2025 Crop Frequency Layers

Identification_Information:

Citation:

Citation_Information:

Originator:

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

Publication_Date: 20260309
Title: 2025 Crop Frequency Layers
Edition: 2025 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:

The data can be viewed at CroplandCROS <https://croplandcros.scinet.usda.gov/> and free for download at <https://www.nass.usda.gov/Research_and_Science/Cropland/Release/>. NASS maintains a Frequently Asked Questions (FAQ's) at <https://www.nass.usda.gov/Research_and_Science/Cropland/sarsfaqs2.php>.

Online_Linkage:

<https://www.nass.usda.gov/Research_and_Science/Cropland/Release/>

Larger_Work_Citation:

Citation_Information:

Originator:

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

Publication_Date: 20260309
Title: 2025 Cropland Data Layer
Edition: 2025 Edition
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publication_Place: Washington, District of Columbia 20250-9410 USA
Publisher: USDA NASS

Other_Citation_Details:

For more technical details, FAQs, metadata and download links please visit <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>. The parent dataset, the Cropland Data Layer, is available free for download through CroplandCROS <https://croplandcros.scinet.usda.gov/>

Online_Linkage: <https://croplandcros.scinet.usda.gov/>

Description:

Abstract:

The 2025 Crop Frequency Layers identify crop specific planting frequency for the Continental United States and are based on land cover information derived from the 2008 through 2025 USDA NASS Cropland Data Layers (CDL). The Crop Frequency Layers are raster, geo-referenced data layers that have a ground resolution of 30 meters. There are currently four individual crop frequency data layers that represent four major crop types: corn, cotton, soybeans and wheat. The 2025 CDL has a 10-meter spatial resolution, however in order to maintain consistency with historical data the 2025 Crop Frequency Layers are based on a 30-meter resampled version of 2025 CDL. See the 'Process_Description' Section for details on how this data layer was created.

For a more detailed description of the Crop Frequency Layers please refer to the following journal article: C.G. Boryan.; Z. Yang.; P. Willis, "US Geospatial Crop Frequency Data Layers," Proc. Of the Third International Conference on Agro-geoinformatics (Agro-geoinformatics 2014), August 11-14, 2014, Beijing, China, DOI:10.1109/Agro-Geoinformatics.2014.6910657.

Purpose:

The purpose of the Crop Frequency Layers are to improve NASS Area Frame stratification and sub-stratification.

Time_Period_of_Content:

Time_Period_Information:

Range_of_Dates/Times:

Beginning_Date: 20241001
Ending_Date: 20251230

Currentness_Reference: 2025 growing season

Status:

Progress: Complete
Maintenance_and_Update_Frequency: annual updates

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -130.2328
East_Bounding_Coordinate: -63.6722
North_Bounding_Coordinate: 52.8510
South_Bounding_Coordinate: 21.7423

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: None
Theme_Keyword: crop cover
Theme_Keyword: cropland
Theme_Keyword: agriculture
Theme_Keyword: farming
Theme_Keyword: land cover
Theme_Keyword: crop estimates
Theme_Keyword: ESA SENTINEL-2
Theme_Keyword: Landsat
Theme_Keyword: CroplandCROS

Place:

Place_Keyword_Thesaurus: Global Change Master Directory (GCMD) Location Keywords
Place_Keyword: Continent > North America > United States of America

Place:

Place_Keyword_Thesaurus: None
Place_Keyword: United States
Place_Keyword: USA
Place_Keyword: CONUS

Temporal:

Temporal_Keyword_Thesaurus: None
Temporal_Keyword: 2025

Access_Constraints: none
Use_Constraints:

The Crop Frequency Layers are 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.

