRANT(S) 40D 45B
AWIFS DATE 20070824 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070827 PATH 242 ROW(S)&QUADRANT(S) 40BD
AWIFS DATE 20070901 PATH 243 ROW(S)&QUADRANT(S) 40D
AWIFS DATE 20070902 PATH 248 ROW(S)&QUADRANT(S) 45BD
AWIFS DATE 20070916 PATH 246 ROW(S)&QUADRANT(S) 40BD 45BD
AWIFS DATE 20070917 PATH 251 ROW(S)&QUADRANT(S) 45D
AWIFS DATE 20070920 PATH 242 ROW(S)&QUADRANT(S) 40B
AWIFS DATE 20070926 PATH 248 ROW(S)&QUADRANT(S) 45D

MODIS 16 DAY NDVI COMPOSITE DATE 20060930
MODIS 16 DAY NDVI COMPOSITE DATE 20061016
MODIS 16 DAY NDVI COMPOSITE DATE 20061101
MODIS 16 DAY NDVI COMPOSITE DATE 20061117
MODIS 16 DAY NDVI COMPOSITE DATE 20070101
MODIS 16 DAY NDVI COMPOSITE DATE 20070117
MODIS 16 DAY NDVI COMPOSITE DATE 20070202
MODIS 16 DAY NDVI COMPOSITE DATE 20070218
MODIS 16 DAY NDVI COMPOSITE DATE 20070306
MODIS 16 DAY NDVI COMPOSITE DATE 20070322
MODIS 16 DAY NDVI COMPOSITE DATE 20070407
MODIS 16 DAY NDVI COMPOSITE DATE 20070423
MODIS 16 DAY NDVI COMPOSITE DATE 20070509
MODIS 16 DAY NDVI COMPOSITE DATE 20070525
MODIS 16 DAY NDVI COMPOSITE DATE 20070610
MODIS 16 DAY NDVI COMPOSITE DATE 20070626
MODIS 16 DAY NDVI COMPOSITE DATE 20070712
MODIS 16 DAY NDVI COMPOSITE DATE 20070728
MODIS 16 DAY NDVI COMPOSITE DATE 20070813
MODIS 16 DAY NDVI COMPOSITE DATE 20070829
MODIS 16 DAY NDVI COMPOSITE DATE 20070914

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

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

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

Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20070401

Ending_Date: 20070930

Currentness_Reference: 2007 growing season

Status:

Progress: Complete

Maintenance_and_Update_Frequency: None planned

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate:

30 meter version: -124.5878 56 meter version: -124.5878

East_Bounding_Coordinate:

30 meter version: -114.1883 56 meter version: -114.1881

North_Bounding_Coordinate:

30 meter version: 41.9744 56 meter version: 41.9744

South_Bounding_Coordinate:

30 meter version: 32.5026 56 meter version: 32.5029

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: AWIFS > Advanced Wide Field Sensor

Theme_Keyword: MODIS > Moderate-Resolution Imaging Spectroradiometer

Theme:

Theme_Keyword_Thesaurus: None

Theme_Keyword: crop cover

Theme_Keyword: cropland

Theme_Keyword: agriculture

Theme_Keyword: land cover

Theme_Keyword: crop estimates

Theme_Keyword: AWiFS

Theme_Keyword: MODIS

Place:

Place_Keyword_Thesaurus: Global Change Master Directory (GCMD) Location Keywords

Place_Keyword:

Continent > North America > United States of America > California

Place:

Place_Keyword_Thesaurus: None

Place_Keyword: California

Place_Keyword: CA

Temporal:

Temporal_Keyword_Thesaurus: None

Temporal_Keyword: 2007

Access_Constraints: None

Use_Constraints:

The USDA, NASS Cropland Data Layer is provided to the public as is and is considered public domain and free to redistribute. The USDA, NASS does not warrant any conclusions drawn from these data. If the user does not have software capable of viewing GEOTIF (.tif) or ERDAS Imagine (.img) file formats then we suggest using the freeware browser ESRI ArcReader. Visit their site at <http://www.esri.com/arcreader/> for more information.

Point_of_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: USDA, NASS, Spatial Analysis Research Section

Contact_Person: USDA, NASS, Spatial Analysis Research Section staff

Contact_Address:

Address_Type: mailing and physical address

Address: 3251 Old Lee Highway, Room 305

City: Fairfax

State_or_Province: Virginia

Postal_Code: 22030-1504

Country: USA

Contact_Voice_Telephone: 703-877-8000

Contact_Facsimile_Telephone: 703-877-8044

Contact_Electronic_Mail_Address: HQ_RD_GIB@nass.usda.gov

Data_Set_Credit: USDA, National Agricultural Statistics Service

Security_Information:

Security_Classification_System: None

Security_Classification: Unclassified

Security_Handling_Description: None

Native_Data_Set_Environment:

Microsoft Windows XP; Leica Geosystems ERDAS Imagine 9.1 <http://gi.leica-geosystems.com/>; ESRI ArcGIS Version 9.1 and 9.2 with Service Pack 3 <http://www.esri.com/>; Rulequest See5.0 Release 2.04 <http://www.rulequest.com/>; NLCD Mapping Tool <http://www.mrlc.gov/>.
Leica Geosystems ERDAS Imagine is used in the pre- and post- processing of all raster-based data. ESRI ArcGIS is used to prepare the vector-based 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 classified using in-house software (Peditor) based upon a maximum likelihood classifier approach. Check this section and the 'Process Description' section of the specific state and year metadata file to verify what methodology was used.

