MS Croplands by County 2024 Type File Geodatabase Feature Class Tags USDA, crops, land use, Mississippi
Summary
The purpose of the Cropland Data Layer Program is to use satellite imagery to (1) provide supplemental acreage estimates to the Agricultural Statistics Board for the state's major commodities and (2) produce digital, crop-specific, categorized geo-referenced output products.
*** November 2025 - MARIS staff converted the .tif from USDA to a polygon feature class. They then created their own shade set to not have non-Mississippi Categories in the Legend. For full USDA metadata, see : https://maris.mississippi.edu//HTML/DATA/data_Geoscience/Cropland.html#gsc.tab=0
or the .htm included in this packet!
MARIS staff copied some of the major metadata into this document. ***
Description
The USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) is an annual raster, geo-referenced, crop-specific land cover data layer produced using satellite imagery and extensive agricultural ground reference data. The program began in 1997 with limited coverage and in 2008 forward expanded coverage to the entire Continental United States. Please note that no farmer reported data are derivable from the Cropland Data Layer.
New for the 2024 10-meter CDL, the crop classification utilized remote sensing data from harmonized Sentinel-2 MSI Level-2A, Landsat 8, and Landsat 9 Level-2 Collection 2 Tier-1 products, providing surface reflectance (SR) data across multiple spectral bands, including GREEN, RED, NIR, SWIR1, SWIR2, and RedEdge bands 1-4. To mitigate cloud cover, 10-day median composites of surface reflectance and NDVI were created from the cloud-masked Landsat-Sentinel multi-sensor data for the growing season of 2024. An impervious layer from USGS NLCD 2021 and a digital elevation model from USGS 3DEP were also included ancillary input variables. In addition, mixed sampling strategies and localized training and were applied to the 2024 10m CDL production. Additional information: Z. Li, R. Mueller, Z. Yang, D. Johnson and
P. Willis, "Cloud-Powered Agricultural Mapping: A Revolution Toward 10m Resolution Cropland Data Layers," IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 4081-4084, doi: 10.1109/IGARSS53475.2024.10641079. PDF available at
<https://www.nass.usda.gov/Research_and_Science/Cropland/docs/IGARSS2024_Proceedings_10mCDL_Li_ etal.pdf>.
The 2024 CDL has a spatial resolution of 10 meters and was produced using satellite imagery from Landsat 8 and 9 OLI/TIRS and ESA SENTINEL-2A and -2B collected throughout the growing season. Additional ancillary inputs were used to supplement and improve the land cover classification including the United States Geological Survey (USGS) 3D Elevation Program (3DEP) Elevation Dataset (NED), and the USGS National Land Cover Database imperviousness data layer. Agricultural training and validation data are derived from the Farm Service Agency (FSA) Common Land Unit (CLU) Program. Some CDL states incorporate additional crop-specific ground reference obtained from the following non-FSA sources which are detailed in the 'Lineage' Section of this metadata: US Bureau of Reclamation, NASS Citrus Data Layer (internal use only), California Department of Water Resources, Florida Department of Agriculture and Consumer Services Office of Agricultural Water Policy, Cornell University grape/vineyard data, Utah
Department of Water Resources, and Washington State Department of Agriculture. The 2021 NLCD was used as non-agricultural training and validation data for the 2024 CDL. Please visit the CDL FAQs and metadata webpages at <https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php> to view a complete list of imagery, ancillary inputs, and ground reference used for a specific state and year.
** NOTE - In November 2025, ARIS staff converted the .tif from USDA to a polygon feature class. They then created their own shade set to not have non-Mississippi Categories in the Legend. For full metadata from USDA, see their .htm included in this packet! MARIS staff copied some of the major metadata into this document.
Credits
United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS), MARIS
Use limitations
There are no access and use limitations for this item.
Extent
There is no extent for this item.