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

Data_Quality_Information:

Attribute_Accuracy:

Attribute_Accuracy_Report:

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

USDA National Agricultural Statistics Service, 2025 Crop Frequency Layers
STATEWIDE AGRICULTURAL ACCURACY REPORT

Crop-specific covers only               *Correct   Accuracy      Error      Kappa
-------------------------                -------   --------     ------      -----
CORN OVERALL ACCURACY                 43,915,303      86.0%      14.0%      0.837
COTTON OVERALL ACCURACY               50,749,096      99.4%       0.6%      0.840
SOYBEANS OVERALL ACCURACY             43,997,627      86.1%      13.9%      0.834
WHEAT OVERALL ACCURACY                45,970,015      90.0%      10.0%      0.821

CORN
Cover                       Attribute   *Correct Producer's   Omission                User's Commission     Cond'l
Type                             Code     Pixels   Accuracy      Error      Kappa   Accuracy      Error      Kappa
----                             ----     ------   --------      -----      -----   --------      -----      -----
One Year                            1  1,203,760      82.2%      17.8%      0.816      75.5%      24.5%      0.748
Two Years                           2    880,067      77.8%      22.2%      0.773      75.6%      24.4%      0.751
Three Years                         3    806,844      74.0%      26.0%      0.734      74.4%      25.6%      0.738
Four Years                          4    858,128      71.8%      28.2%      0.711      72.9%      27.1%      0.722
Five Years                          5    959,652      68.4%      31.6%      0.675      71.2%      28.8%      0.704
Six Years                           6  1,218,850      72.5%      27.5%      0.715      70.5%      29.5%      0.695
Seven Years                         7  1,402,780      71.1%      28.9%      0.700      70.5%      29.5%      0.693
Eight Years                         8  2,727,890      68.8%      31.2%      0.664      75.2%      24.8%      0.731
Nine Years                          9 13,051,400      91.4%       8.6%      0.881      90.6%       9.4%      0.870
Ten Years                          10  3,430,150      83.8%      16.2%      0.823      80.0%      20.0%      0.782
Eleven Years                       11  2,071,540      85.9%      14.1%      0.851      83.3%      16.7%      0.825
Twelve Years                       12  1,683,580      87.3%      12.7%      0.868      86.5%      13.5%      0.860
Thirteen Years                     13  1,150,510      88.3%      11.7%      0.880      86.3%      13.7%      0.860
Fourteen Years                     14    817,690      87.7%      12.3%      0.875      87.2%      12.8%      0.870
Fifteen Years                      15    598,553      87.8%      12.2%      0.877      87.7%      12.3%      0.876
Sixteen Years                      16    424,408      87.3%      12.7%      0.872      87.7%      12.3%      0.876
Seventeen Years                    17    381,442      90.1%       9.9%      0.900      88.2%      11.8%      0.881
Eighteen Years                     18    431,179      91.2%       8.8%      0.911      97.1%       2.9%      0.971

COTTON
Cover                       Attribute   *Correct Producer's   Omission                User's Commission     Cond'l
Type                             Code     Pixels   Accuracy      Error      Kappa   Accuracy      Error      Kappa
----                             ----     ------   --------      -----      -----   --------      -----      -----
One Year                            1    166,419      83.1%      16.9%      0.830      65.5%      34.5%      0.653
Two Years                           2     98,849      77.7%      22.3%      0.776      73.4%      26.6%      0.733
Three Years                         3     72,561      74.2%      25.8%      0.741      72.6%      27.4%      0.725
Four Years                          4     65,045      74.9%      25.1%      0.749      74.8%      25.2%      0.748
Five Years                          5     52,753      71.9%      28.1%      0.719      74.4%      25.6%      0.744
Six Years                           6     50,947      73.7%      26.3%      0.737      74.2%      25.8%      0.742
Seven Years                         7     42,261      72.6%      27.4%      0.726      70.6%      29.4%      0.706
Eight Years                         8     41,298      70.0%      30.0%      0.699      73.2%      26.8%      0.732
Nine Years                          9     36,808      71.6%      28.4%      0.716      76.3%      23.7%      0.763
Ten Years                          10     21,161      68.0%      32.0%      0.679      66.3%      33.7%      0.663
Eleven Years                       11     17,524      68.2%      31.8%      0.682      70.3%      29.7%      0.703
Twelve Years                       12     15,762      69.1%      30.9%      0.690      69.8%      30.2%      0.698
Thirteen Years                     13     15,936      74.4%      25.6%      0.744      74.1%      25.9%      0.741
Fourteen Years                     14     11,547      72.2%      27.8%      0.722      71.3%      28.7%      0.713
Fifteen Years                      15     10,220      71.1%      28.9%      0.711      72.7%      27.3%      0.727
Sixteen Years                      16      9,566      77.5%      22.5%      0.775      69.9%      30.1%      0.699
Seventeen Years                    17      8,347      72.5%      27.5%      0.725      70.9%      29.1%      0.709
Eighteen Years                     18     19,792      81.9%      18.1%      0.819      95.8%       4.2%      0.958