Data_Quality_Information:

Attribute_Accuracy:

Attribute_Accuracy_Report:

If the following table does not display properly, then please visit this internet site <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm> to view the original metadata file.

USDA, National Agricultural Statistics Service, 2007 California Cropland Data Layer - 30 METER VERSION
STATEWIDE AGRICULTURAL ACCURACY REPORT

 30 METER VERSION

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


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

*Correct Pixels represents the total number of independent validation pixels correctly identifed
in the error matrix.
USDA, National Agricultural Statistics Service, 2007 California Cropland Data Layer - 56 METER VERSION
STATEWIDE AGRICULTURAL ACCURACY REPORT

 56 METER VERSION

Crop-specific covers only  *Correct  Accuracy   Error   Kappa
-------------------------   -------  --------   -----   -----
OVERALL ACCURACY             431174    81.31%  18.69%  0.7866


Cover              Attribute  *Correct  Producer's  Omission            User's  Commission  Cond'l
Type                    Code    Pixels   Accuracy     Error    Kappa  Accuracy      Error    Kappa
----                    ----    ------   --------     -----    -----  --------      -----    -----
Corn                       1     29340     91.25%     8.75%   0.9111    84.46%     15.54%   0.8423
Cotton                     2      9945     85.19%    14.81%   0.8511    84.55%     15.45%   0.8447
Rice                       3    105854     98.65%     1.35%   0.9858    98.08%      1.92%   0.9798
Sorghum                    4        17      5.03%    94.97%   0.0503    39.53%     60.47%   0.3953
Sunflowers                 6       171     36.54%    63.46%   0.3653    66.80%     33.20%   0.6679
Sweet Corn                12        46     80.70%    19.30%   0.8070    97.87%      2.13%   0.9787
Pop. or Orn. Corn         13         0      0.00%   100.00%   0.0000      n/a        n/a      n/a
Barley                    21      5376     45.61%    54.39%   0.4541    64.24%     35.76%   0.6405
Durum Wheat               22      3949     62.55%    37.45%   0.6247    79.17%     20.83%   0.7911
Spring Wheat              23      1916     75.43%    24.57%   0.7540    70.18%     29.82%   0.7015
Winter Wheat              24     42523     80.03%    19.97%   0.7950    72.81%     27.19%   0.7215
Rye                       27       977     35.67%    64.33%   0.3563    68.66%     31.34%   0.6862
Oats                      28      3677     37.43%    62.57%   0.3724    54.82%     45.18%   0.5462
Canola                    31         0      0.00%   100.00%   0.0000      n/a        n/a      n/a
Safflower                 33      4960     78.79%    21.21%   0.7874    82.67%     17.33%   0.8262
Alfalfa                   36     92371     93.88%     6.12%   0.9357    86.61%     13.39%   0.8600
Other Hays                37        88      6.09%    93.91%   0.0607    16.24%     83.76%   0.1618
Sugarbeets                41       102     20.99%    79.01%   0.2098    54.55%     45.45%   0.5454
Dry Beans                 42        81     17.42%    82.58%   0.1741    49.69%     50.31%   0.4968
Other Crops               44         0      0.00%   100.00%   0.0000      n/a        n/a      n/a
Sugarcane                 45         0       n/a       n/a      n/a      0.00%    100.00%   0.0000
Sweet Potatoes            46         0      0.00%   100.00%   0.0000     0.00%    100.00%   0.0000
Misc. Vegs. & Fruits      47        42     54.55%    45.45%   0.5454    54.55%     45.45%   0.5454
Watermelon                48         0      0.00%   100.00%   0.0000     0.00%    100.00%   0.0000
Onions                    49         2      1.22%    98.78%   0.0122    40.00%     60.00%   0.4000
Peas                      53         0      0.00%   100.00%   0.0000     0.00%    100.00%   0.0000
Herbs                     57       559     67.51%    32.49%   0.6750    70.14%     29.86%   0.7013
Clover/Wildflowers        58      2744     55.76%    44.24%   0.5568    65.74%     34.26%   0.6566
Seed/Sod Grass            59       351     29.37%    70.63%   0.2936    90.46%      9.54%   0.9046
Fallow/Idle Cropland      61     32488     51.81%    48.19%   0.5075    67.66%     32.34%   0.6673
Peaches                   67       138     25.27%    74.73%   0.2526    30.87%     69.13%   0.3086
Apples                    68         3     11.54%    88.46%   0.1154    42.86%     57.14%   0.4286
Grapes                    69      5211     61.39%    38.61%   0.6127    77.13%     22.87%   0.7704
Christmas Trees           70         1      3.85%    96.15%   0.0385    25.00%     75.00%   0.2500
Other Tree Nuts           71         0      0.00%   100.00%   0.0000     0.00%    100.00%   0.0000