Scale Range
Maximum (zoomed in) 1:5,000
Minimum (zoomed out) 1:150,000,000
Themes or categories of the resource Farming, Biota, Boundaries, Geoscientific
Content type ⇔ Downloadable Data
Export to FGDC CSDGM XML format as Resource Description No
Title MS Croplands by County 2024 Creation date 2024-12-30 00:00:00
Publication date 2025-02-27 00:00:00 Presentation formats ⇔ digital map
Other citation details
Z. Li, R. Mueller, Z. Yang, D. Johnson and P. Willis, "Cloud-Powered Agricultural Mapping: A Revolution Toward 10m Resolution Cropland Data Layers," IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 4081-4084, doi: 10.1109/IGARSS53475.2024.10641079. PDF available at
<https://www.nass.usda.gov/Research_and_Science/Cropland/docs/IGARSS2024_Proceedings_10 mCDL_Li_etal.pdf>. Data available free for download at <https://croplandcros.scinet.usda.gov/>. Frequently Asked Questions at
<https://www.nass.usda.gov/Research_and_Science/Cropland/SARS1a.php>.
Responsible party - originator Individual's name Staff
Organization's name United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS)
Address
Type physical
Delivery point USDA NASS Marketing and Information Services Office, Washington, D.C. Contact instructions
Responsible party - distributor Individual's name Steve Walker Organization's name MARIS
Contact's position GIS Operations Manager
Address Type postal
Delivery point 3825 Ridgewood Rd Suite 717 City Jackson
Administrative area MS Postal code 39211 Country US
e-mail address swalker@mississippi.edu
Dataset languages ⇔ English (UNITED STATES) Spatial representation type ⇔ vector
Processing environment ⇔ Microsoft Windows 10 Version 10.0 (Build 26100) ; Esri ArcGIS
13.5.2.57366
Credits
United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS), MARIS
ArcGIS item properties
Name ⇔ MS_CroplandFC_2024_County
Location
⇔ file://\\10.10.17.31\MARIS\ArcPro_Projects\Geoscience\Geoscience\MS_Cropland_2024\MS_ Cropland_2024.gdb
Access protocol ⇔ Local Area Network
Point of contact - point of contact
Individual's name USDA NASS, Spatial Analysis Research Section staff Organization's name USDA NASS, Spatial Analysis Research Section
Phone
Voice 855-493-0447
Address Type both
Delivery point 1400 Independence Avenue, SW, Room 5029 South Building City Washington
Administrative area District of Columbia Postal code 20250-2001
Country US
e-mail address SM.NASS.RDD.GIB@usda.gov
ArcGIS coordinate system Type ⇔ Projected
Geographic coordinate reference ⇔ GCS_WGS_1984 Projection ⇔ WGS_1984_UTM_Zone_16N Coordinate reference details ⇔ ProjectedCoordinateSystem
WKID 32616
XOrigin -5120900
YOrigin -9998100
XYScale 1
ZOrigin -100000
ZScale 10000
MOrigin -100000
MScale 10000
XYTolerance 2
ZTolerance 0.001
MTolerance 0.001 HighPrecision true LatestWKID 32616 WKT
PROJCS["WGS_1984_UTM_Zone_16N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHE ROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174