SOYBEANS
Cover                       Attribute   *Correct Producer's   Omission                User's Commission     Cond'l
Type                             Code     Pixels   Accuracy      Error      Kappa   Accuracy      Error      Kappa
----                             ----     ------   --------      -----      -----   --------      -----      -----
One Year                            1    909,106      80.8%      19.2%      0.803      76.0%      24.0%      0.754
Two Years                           2    807,863      79.6%      20.4%      0.792      78.9%      21.1%      0.784
Three Years                         3    952,177      79.4%      20.6%      0.789      80.7%      19.3%      0.803
Four Years                          4  1,171,940      79.9%      20.1%      0.794      80.3%      19.7%      0.797
Five Years                          5  1,541,280      80.8%      19.2%      0.800      81.2%      18.8%      0.805
Six Years                           6  2,108,150      81.9%      18.1%      0.810      82.6%      17.4%      0.816
Seven Years                         7  2,588,240      80.0%      20.0%      0.786      80.4%      19.6%      0.791
Eight Years                         8  4,324,150      75.7%      24.3%      0.728      79.6%      20.4%      0.771
Nine Years                          9 13,547,400      91.1%       8.9%      0.874      90.3%       9.7%      0.863
Ten Years                          10  1,971,310      75.3%      24.7%      0.739      71.8%      28.2%      0.703
Eleven Years                       11    851,129      72.5%      27.5%      0.718      68.9%      31.1%      0.681
Twelve Years                       12    588,048      72.5%      27.5%      0.720      70.6%      29.4%      0.702
Thirteen Years                     13    310,749      67.2%      32.8%      0.669      64.6%      35.4%      0.643
Fourteen Years                     14    192,181      64.9%      35.1%      0.647      61.2%      38.8%      0.609
Fifteen Years                      15    134,106      60.6%      39.4%      0.605      60.5%      39.5%      0.603
Sixteen Years                      16    108,739      61.5%      38.5%      0.614      59.7%      40.3%      0.596
Seventeen Years                    17    102,006      69.3%      30.7%      0.692      61.7%      38.3%      0.616
Eighteen Years                     18    108,153      78.5%      21.5%      0.785      76.8%      23.2%      0.767