Citrus                    72        24     40.00%    60.00%   0.4000    68.57%     31.43%   0.6857
Other Tree Fruits         73        12      8.11%    91.89%   0.0811    44.44%     55.56%   0.4444
Aquaculture               92         0      0.00%   100.00%   0.0000      n/a        n/a      n/a
Almonds                  201     17944     74.30%    25.70%   0.7401    72.03%     27.97%   0.7173
Tomatoes                 202       940     35.11%    64.89%   0.3507    62.33%     37.67%   0.6229
Walnuts                  203      6405     65.30%    34.70%   0.6516    70.11%     29.89%   0.6998
Pistachios               204      3040     38.56%    61.44%   0.3845    78.65%     21.35%   0.7858
Triticale                205       651     17.57%    82.43%   0.1753    66.91%     33.09%   0.6685
Carrots                  206       101     93.52%     6.48%   0.9352    47.42%     52.58%   0.4742
Asparagus                207        40     42.11%    57.89%   0.4210   100.00%      0.00%   1.0000
Garlic                   208         0      0.00%   100.00%   0.0000     0.00%    100.00%   0.0000
Cantaloupe               209        51     14.87%    85.13%   0.1486    37.50%     62.50%   0.3749
Prunes                   210      1049     50.90%    49.10%   0.5086    67.63%     32.37%   0.6760
Olives                   211       528     43.24%    56.76%   0.4323    78.81%     21.19%   0.7879
Oranges                  212       104     57.46%    42.54%   0.5746    88.14%     11.86%   0.8813
Honeydew Melon           213         4      2.48%    97.52%   0.0248    28.57%     71.43%   0.2857
Broccoli                 214         0       n/a       n/a      n/a      0.00%    100.00%   0.0000
Cherry Orchards          215        95     18.96%    81.04%   0.1895    39.92%     60.08%   0.3990
Peppers                  216         0      0.00%   100.00%   0.0000     0.00%    100.00%   0.0000
Pomegranates             217       193     78.78%    21.22%   0.7877    71.22%     28.78%   0.7121
Nectarine                218        29      7.42%    92.58%   0.0741    63.04%     36.96%   0.6304
Greens                   219         0      0.00%   100.00%   0.0000      n/a        n/a      n/a
Plums                    220        23      9.02%    90.98%   0.0902    48.94%     51.06%   0.4893
Strawberries             221         8      4.10%    95.90%   0.0410   100.00%      0.00%   1.0000
Squash                   222         0      0.00%   100.00%   0.0000      n/a        n/a      n/a
Apricots                 223         3      2.27%    97.73%   0.0227    18.75%     81.25%   0.1875
Vetch                    224        16     14.29%    85.71%   0.1428    57.14%     42.86%   0.5714
Dbl. Crop WinWht/Corn    225      1969     51.59%    48.41%   0.5152    62.73%     37.27%   0.6266
Dbl. Crop Oats/Corn      226         1      0.50%    99.50%   0.0049     5.26%     94.74%   0.0525
Lettuce                  227        21     38.89%    61.11%   0.3889    77.78%     22.22%   0.7778
Pumpkin                  229         0      0.00%   100.00%   0.0000      n/a        n/a      n/a

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

Quantitative_Attribute_Accuracy_Assessment:

Attribute_Accuracy_Value:

Classification accuracy is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the detailed accuracy report.

Attribute_Accuracy_Explanation:

The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes is entirely dependent upon the USGS, National Land Cover Dataset (NLCD 2001). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover.

The official DVD contains additional accuracy assessment information that is not available through the Geospatial Data Gateway in the form of an associated confidence layer. The following description of the confidence layer is taken from the document entitled 'MDA_NLCD_User_Guide.doc' which is available free for download with the NLCD Mapping Tool at <http://www.mrlc.gov/>. The Confidence Layer "spatially represents the predicted confidence that is associated with that output pixel, based upon the rule(s) that were used to classify it. This is useful in that the user can see the spatial representation of distribution and magnitude of error or confidence for a given classification. ... This error layer represents a percent confidence associated with each rule and output categorical, classified value. It is expressed as a percentage of confidence. A value of zero would therefore have a low confidence (always wrong), while a value of 100 would have a very high confidence (always right)." For more information on the use of confidence layers please refer to the following paper: Liu, Weiguo, Sucharita Gopal and Curtis E. Woodcock, 2004. Uncertainty and confidence in land cover classification using a hybrid classifier approach, Photogrammetric Engineering & Remote Sensing, 70(8):963-971.