532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PA RAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-87.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.
0],AUTHORITY["EPSG",32616]]
Reference system identifier Value ⇔ 32616
Codespace ⇔ EPSG
Version ⇔ 9.8.8(3.0.1)
Level of topology for this dataset ⇔ geometry only
Geometric objects
Feature class name MS_CroplandFC_2024_County Object type ⇔ composite
Object count ⇔ 0
ArcGIS Feature Class Properties ► Feature class name MS_CroplandFC_2024_County Feature type ⇔ Simple
Geometry type ⇔ Polygon Has topology ⇔ FALSE Feature count ⇔ 0
Spatial index ⇔ TRUE
Linear referencing ⇔ FALSE
Scope of quality information ►
Resource level attribute
Data quality report - Quantitative attribute accuracy ►
Conformance test results Result explanation
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. Accuracy at the individual state-level can be viewed at the CDL Metadata webpage. USDA National Agricultural Statistics Service, 2024 Cropland Data Layer
STATEWIDE AGRICULTURAL ACCURACY REPORT
Crop-specific covers only *Correct Accuracy Error Kappa OVERALL ACCURACY** 2,763,127 77.5% 22.5% 0.733
Cover Attribute *Correct Producer's Omission User's Commission Cond'l
Type | Code | Pixels | Accuracy | Error | Kappa | Accuracy | Error | Kappa |
Corn | 1 | 926,684 | 92.6% | 7.4% | 0.923 | 92.3% | 7.7% | 0.919 |
Cotton | 2 | 118,322 | 85.2% | 14.8% | 0.852 | 86.2% | 13.8% | 0.861 |
Rice | 3 | 35,276 | 96.1% | 3.9% | 0.961 | 91.3% | 8.7% | 0.912 |
Sorghum | 4 60,299 79.9% | 20.1% 0.799 69.8% 30.2% 0.697 | ||||||
Soybeans | 5 830,135 91.2% | 8.8% 0.908 91.6% 8.4% 0.912 | ||||||
Sunflower | 6 | 7,181 | 82.8% | 17.2% | 0.828 | 82.8% | 17.2% | 0.828 |
Peanuts | 10 | 18,182 | 90.7% | 9.3% | 0.906 | 74.8% | 25.2% | 0.747 |
Tobacco | 11 329 37.9% 62.1% 0.379 70.3% 29.7% 0.703 |
Sweet Corn | 12 1,389 56.2% 43.8% 0.562 56.6% 43.4% 0.566 |
Pop or Orn Corn | 13 1,298 82.7% 17.3% 0.827 52.3% 47.7% 0.523 |
Mint | 14 402 82.5% 17.5% 0.825 76.9% 23.1% 0.769 |
Barley | 21 16,542 74.3% 25.7% 0.743 65.1% 34.9% 0.650 |
16,332 | 72.0% | 28.0% | 0.720 | 62.6% | 37.4% |
110,760 | 82.9% | 17.1% | 0.828 | 86.7% | 13.3% 0.866 |
204,900 | 87.1% | 12.9% | 0.869 | 81.1% | 18.9% |
90 | 33.2% | 66.8% | 0.332 | 54.5% | 45.5% 0.545 |
Durum Wheat 22
0.625
Spring Wheat 23
Winter Wheat 24
0.809
Other Small Grains 25
Dbl Crop 0.815 Rye | WinWht/Soybeans 27 | 26 2,895 | 36,376 54.7% | 78.4% 45.3% | 21.6% 0.546 | 0.783 36.1% | 81.6% 63.9% | 18.4% 0.360 |
Oats | 28 | 6,701 | 57.3% | 42.7% | 0.573 | 36.2% | 63.8% | 0.362 |
Millet | 29 | 5,076 | 64.7% | 35.3% | 0.647 | 52.3% | 47.7% | 0.523 |
Speltz | 30 | 29 | 15.4% | 84.6% | 0.154 | 30.9% | 69.1% | 0.309 |
Canola | 31 | 28,077 93.8% 6.2% 0.938 | 89.1% 10.9% 0.891 | |||||
Flaxseed | 32 | 1,003 61.2% 38.8% 0.612 | 51.4% 48.6% 0.514 | |||||
Safflower | 33 | 1,363 75.4% 24.6% 0.754 | 77.2% 22.8% 0.772 | |||||
Rape Seed | 34 | 25 25.5% 74.5% 0.255 | 50.0% 50.0% 0.500 | |||||
Mustard | 35 | 1,657 82.9% 17.1% 0.829 | 73.3% 26.7% 0.733 | |||||
Alfalfa | 36 | 88,352 | 79.6% 20.4% 0.795 60.3% 39.7% | 0.601 |