WHEAT
Cover                       Attribute   *Correct Producer's   Omission                User's Commission     Cond'l
Type                             Code     Pixels   Accuracy      Error      Kappa   Accuracy      Error      Kappa
----                             ----     ------   --------      -----      -----   --------      -----      -----
One Year                            1  2,345,700      85.5%      14.5%      0.847      81.5%      18.5%      0.804
Two Years                           2  1,280,500      78.8%      21.2%      0.781      77.9%      22.1%      0.772
Three Years                         3    951,202      73.5%      26.5%      0.729      75.2%      24.8%      0.745
Four Years                          4    844,425      64.7%      35.3%      0.639      71.7%      28.3%      0.709
Five Years                          5    789,109      54.9%      45.1%      0.538      63.7%      36.3%      0.626
Six Years                           6    968,641      65.4%      34.6%      0.643      60.6%      39.4%      0.594
Seven Years                         7    736,386      62.4%      37.6%      0.615      59.8%      40.2%      0.589
Eight Years                         8    812,345      66.5%      33.5%      0.657      64.4%      35.6%      0.635
Nine Years                          9  2,231,960      88.4%      11.6%      0.878      85.1%      14.9%      0.843
Ten Years                          10    462,061      70.3%      29.7%      0.700      68.5%      31.5%      0.681
Eleven Years                       11    329,169      70.5%      29.5%      0.703      67.4%      32.6%      0.671
Twelve Years                       12    325,482      74.1%      25.9%      0.738      72.0%      28.0%      0.717
Thirteen Years                     13    189,229      69.0%      31.0%      0.688      65.0%      35.0%      0.648
Fourteen Years                     14    134,115      66.6%      33.4%      0.665      61.3%      38.7%      0.612
Fifteen Years                      15    111,086      64.8%      35.2%      0.647      62.7%      37.3%      0.625
Sixteen Years                      16     68,478      50.4%      49.6%      0.503      52.1%      47.9%      0.520
Seventeen Years                    17     59,922      54.3%      45.7%      0.542      51.6%      48.4%      0.515
Eighteen Years                     18    135,005      77.9%      22.1%      0.778      65.1%      34.9%      0.650

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

Quantitative_Attribute_Accuracy_Assessment:

Attribute_Accuracy_Value:

The Crop Frequency Layers are based on the Cropland Data Layer (CDL). The classification accuracy of the original CDLs is generally 85% to 95% correct for the major crop-specific land cover categories. See the 'Attribute Accuracy Report' section of this metadata file for the detailed accuracy report.

Attribute_Accuracy_Explanation:

The accuracy assessment of the Crop Frequency Layers use the entire FSA CLU data (agricultural categories) that was used in the training and validation of the original Cropland Data Layers (CDL). Only FSA data that exists in all years (2008-2025) is used for validating the Crop Frequency Layers. See the 'Attribute Accuracy Report' section of this metadata file for the full accuracy report.

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 2025 Crop Frequency Layers are based on the 2008-2025 Cropland Data Layers (CDLs). The CDL data are produced using training and independent validation data from the Farm Service Agency (FSA) Common Land Unit (CLU) Program (agricultural data) and the most recent version of the United States Geological Survey (USGS) National Land Cover Database (NLCD). More information about the FSA CLU Program can be found at <https://www.fsa.usda.gov/>. More information about the NLCD can be found at <https://www.mrlc.gov/>.

Completeness_Report: The data encompasses the Continental United States.
Positional_Accuracy:

Horizontal_Positional_Accuracy:

Horizontal_Positional_Accuracy_Report:

The Cropland Data Layer and Crop Frequency Layers retain the spatial attributes of the input imagery. The Landsat 8 and 9 OLI/TIRS imagery is obtained via download from the USGS Global Visualization Viewer <https://glovis.usgs.gov/> using the Collection 2 Level-1 specifications. Please reference the metadata on the Glovis website for the positional accuracy of each Landsat scene. The Sentinel 2A and 2B imagery is obtained via download from the Copernicus Open Access Hub <https://scihub.copernicus.eu/> using the S2MSI1C product type which is orthorectified Top-of-Atmosphere reflectance. Please reference the metadata on the Copernicus website for positional accuracy details.

Lineage:

Source_Information:

Source_Citation:

Citation_Information:

Originator:

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

Publication_Date: 20260309
Title: 2025 Cropland Data Layer
Edition: 2025 Edition
Geospatial_Data_Presentation_Form: remote-sensing image
Publication_Information:

Publication_Place: Washington, District of Columbia 20250-9410 USA
Publisher: USDA NASS

Other_Citation_Details:

Visit CroplandCROS <https://croplandcros.scinet.usda.gov/> or <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php> for more information.