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 '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 '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 'Conditional Kappa Coefficient' is the agreement for an individual category within the entire error matrix.

Logical_Consistency_Report:

The Cropland Data Layer (CDL) has been produced using training and independent validation data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program (agricultural data) and United States Geological Survey (USGS) National Land Cover Dataset 2001 (NLCD 2001). More information about the FSA CLU Program can be found at <http://www.fsa.usda.gov/>. More information about the NLCD 2001 can be found at <http://www.mrlc.gov/>. The CDL encompasses the entire state unless noted otherwise in the 'Completeness Report' section of this metadata file.

Completeness_Report: The entire state is covered by the Cropland Data Layer.

Positional_Accuracy:

Horizontal_Positional_Accuracy:

Horizontal_Positional_Accuracy_Report:

The AWiFS satellite imagery is purchased in an orthorectified and projected format. The Cropland Data Layer retains the spatial attributes of the input AWiFS imagery.

Quantitative_Horizontal_Positional_Accuracy_Assessment:

Horizontal_Positional_Accuracy_Value: 60 meter CE90

Horizontal_Positional_Accuracy_Explanation:

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:

United States Geological Survey (USGS), Earth Resources Observation and Science (EROS)

Title: Landsat 5 Thematic Mapper (TM)

Geospatial_Data_Presentation_Form: remote-sensing image

Publication_Information:

Publisher: USGS, EROS

Publication_Place: Sioux Falls, South Dakota 57198-001

Publication_Date: 2007 growing season

Other_Citation_Details:

Additional information about Landsat 5 TM data can be obtained at <http://eros.usgs.gov/products/satellite/tm.php>. The Landsat 5 TM imagery used in the 2007 California Cropland Data Layer was 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 and rows used as classification inputs.

Source_Scale_Denominator: 30 meter

Type_of_Source_Media: CD-ROM and/or DVD

Source_Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20070416

Ending_Date: 20070913

Source_Currentness_Reference: ground condition

Source_Contribution: Raw data used in land cover spectral signature analysis

Source_Information:

Source_Citation:

Citation_Information:

Originator: Landsat 5

Title: RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS)

Geospatial_Data_Presentation_Form: remote-sensing image

Publication_Information:

Publisher: GeoEye

Publication_Place: Dulles, Virginia 20166

Publication_Date: 2007 growing season

Other_Citation_Details:

The RESOURCESAT-1 (IRS-P6) AWiFS satellite sensor operates in four spectral bands at a spatial resolution of 56 meters. Additional information about AWiFS data can be obtained at <http://www.isro.org/programmes.htm>. 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. Acquisition begins April 1 and ends September 30 of the current growing season. Refer to the 'Supplemental Information' Section of this metadata file for specific scene date, path, row and quadrants used as classification inputs.

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: 20070401

Ending_Date: 20070930

Source_Currentness_Reference: ground condition

Source_Contribution: Raw data used in land cover spectral signature analysis

Source_Information:

Source_Citation:

Citation_Information:

Originator:

United States Geological Survey (USGS) and National Aeronautics and Space Administration (NASA) Land Processes Distributed Active Archive Center (LP DAAC)

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:

late 2006 growing season (used to improve winter wheat identification) and the entire 2007 growing season

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 <http://edcdaac.usgs.gov/modis/dataproducts.asp>. 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: 20061001

Ending_Date: 20070930

Source_Currentness_Reference: ground condition

Source_Contribution: NDVI data used in land cover spectral signature analysis

Source_Information:

Source_Citation:

Citation_Information:

Originator:

United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Data Center

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: Continuously updated

Other_Citation_Details:

The USGS NED Digital Elevation Model (DEM) is used as an ancillary data source in the production of the Cropland Data Layer. Slope and Aspect derived from the DEM are also used as additional classification inputs. More information on the USGS NED can be found at <http://ned.usgs.gov/>. Refer to the 'Supplemental Information' Section of this metadata file for the complete list of ancillary data sources used as classification inputs.

Source_Scale_Denominator: 30 meter

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: unknown

Source_Currentness_Reference: ground condition

Source_Contribution:

spatial and attribute information used in land cover spectral signature analysis

Source_Information:

Source_Citation:

Citation_Information:

Originator:

United States Geological Survey (USGS) Earth Resources Observation and Science (EROS) Data Center

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 <http://www.mrlc.gov/>. Refer to the 'Supplemental Information' Section of this metadata file for the complete list of ancillary data sources used as classification inputs.

Source_Scale_Denominator: 30 meter

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: unknown

Source_Currentness_Reference: ground condition

Source_Contribution:

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

Source_Information:

Source_Citation:

Citation_Information:

Originator:

United States Department of Agriculture (USDA), Farm Service Agency (FSA)

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: 2006

Other_Citation_Details:

Access to the USDA, Farm Service Agency (FSA) Common Land Unit (CLU) digital data set is currently limited to FSA and Agency partnerships. During the current growing season, producers enrolled in FSA programs report their growing intentions, crops and acreage to USDA Field Service Centers. Their field boundaries are digitized in a standardized GIS data layer and the associated attribute information is maintained in a database known as 578 Administrative Data. This CLU/578 dataset provides a comprehensive and robust agricultural training and validation data set for the Cropland Data Layer. Additional information about the CLU Program can be found at <http://www.fsa.usda.gov/>.

Source_Scale_Denominator: 1:4800

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: unknown

Source_Currentness_Reference: ground condition, updated annually

Source_Contribution:

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

Source_Information:

Source_Citation:

Citation_Information:

Originator:

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

Title: June Area Survey (JAS)

Geospatial_Data_Presentation_Form: paper-based data

Publication_Information:

Publisher: unpublished material

Other_Citation_Details:

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

Source_Scale_Denominator: 1:4800

Type_of_Source_Media: paper-based

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 2007

Source_Currentness_Reference: ground condition, updated annually

Source_Contribution:

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

Source_Information:

Source_Citation:

Citation_Information:

Originator:

California Department of Conservation, Division of Land Resource Protection

Title: Farmland Mapping and Monitoring Program (FMMP)

Geospatial_Data_Presentation_Form: vector digital data

Publication_Information:

Publisher:

California Department of Conservation, Division of Land Resource Protection

Publication_Place: Sacramento, California 95814-3528 USA

Publication_Date: 2004

Other_Citation_Details:

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

Source_Scale_Denominator: 1:24,000

Type_of_Source_Media: online

Source_Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: unknown

Source_Currentness_Reference: ground condition, updated biennially on even numbered years

Source_Contribution:

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

Process_Step:

Process_Description:

SPECIAL NOTE FOR THE 2007 CALIFORNIA CROPLAND DATA LAYER: There are two versions of the 2007 California Cropland Data Layer. One is a 56 meter pixel resolution product based on AWiFS satellite imagery. The files are named with the following prefix - cdl_awifs_r_ca_2007. The second is a 30 meter pixel resolution product that used Landsat TM imagery in additon to the AWiFS imagery. The files are named with the following prefix - cdl_tm_r_ca_2007. These two land cover products were created independent from one another by different analysts, using different dates of imagery and different spatial resolutions. The user should be aware that the categorization of these two land cover products will be different.

SPECIAL PROCESSING NOTES FOR THE 2007 CALIFORNIA CROPLAND DATA LAYER: The processing steps outlined in the following 'Process Description' Section of this metadata file apply to most CDL projects. However, the 2007 California CDL used slightly different processing techniques. Firstly, the 30 meter version used Landsat 5 TM satellite imagery in addition to AWiFS imagery. See the 'Supplemental Information' Section of this metadata file for a full list of inputs. Secondly, both versions used additional ground data for training the classifier derived from the USDA, NASS 2007 June Area Survey (JAS). For more information about the JAS visit the following website: <http://www.nass.usda.gov/Surveys/June_Area/>. Thirdly, in order to better manage the large amount of input imagery, the state was split into three Analysis Districts (AD) for processing. For the 30 meter version the North AD was defined by the extents of Landsat paths 45 thru 46, the Central AD was defined by Landsat paths 42 thru 44, and the South AD was defined by Landsat paths 38 thru 41. The three ADs were mosaiced together for the public release. Fourthly, a minimum mapping unit (mmu) was applied to a subset of categories. For the 30 meter version a MMU of 1 pixel (approximately 0.25 acre) was applied to the following CDL categories: 12, 13, 43, 48, 47, 49, 57, 206, 207, 208, 209, 213, 214, 216, 219, 221, 222, 224; and a MMU of 4 pixels (approximately 1 acre) was applied to the following CDL categories: 67, 68, 69, 70, 71, 72, 73, 201, 203, 204, 210, 211, 212, 215, 217, 218, 220, 223. For the 56 meter version a MMU of 5 pixels (approximately 4 acres) was applied to all CDL categories. Lastly, there is no confidence layer available for either version of the 2007 California CDL.

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

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

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

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

INPUTS: The CDL is produced using satellite imagery from the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS) collected during the current growing season. NASS acquires AWiFS imagery for CDL production states from April 1 through September 30 of the current growing season through a cooperative agreement with the USDA, Foreign Agricultural Service (FAS), International Production Assessment (IPA) unit. Ancillary inputs include; the United States Geological Survey (USGS) National Elevation Dataset (NED), the USGS National Land Cover Dataset 2001 (NLCD 2001), and the National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter 16 day Normalized Difference Vegetation Index (NDVI) composites.

ACCURACY: The accuracy of the land cover classifications are evaluated using independent validations data sets generated from the FSA CLU data (agricultural categories) and the NLCD 2001 (non-agricultural categories). The Producer's Accuracy is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the full accuracy report. The official DVD contains additional accuracy assessment information that is not available through the Geospatial Data Gateway in the form of an associated confidence layer. See the 'Attribute Accuracy Explanation' Section of this metadata file for more information on the confidence layer.

PUBLIC RELEASE: The USDA, NASS Cropland Data Layer is considered public domain and free to redistribute. The data is available on DVD for the cost of reproduction through the official website at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. The data is also available free for download through the Geospatial Data Gateway at <http://datagateway.nrcs.usda.gov/>. See the 'Ordering Instructions' section of this metadata file for detailed download instructions. Please note that in no case are farmer reported data revealed or derivable from the public use Cropland Data Layer.

Process_Date: 2007

Process_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: USDA, NASS, Spatial Analysis Research Section

Contact_Person: USDA, NASS, Spatial Analysis Research Section staff

Contact_Address:

Address_Type: mailing and physical address

Address: 3251 Old Lee Highway, Room 305

City: Fairfax

State_or_Province: Virginia

Postal_Code: 22030-1504

Country: USA

Contact_Voice_Telephone: 703-877-8000

Contact_Facsimile_Telephone: 703-877-8044

Contact_Electronic_Mail_Address: HQ_RD_GIB@nass.usda.gov

Cloud_Cover:

Generally, there is enough cloud-free AWiFS satellite imagery available during the growing season that there will be no cloud cover in the published CDL. Older versions of the CDL (prior to 2006) may contain significant cloud cover due to available imagery and processing limitations which have since been overcome. Reference the attribute information within the specific CDL state and year image file to verify the extent of cloud cover.

Spatial_Data_Organization_Information:

Indirect_Spatial_Reference: California

Direct_Spatial_Reference_Method: Raster

Raster_Object_Information:

Raster_Object_Type: Pixel

Row_Count:

30 meter version: 35842 56 meter version: 19201

Column_Count:

30 meter version: 29768 56 meter version: 15948

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Grid_Coordinate_System:

Grid_Coordinate_System_Name:

FOR GEOSPATIAL DATA GATEWAY USERS: Universal Transverse Mercator (UTM)

FOR CD-ROM AND/OR DVD USERS: Albers Conical Equal Area is the native projection used in the production of the Cropland Data Layer. Due to technical restrictions, the online data available free for download through the Geospatial Data Gateway can only be offered in UTM. However, the official Cropland Data Layer CD-Rom and/or DVD available at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> includes the data in its native Albers Conical Equal Area coordinate system, in addition to UTM. The projection parameters for the Albers projection are as follows:

Map_Projection_Name: Albers Conical Equal Area
Albers_Conical_Equal_Area:
Standard_Parallel: 29.500000
Standard_Parallel: 45.500000
Longitude_of_Central_Meridian: -96.000000
Latitude_of_Projection_Origin: 23.000000
False_Easting: 0.000000
False_Northing: 0.000000
Planar_Coordinate_Information:
Planar_Coordinate_Encoding_Method: row and column
Coordinate_Representation:
Abscissa_Resolution: 56
Ordinate_Resolution: 56
Planar_Distance_Units: meters
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: Geodetic Reference System 80
Semi-major_Axis: 6378137.000000
Denominator_of_Flattening_Ratio: 298.257223563

Universal_Transverse_Mercator:

UTM_Zone_Number: 11 North

Transverse_Mercator:

Scale_Factor_at_Central_Meridian: 0.9996

Longitude_of_Central_Meridian: -117

Latitude_of_Projection_Origin: 0

False_Easting: 500000

False_Northing: 0

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: coordinate pair

Coordinate_Representation:

Abscissa_Resolution:

30 meter version: 30 56 meter version: 56

Ordinate_Resolution:

30 meter version: 30 56 meter version: 56

Planar_Distance_Units: meters

Geodetic_Model:

Horizontal_Datum_Name: WGS84

Ellipsoid_Name: WGS84

Semi-major_Axis: 6378137.00

Denominator_of_Flattening_Ratio: 298.257223563

Entity_and_Attribute_Information:

Overview_Description:

Entity_and_Attribute_Overview:

The Cropland Data Layer (CDL) is produced using agricultural training data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program and non-agricultural training data from the United States Geological Survey (USGS) National Land Cover Dataset 2001 (NLCD 2001). The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes are entirely dependent upon the NLCD. Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover.

Entity_and_Attribute_Detail_Citation:

If the following table does not display properly, then please visit this internet site <http://www.nass.usda.gov/research/Cropland/metadata/meta.htm> to view the original metadata file.

 Data Dictionary: USDA, National Agricultural Statistics Service, 2007 California 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: ROW CROPS 1-20
 Categorization Code   Land Cover

         "1"           Corn
         "2"           Cotton
         "3"           Rice
         "4"           Sorghum
         "5"           Soybeans
         "6"           Sunflowers
         "10"          Peanuts
         "11"          Tobacco
         "12"          Sweet Corn
         "13"          Popcorn or Ornamental Corn

 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"          Winter Wheat/Soybeans Double-Cropped
         "27"          Rye
         "28"          Oats
         "29"          Millet
         "30"          Speltz
         "31"          Canola
         "32"          Flaxseed
         "33"          Safflower
         "34"          Rape seed
         "35"          Mustard
         "36"          Alfalfa
         "37"          Other Hays
         "38"          Camelina

 Raster
 Attribute Domain Values and Definitions: OTHER CROPS 41-60
 Categorization Code   Land Cover

         "41"          Sugarbeets
         "42"          Dry Beans
         "43"          Potatoes
         "44"          Other Crops
         "45"          Sugarcane
         "46"          Sweet Potatoes
         "47"          Miscellaneous Vegetables & Fruit
         "48"          Watermelon
         "49"          Onions
         "50"          Pickles
         "51"          Chick Peas
         "52"          Lentils
         "53"          Peas
         "56"          Hops
         "57"          Herbs
         "58"          Clover/Wildflowers
         "59"          Seed/Sod Grass

 Raster
 Attribute Domain Values and Definitions: FSA-DERIVED NON-CROP 61-65
 Categorization Code   Land Cover

         "61"          Fallow/Idle Cropland
         "62"          Grass/Pasture/Non-agricultural
         "63"          Woodland
         "64"          Shrubland
         "65"          Barren

 Raster
 Attribute Domain Values and Definitions: TREE CROPS 66-80
 Categorization Code   Land Cover

         "67"          Peaches
         "68"          Apples
         "69"          Grapes
         "70"          Christmas Trees
         "71"          Other Tree Nuts
         "72"          Citrus
         "73"          Other Tree Fruit

 Raster
 Attribute Domain Values and Definitions: FSA-DERIVED OTHER NON-CROP 81-99
 Categorization Code   Land Cover

         "81"          Clouds
         "82"          Urban/Developed
         "83"          Water
         "87"          Wetlands
         "92"          Aquaculture

 Raster
 Attribute Domain Values and Definitions: NLCD-DERIVED NON-CROP 100-195
 Categorization Code   Land Cover

         "111"          NLCD - Open Water
         "112"          NLCD - Perennial Ice, Snow
         "121"          NLCD - Developed/Open Space
         "122"          NLCD - Developed/Low Intensity
         "123"          NLCD - Developed/Medium Intensity
         "124"          NLCD - Developed/High Intensity
         "131"          NLCD - Barren
         "141"          NLCD - Deciduous Forest
         "142"          NLCD - Evergreen Forest
         "143"          NLCD - Mixed Forest
         "152"          NLCD - Shrubland
         "171"          NLCD - Grassland Herbaceous
         "181"          NLCD - Pasture/Hay
         "182"          NLCD - Cultivated Crop
         "190"          NLCD - Woody Wetlands
         "195"          NLCD - Herbaceous Wetlands

 Raster
 Attribute Domain Values and Definitions: STATE-SPECIFIC CROPS 201-255
 (The following codes are unique to the 2007 California CDL and may not match the codes of other CDLs)
 Categorization Code   Land Cover
         "201"          Almonds
         "202"          Tomatoes
         "203"          Walnuts
         "204"          Pistachios
         "205"          Triticale
         "206"          Carrots
         "207"          Asparagus
         "208"          Garlic
         "209"          Cantaloupe
         "210"          Prunes
         "211"          Olives
         "212"          Oranges
         "213"          Honeydew Melons
         "214"          Broccoli
         "215"          Cherry Orchards
         "216"          Peppers
         "217"          Pomegranates
         "218"          Nectarine
         "219"          Greens
         "220"          Plums
         "221"          Strawberries
         "222"          Squash
         "223"          Apricots
         "224"          Vetch
         "225"          Double-Cropped Winter Wheat/Corn
         "226"          Double-Cropped Oats/Corn
         "227"          Lettuce
         "228"          Cucumber
         "229"          Pumpkin

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: California

State_or_Province: District of Columbia

Postal_Code: 20250-9410

Country: USA

Contact_Voice_Telephone: 800-727-9540

Contact_Facsimile_Telephone: 703-877-8044

Contact_Electronic_Mail_Address: HQ_RD_OD@nass.usda.gov

Contact_Instructions:

The Cropland Data Layer is available free for download at <http://datagateway.nrcs.usda.gov/>.
To order a CD-ROM or DVD fill out the order form at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> and submit it either electronically (invoice will follow with the delivery) or mail the completed form with your check to: USDA/NASS Customer Service, 1400 Independence Avenue, SW, Room 5829-S, California DC 20250-9410. Please note 'Cropland Data Layer - (State and Year)' in the 'Memo' of your check. Checks should be made out to 'USDA, NASS'. Allow 1 week for delivery.

Resource_Description: Cropland Data Layer - California 2007

Distribution_Liability:

Disclaimer: Users of the Cropland Data Layer (CDL) are solely responsible for interpretations made from these products. The CDL is provided 'as is' and the USDA, NASS does not warrant results you may obtain using the Cropland Data Layer. Contact our staff at (HQ_RD_OD@nass.usda.gov) if technical questions arise in the use of the CDL. NASS does maintain a Frequently Asked Questions (FAQ's) section on the CDL website at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>.

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information:

Format_Name: GEOTIFF

Format_Version_Date: California 2007

Format_Information_Content: GEOTIFF

Transfer_Size:

The image file size will vary depending on the state and completeness of coverage. The CD-ROM and/or DVD obtained through the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> contains data for a single year.
When downloading the data through the Geospatial Data Gateway <http://datagateway.nrcs.usda.gov/> all available years of CDL production for the requested state are included in one compressed file. Technical restrictions do not allow us to offer the CDL by individual state/year through the Geospatial Data Gateway. See the 'Ordering Instructions' section of this metadata file for additional information.

Digital_Transfer_Option:

Offline_Option:

Offline_Media: CD-ROM or DVD

Recording_Format: DOS-COPY

Online_Option:

Computer_Contact_Information:

Network_Address:

Network_Resource_Name: <http://datagateway.nrcs.usda.gov/>

Access_Instructions:

See the 'Ordering Instructions' section of this metadata file for detailed download instructions.

Fees:

The USDA, NASS charges a nominal fee to cover the cost of CD-ROM and DVD production and shipping costs. Please visit the official website <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> for prices. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540. The Cropland Data Layer is also available free for download at <http://datagateway.nrcs.usda.gov/>.

Ordering_Instructions:

To order a CD-ROM or DVD fill out the order form at <http://www.nass.usda.gov/research/Cropland/SARS1a.htm> and submit it either electronically (invoice will follow with the delivery) or mail the completed form with your check to: USDA, NASS Customer Service, 1400 Independence Avenue, SW, Room 5829-S, California DC 20250-9410. Please note 'Cropland Data Layer - (State and Year)' in the 'Memo' part of your check. Checks should be made out to 'USDA, NASS'. Allow 1 week for delivery. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540.

The Cropland Data Layer is also available free for download from the NRCS Geospatial Data Gateway at <http://datagateway.nrcs.usda.gov/>.

IMPORTANT NOTE: When downloading the CDL using the NRCS Geospatial Data Gateway all available years of CDL production for the requested state are included in a single compressed file. Geospatial Data Gateway technical restrictions do not allow us to offer the CDL by individual state/year. We are working on offering this option in the future.

Instructions for downloading from the NRCS Geospatial Data Gateway:

Start by clicking on 'Get Data'

Then click on 'Quick State'

Scroll down to choose your state and click 'Continue'

Choose 'Land_use_land_cover' and select 'Cropland Data Layer by State' and 'Continue to Step3'

Choose 'Continue' to Step4

Lastly, you are given the option to download the data for free or to order the
official DVD/CD for the cost of the reproduction.

Turnaround: Allow 1 week for delivery for CD-ROM and/or DVD.

Custom_Order_Process:

For a list of other states and years of available data please visit: <http://www.nass.usda.gov/research/Cropland/SARS1a.htm>. Distribution issues can also be directed to the NASS Customer Service Hotline at 1-800-727-9540. The Cropland Data Layer is also available free for download at <http://datagateway.nrcs.usda.gov/>.

Technical_Prerequisites:

If the user does not have software capable of viewing GEOTIF (.tif) or ERDAS Imagine (.img) file formats then we suggest using the freeware browser ESRI ArcReader <http://www.esri.com/arcreader/>.

Metadata_Reference_Information:

Metadata_Date: 20080701

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization: USDA, NASS, Spatial Analysis Research Section

Contact_Person: USDA, NASS, Spatial Analysis Research Section Staff

Contact_Address:

Address_Type: mailing and physical address

Address: 3251 Old Lee Highway, Room 305

City: Fairfax

State_or_Province: Virginia

Postal_Code: 22030-1504

Country: USA

Contact_Voice_Telephone: 703-877-8000

Contact_Facsimile_Telephone: 703-877-8044

Contact_Electronic_Mail_Address: HQ_RD_GIB@nass.usda.gov

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001-1998

Metadata_Access_Constraints: No restrictions on the distribution or use of the metadata file

Metadata_Use_Constraints: No restrictions on the distribution or use of the metadata file