Other Hay/Non Alfalfa | 37 | 13,256 46.8% 53.2% 0.464 8.3% | 91.7% | |
0.082 |
Camelina | 38 165 | 44.6% | 55.4% | 0.446 | 39.0% | 61.0% | 0.390 | |
Buckwheat | 39 311 | 57.9% | 42.1% | 0.579 | 71.0% | 29.0% | 0.710 | |
Sugarbeets | 41 11,233 | 95.6% | 4.4% | 0.956 | 91.1% | 8.9% | 0.911 | |
Dry Beans | 42 14,668 | 80.6% | 19.4% | 0.806 | 77.0% | 23.0% | 0.770 | |
Potatoes | 43 8,489 | 89.7% | 10.3% | 0.897 | 87.1% | 12.9% | 0.871 | |
Other Crops | 44 731 | 46.0% | 54.0% | 0.460 | 54.3% | 45.7% | 0.543 | |
Sugarcane | 45 13,498 | 88.5% | 11.5% | 0.885 | 90.0% | 10.0% | 0.900 | |
Sweet Potatoes | 46 935 | 83.8% | 16.2% | 0.838 | 77.6% | 22.4% | 0.776 | |
Misc Vegs & Fruits | 47 62 | 9.8% | 90.2% | 0.098 | 24.5% | 75.5% | 0.245 | |
Watermelons | 48 268 | 45.9% | 54.1% | 0.459 | 55.4% | 44.6% | 0.554 | |
Onions | 49 923 | 70.1% | 29.9% | 0.701 | 76.8% | 23.2% | 0.768 | |
Cucumbers | 50 306 | 56.5% | 43.5% | 0.565 | 68.0% | 32.0% | 0.680 | |
Chick Peas | 51 5,280 | 77.7% | 22.3% | 0.777 | 81.7% | 18.3% | 0.817 | |
Lentils | 52 10,012 | 82.2% | 17.8% | 0.822 | 77.6% | 22.4% | 0.776 | |
Peas | 53 10,544 | 81.8% | 18.2% | 0.818 | 73.0% | 27.0% | 0.730 | |
Tomatoes | 54 1,893 | 78.0% | 22.0% | 0.780 | 86.1% | 13.9% | 0.861 | |
Caneberries | 55 | 62 | 51.2% | 48.8% | 0.512 | 49.2% | 50.8% | 0.492 |
Hops | 56 | 594 | 88.9% | 11.1% | 0.889 | 81.5% | 18.5% | 0.815 |
Herbs | 57 | 615 53.2% 46.8% 0.532 38.7% 61.3% 0.387 | ||||||
Clover/Wildflowers | 58 | 490 | 41.7% | 58.3% | 0.417 | 34.8% | 65.2% | 0.348 |
Sod/Grass Seed | 59 | 4,068 | 60.1% | 39.9% | 0.600 | 49.6% | 50.4% | 0.496 |
Switchgrass | 60 | 33 18.8% 81.3% 0.187 30.0% 70.0% 0.300 | ||||||
Fallow/Idle Cropland | 61 | 68,594 | 84.1% | 15.9% | 0.840 | 67.7% | 32.3% |
0.676 |
Citrus | 72 3,974 58.5% 41.5% 0.585 75.1% 24.9% 0.751 | |||||||
Pecans | 74 | 2,706 76.6% 23.4% 0.766 49.9% 50.1% 0.499 | ||||||
Almonds | 75 | 23,975 86.3% 13.7% 0.863 86.5% 13.5% 0.865 | ||||||
Walnuts | 76 | 5,826 88.7% 11.3% 0.887 72.3% 27.7% 0.723 | ||||||
Pears | 77 | 293 | 56.0% | 44.0% | 0.560 | 52.6% | 47.4% | 0.526 |
Aquaculture | 92 | 4,555 | 85.3% | 14.7% | 0.853 | 80.7% | 19.3% | 0.807 |
Pistachios | 204 | 8,607 | 88.9% | 11.1% | 0.889 | 85.7% | 14.3% | 0.857 |
Triticale | 205 | 2,559 | 46.5% | 53.5% | 0.465 | 25.7% | 74.3% | 0.257 |
Carrots | 206 | 147 | 54.6% | 45.4% | 0.546 | 56.5% | 43.5% | 0.565 |
Asparagus | 207 | 17 | 34.0% | 66.0% | 0.340 | 54.8% | 45.2% | 0.548 |
Garlic | 208 | 144 | 66.4% | 33.6% | 0.664 | 76.6% | 23.4% | 0.766 |
Cantaloupes | 209 57 34.8% 65.2% 0.348 60.0% 40.0% 0.600 |
Prunes | 210 245 54.1% 45.9% 0.541 36.5% 63.5% 0.365 |
Olives | 211 479 73.6% 26.4% 0.736 45.7% 54.3% 0.457 |
Oranges | 212 3,617 61.0% 39.0% 0.610 58.5% 41.5% 0.585 |
Honeydew Melons | 213 2 10.5% 89.5% 0.105 11.1% 88.9% |
0.111 | |
Broccoli | 214 61 36.7% 63.3% 0.367 47.7% 52.3% 0.477 |
Avocados | 215 353 69.9% 30.1% 0.699 48.9% 51.1% 0.489 |
Peppers | 216 108 38.3% 61.7% 0.383 54.5% 45.5% 0.545 |
Pomegranates | 217 206 83.7% 16.3% 0.837 51.2% 48.8% 0.512 |
Nectarines | 218 | 1 | 5.3% | 94.7% | 0.053 | 14.3% | 85.7% | 0.143 | |
Greens | 219 | 63 | 39.1% | 60.9% | 0.391 | 40.9% | 59.1% | 0.409 | |
Plums | 220 | 20 | 14.6% | 85.4% | 0.146 | 5.7% | 94.3% | 0.057 | |
Strawberries | 221 | 26 | 15.7% | 84.3% | 0.157 | 45.6% 54.4% 0.456 | |||
Squash | 222 | 51 | 24.4% | 75.6% | 0.244 | 45.1% 54.9% 0.451 | |||
Apricots | 223 | 5 | 7.5% | 92.5% | 0.075 | 6.2% 93.8% 0.062 | |||
Vetch | 224 | 64 | 57.7% | 42.3% | 0.577 | 59.8% | 40.2% | 0.598 | |
Dbl Crop WinWht/Corn 0.485 Dbl Crop Oats/Corn | 225 226 | 1,796 315 | 46.1% 47.9% | 53.9% 52.1% | 0.460 0.479 | 48.5% 48.8% | 51.5% 51.2% | ||
0.488 Lettuce | 227 | 97 | 41.6% | 58.4% | 0.416 | 27.1% | 72.9% | 0.271 | |
Dbl Crop Triticale/Corn 0.618 | 228 1,841 | 47.0% | 53.0% | 0.469 | 61.8% | 38.2% | |||
Pumpkins 229 | 226 | 36.3% 63.7% | 0.363 57.1% 42.9% | 0.571 | |||||
Dbl Crop Lettuce/Durum Wht n/a | 230 | 0 0.0% | 100.0% 0.000 n/a | n/a | |||||
Shrubland | 64 | 18,064 | 72.3% | 27.7% | 0.723 | 49.2% | 50.8% | 0.492 | |
Cherries | 66 | 805 | 52.9% | 47.1% | 0.529 | 47.0% | 53.0% | 0.470 | |
Peaches | 67 | 597 | 45.5% | 54.5% | 0.455 | 48.4% | 51.6% | 0.484 | |
Apples | 68 | 2,715 | 63.5% | 36.5% | 0.635 | 74.8% | 25.2% | 0.747 | |
Grapes | 69 | 10,441 | 71.9% | 28.1% | 0.719 | 76.3% | 23.7% | 0.763 | |
Christmas Trees | 70 | 68 | 9.7% | 90.3% | 0.097 | 14.3% | 85.7% | 0.143 | |
Other Tree Crops | 71 | 275 | 30.8% | 69.2% | 0.308 | 44.0% | 56.0% | 0.440 | |
Dbl Crop Lettuce/Cantaloupe 0.903 Dbl Crop Lettuce/Cotton | 231 232 | 56 48.7% 51.3% 0.487 90.3% 9.7% 97 68.3% 31.7% 0.683 84.3% 15.7% | |||||
0.843 | |||||||
Dbl Crop Lettuce/Barley 0.250 Dbl Crop WinWht/Sorghum | 233 | 236 | 1 | 20.0% 80.0% 0.200 1,725 56.4% 43.6% | 25.0% 75.0% 0.564 33.3% 66.7% | ||
0.333 | |||||||
Dbl Crop Barley/Corn 0.579 Dbl Crop WinWht/Cotton | 237 238 | 187 407 | 39.0% 32.9% | 61.0% 67.1% | 0.390 0.329 | 57.9% 18.2% | 42.1% 81.8% |
0.182 Dbl Crop Soybeans/Cotton | 239 | 0 | 0.0% | 100.0% | 0.000 | n/a | n/a n/a |
Dbl Crop Soybeans/Oats | 240 | 160 | 29.5% | 70.5% | 0.295 | 37.0% | 63.0% |
0.370 | |||||||
Dbl Crop Corn/Soybeans | 241 | 31 | 32.6% | 67.4% | 0.326 | 48.4% | 51.6% |
0.484 | |||||||
Blueberries 242 | 368 | 45.4% | 54.6% | 0.454 | 39.1% | 60.9% | 0.391 |
Cabbage 243 | 90 | 49.2% | 50.8% | 0.492 | 46.9% | 53.1% | 0.469 |
Cauliflower 244 | 10 | 28.6% | 71.4% | 0.286 | 20.4% | 79.6% | 0.204 |
Celery 245 | 6 | 14.3% | 85.7% | 0.143 | 25.0% | 75.0% | 0.250 |
Radishes 246 | 28 | 46.7% | 53.3% | 0.467 | 50.9% | 49.1% | 0.509 |
Turnips 247 | 19 | 38.8% | 61.2% | 0.388 | 48.7% | 51.3% | 0.487 |
Eggplants 248 | 1 | 10.0% | 90.0% | 0.100 | 50.0% | 50.0% | 0.500 |
Gourds 249 | 3 | 17.6% | 82.4% | 0.176 | 60.0% | 40.0% | 0.600 |
Cranberries 250 | 18 | 17.6% | 82.4% | 0.176 | 69.2% | 30.8% | 0.692 |
Dbl Crop Barley/Soybeans | 254 | 433 | 47.5% | 52.5% | 0.475 | 63.0% | 37.0% |
0.630 |
*Correct Pixels represents the total number of independent validation pixels correctly identified in the error matrix.
**The Overall Accuracy represents only the FSA row crops and annual fruit and vegetables (codes 1-61, 66-80, 92 and 200-255).
FSA-sampled grass and pasture. Non-agricultural and NLCD-sampled categories (codes 62-65, 81-91 and 93-199) are not included in the Overall Accuracy.
The accuracy of the non-agricultural land cover classes within the Cropland Data Layer is entirely dependent upon the USGS, National Land Cover Database. Thus, the USDA NASS recommends that users consider the NLCD for studies involving non-agricultural land cover. For more information on the accuracy of the NLCD please reference <https://www.mrlc.gov/>.
Process
Process name
Date 2025-11-18 13:59:17
Tool location c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Conversion Tools.tbx\RasterToPolygon
Command issued
RasterToPolygon cdl_10m_r_ms_2024_utm16.tif Y:\ArcPro_Projects\Geoscience\Geoscience\MS_Cropland_2024\MS_Cropland_ 2024.gdb\RasterT_cdl_10m1 NO_SIMPLIFY Class_Name SINGLE_OUTER_PART 100
Include in lineage when exporting metadata No
Process
Process name
Date 2025-11-20 07:27:43
Tool location c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\Rename
Command issued
Rename Y:\MAPS\MS_Cropland_Data_2024\MS_Cropland_2024.gdb\RasterT_cdl_10m1 Y:\MAPS\MS_Cropland_Data_2024\MS_Cropland_2024.gdb\MS_CroplandFC_2024 FeatureClass
Include in lineage when exporting metadata No
Process
Process name
Date 2025-11-20 08:05:57
Tool location c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\UpdateSchema
Command issued
UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.5.0'><WorkspaceFact ory>FileGDB</WorkspaceFactory><Dataset>MS_CroplandFC_2024</Dataset><Da tasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection> "
<operationSequence><workflow><AddField><field_name>Categor_Code</field
_name><field_type>SHORT</field_type><field_is_nullable>True</field_is_ nullable><field_is_required>False</field_is_required></AddField></work flow></operationSequence>
Include in lineage when exporting metadata No
Process
Process name
Date 2025-11-20 12:28:52
Tool location c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Data Management Tools.tbx\DeleteField
Command issued
DeleteField MS_CroplandFC_2024 Categor_Code DELETE_FIELDS
Include in lineage when exporting metadata No
Process
Process name
Date 2025-11-21 09:21:49
Tool location c:\program files\arcgis\pro\Resources\ArcToolbox\toolboxes\Analysis Tools.tbx\Identity
Command issued
Identity MS_CroplandFC_2024 MS_CountyBoundaries_2015 Y:\ArcPro_Projects\Geoscience\Geoscience\MS_Cropland_2024\MS_Cropland_ 2024.gdb\MS_CroplandFC_2024_County ALL # NO_RELATIONSHIPS
Include in lineage when exporting metadata No
Distribution format
Name ⇔ File Geodatabase Feature Class
Distribution format
Name File geodatabase Version 11.5
Details for object MS_CroplandFC_2024_County ►
Type ⇔ Feature Class
Row count ⇔ 0
Field OBJECTID ► Alias ⇔ OBJECTID Data type ⇔ OID Width ⇔ 4
Precision ⇔ 0
Scale ⇔ 0
Field description ⇔
Internal feature number.
Description source ⇔
Esri
Description of values ⇔
Sequential unique whole numbers that are automatically generated.
Alias ⇔ Shape
Data type ⇔ Geometry
Width ⇔ 0
Precision ⇔ 0
Scale ⇔ 0
Field description ⇔
Feature geometry.
Description source ⇔
Esri
Description of values ⇔
Coordinates defining the features.
Field FID_MS_CroplandFC_2024 ► Alias ⇔ FID_MS_CroplandFC_2024 Data type ⇔ Integer
Width ⇔ 4
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ Id
Data type ⇔ Integer
Width ⇔ 4
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ gridcode Data type ⇔ Integer Width ⇔ 4
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ Class_Name Data type ⇔ String Width ⇔ 27
Precision ⇔ 0
Scale ⇔ 0
Field FID_MS_CountyBoundaries_2015 ►
Alias ⇔ FID_MS_CountyBoundaries_2015
Data type ⇔ Integer
Width ⇔ 4
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ AREA
Data type ⇔ Double
Width ⇔ 8
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ PERIMETER Data type ⇔ Double Width ⇔ 8
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ NEWSTCO_ Data type ⇔ Double Width ⇔ 8
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ NEWSTCO_ID Data type ⇔ Double Width ⇔ 8
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ COUNTY
Data type ⇔ SmallInteger
Width ⇔ 2
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ CONAME Data type ⇔ String Width ⇔ 15
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ CO_SEAT Data type ⇔ String Width ⇔ 40
Precision ⇔ 0
Scale ⇔ 0
Alias ⇔ Shape_Length Data type ⇔ Double Width ⇔ 8
Precision ⇔ 0
Scale ⇔ 0
Field description ⇔
Length of feature in internal units.
Description source ⇔
Esri
Description of values ⇔
Positive real numbers that are automatically generated.
Alias ⇔ Shape_Area Data type ⇔ Double Width ⇔ 8
Precision ⇔ 0
Scale ⇔ 0
Field description ⇔
Area of feature in internal units squared.
Description source ⇔
Esri
Description of values ⇔
Positive real numbers that are automatically generated.
Overview Description
Entity and Attribute Overview
he 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 most current version of the United States Geological Survey (USGS) National Land Cover Database (NLCD). 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.
f the following table does not display properly, then please visit the following website to view the original metadata at
<https://www.nass.usda.gov/Research_and_Science/Cropland/metadata/meta.php>.
Data Dictionary: USDA National Agricultural Statistics Service, Cropland Data Layer Source: USDA National Agricultural Statistics Service
The following is a cross reference list of the categorization codes and land covers. Note that not all land cover categories listed below will appear in an individual state.
Raster
Attribute Domain Values and Definitions: NO DATA, BACKGROUND 0
Categorization Code Land Cover "0" Background
Attribute Domain Values and Definitions: CROPS 1-60 Categorization Code Land Cover
"1" Corn
"2" Cotton
"3" Rice
"4" Sorghum
"5" Soybeans
"6" Sunflower
"10" Peanuts
"11" Tobacco
"12" Sweet Corn
"13" Pop or Orn Corn "14" Mint
"21" Barley
"22" Durum Wheat
"23" Spring Wheat
"24" Winter Wheat
"25" Other Small Grains
"26" Dbl Crop WinWht/Soybeans "27" Rye
"28" Oats
"29" Millet
"30" Speltz
"31" Canola
"32" Flaxseed
"33" Safflower
"34" Rape Seed
"35" Mustard
"36" Alfalfa
"37" Other Hay/Non Alfalfa "38" Camelina
"39" Buckwheat
"41" Sugarbeets
"42" Dry Beans
"43" Potatoes
"44" Other Crops
"45" Sugarcane
"46" Sweet Potatoes "47" Misc Vegs & Fruits "48" Watermelons
"49" Onions
"50" Cucumbers
"51" Chick Peas
"52" Lentils
"53" Peas
"54" Tomatoes
"55" Caneberries
"56" Hops
"57" Herbs
"58" Clover/Wildflowers
"59" Sod/Grass Seed
"60" Switchgrass
Raster
Attribute Domain Values and Definitions: NON-CROP 61-65
Categorization Code Land Cover "61" Fallow/Idle Cropland
"62" Pasture/Grass
"63" Forest
"64" Shrubland
"65" Barren
Raster
Attribute Domain Values and Definitions: CROPS 66-80
Categorization Code Land Cover "66" Cherries
"67" Peaches
"68" Apples
"69" Grapes
"70" Christmas Trees "71" Other Tree Crops "72" Citrus
"74" Pecans
"75" Almonds
"76" Walnuts
"77" Pears
Raster
Attribute Domain Values and Definitions: OTHER 81-109
Categorization Code Land Cover "81" Clouds/No Data
"82" Developed
"83" Water
"87" Wetlands
"88" Nonag/Undefined
"92" Aquaculture
Raster
Attribute Domain Values and Definitions: NLCD-DERIVED CLASSES 110-195
Categorization Code Land Cover "111" Open Water
"112" Perennial Ice/Snow
"121" Developed/Open Space
"122" Developed/Low Intensity
"123" Developed/Med Intensity
"124" Developed/High Intensity
"131" Barren
"141" Deciduous Forest
"142" Evergreen Forest
"143" Mixed Forest
"152" Shrubland
"176" Grassland/Pasture
"190" Woody Wetlands
"195" Herbaceous Wetlands
Raster
Attribute Domain Values and Definitions: CROPS 195-255
Categorization Code Land Cover "204" Pistachios
"205" Triticale
"206" Carrots
"207" Asparagus
"208" Garlic
"209" Cantaloupes
"210" Prunes
"211" Olives
"212" Oranges
"213" Honeydew Melons
"214" Broccoli
"215" Avocados
"216" Peppers
"217" Pomegranates
"218" Nectarines
"219" Greens
"220" Plums
"221" Strawberries
"222" Squash
"223" Apricots
"224" Vetch
"225" Dbl Crop WinWht/Corn "226" Dbl Crop Oats/Corn "227" Lettuce
"228" Dbl Crop Triticale/Corn "229" Pumpkins
"230" Dbl Crop Lettuce/Durum Wht "231" Dbl Crop Lettuce/Cantaloupe "232" Dbl Crop Lettuce/Cotton "233" Dbl Crop Lettuce/Barley
"234" Dbl Crop Durum Wht/Sorghum "235" Dbl Crop Barley/Sorghum "236" Dbl Crop WinWht/Sorghum "237" Dbl Crop Barley/Corn
"238" Dbl Crop WinWht/Cotton "239" Dbl Crop Soybeans/Cotton "240" Dbl Crop Soybeans/Oats "241" Dbl Crop Corn/Soybeans "242" Blueberries
"243" Cabbage
"244" Cauliflower
"245" Celery
"246" Radishes
"247" Turnips
"248" Eggplants
"249" Gourds
"250" Cranberries
"254" Dbl Crop Barley/Soybeans
Metadata language ⇔ English (UNITED STATES)
Scope of the data described by the metadata ⇔ dataset
Scope name ⇔ dataset
Last update ⇔ 2025-11-21 ArcGIS metadata properties
Metadata format ArcGIS 1.0
Standard or profile used to edit metadata ISO19115_3
Created in ArcGIS for the item 2025-11-18 13:59:17
Last modified in ArcGIS for the item 2025-11-21 10:55:24
Automatic updates
Have been performed Yes
Last update 2025-11-21 08:10:16
Metadata contact - originator
Individual's name Staff
Organization's name United States Department of Agriculture (USDA) National Agricultural Statistics Service (NASS)
Address
Type physical
Delivery point USDA NASS Marketing and Information Services Office, Washington, D.C. Contact instructions
Maintenance
Update frequency unknown
Constraints
Limitations of use
The USDA NASS Cropland Data Layer and the data offered on the CroplandCROS website 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.