The USDA NASS Cropland Data Layer (CDL) is a raster, geo-referenced, crop-specific land cover data layer. The CDL is produced using moderate spatial resolution satellite imagery which in the past has included the following: Landsat 5 TM, Landsat 7 ETM+, Landsat 8 and 9 OLI/TIRS, the Indian Remote Sensing RESOURCESAT-1 (IRS-P6) Advanced Wide Field Sensor (AWiFS), the Disaster Monitoring Constellation (DMC) DEIMOS-1 and UK2 sensors, ISRO ResourceSat-2 LISS-3, and ESA SENTINEL-2A and -2B sensors. 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 most current version of the USGS National Land Cover Database (NLCD), 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 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.

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: 2008
Ending_Date: 2025

Source_Currentness_Reference: ground condition

Source_Citation_Abbreviation: CDL
Source_Contribution: Land cover information used to identify planting history

Process_Step:

Process_Description:

OVERVIEW: The 2025 Crop Frequency Layers identify crop specific planting frequency for the Continental United States and are based on land cover information derived from the 2008 through 2025 USDA NASS Cropland Data Layers (CDL). The Crop Frequency Layers are raster, geo-referenced data layers that have a ground resolution of 30 meters. The 2025 CDL has a 10-meter spatial resolution, however in order to maintain consistency with historical data the 2025 Crop Frequency Layers are based on a 30-meter resampled version of 2025 CDL. There are currently four individual crop frequency data layers that represent four major crop types: corn, cotton, soybeans and wheat. The list below shows the input CDL crop codes for each of the four crop types. In cases of double cropping, the crop is included in both crop type categories.

CROP_TYPE CDL_CODES

Corn           1,225,226,228,237,241
Cotton         2,232,238,239
Soybeans       5,26,239,240,241,254
Wheat          22,23,24,26,225,230,234,236,238

An Erdas Imagine Spatial Model is used to recode the original CDLs to represent only the crop of interest and then the individual years of crop-specific CDLs are added together to calculate a planting frequency count per pixel. The 2025 Crop Frequency Layers have the following attributes:

CODE   CLASS_NAME
0	No Data/Background
1	Planted 1 time in 18 years
2	Planted 2 times in 18 years
3	Planted 3 times in 18 years
4	Planted 4 times in 18 years
5	Planted 5 times in 18 years
6	Planted 6 times in 18 years
7	Planted 7 times in 18 years
8	Planted 8 times in 18 years
9	Planted 9 times in 18 years
10	Planted 10 times in 18 years
11	Planted 11 times in 18 years
12	Planted 12 times in 18 years
13	Planted 13 times in 18 years
14	Planted 14 times in 18 years
15	Planted 15 times in 18 years
16	Planted 16 times in 18 years
17	Planted 17 times in 18 years
18	Planted 18 times in 18 years
255    Planted 0 times in 18 years

For a more detailed description of the Crop Frequency Layers please reference refer to the following: C.G. Boryan.; Z. Yang.; P. Willis, "US Geospatial Crop Frequency Data Layers," Proc. Of the Third International Conference on Agro-geoinformatics (Agro-geoinformatics 2014), August 11-14, 2014, Beijing, China, DOI:10.1109/Agro-Geoinformatics.2014.6910657.

ACCURACY: The accuracy assessment of the Crop Frequency Layers use the entire FSA CLU data (agricultural categories) that was used in the training and validation of the original 2008-2025 Cropland Data Layers (CDL). Only FSA data that exists in all years is used for validating the Crop Frequency Layers. The Crop Frequency Layer validation is prepared using the same processing steps as described above. See the 'Attribute Accuracy Report' section of this metadata file for the full accuracy report.

PUBLIC RELEASE: The Crop Frequency Layers are considered public domain and free to redistribute. The data can be viewed at CroplandCROS <https://croplandcros.scinet.usda.gov/> and downloaded at <https://www.nass.usda.gov/Research_and_Science/Cropland/Release/index.php>. Please note that in no case are farmer reported data revealed or derivable from the public use Crop Frequency Layers or Cropland Data Layer.

Process_Date: 2025
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

2025 Crop Frequency Layers

Metadata: