Interactive map
Interactive map for United States County Cropland Data Layer. Use the map controls to pan and zoom.
US County Mapper
Geography: United States counties
Dataset last updated:
About This Data Source
This interactive mapping tool is designed to help users explore and visualize GIS data derived from the USDA National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL). The CDL provides annual, georeferenced land cover data across the United States, allowing users to analyze crop distribution, land use patterns, and agricultural trends over time.
What you can do
- Visualize cropland data by mapping crop types and land cover classifications across states, counties or regions.
- Analyze agricultural patterns such as crop dominance, land use changes, and regional differences.
- Explore multiple years of data to identify trends and shifts in agricultural production.
- Export maps as images for use in reports, presentations, or research projects.
Map views explained
- Regions view displays categorized land cover or crop type data by county or region. This view is best for precise comparisons and reporting.
- Surface view generates a smoothed visualization of agricultural patterns, helping users identify broader spatial trends such as crop concentration and transition zones.
Using the data
The Cropland Data Layer is available as raster-based GIS data and can be integrated with tabular datasets (such as CSV or Excel files) for enhanced analysis. Each dataset typically includes geographic identifiers (e.g., county boundaries or FIPS codes) and categorized land cover values.
Advanced users can incorporate additional data attributes or customize visualization settings to refine map outputs, including classification schemes, legend formatting, and display options.
Important notes
- This tool is intended for visual exploration and communication of agricultural land use data.
- The Cropland Data Layer is produced using satellite imagery and classification algorithms; therefore, some classification errors may occur.
- Surface visualizations are generalized representations and should not be interpreted as exact values between mapped regions.
- Data availability and accuracy may vary by year and geographic area.
Additional resources, including metadata, classification details, and user guides for the Cropland Data Layer, are available through the USDA NASS website.
Suggested citation
Royal, K (2026). United States County Cropland Data Layer [Interactive map]. CU-CAT Maps, Clemson University Center for Agricultural Technology. Retrieved August 23, 2026, from https://maps.cuagtech.com/us-county-cdl/
Kevin Royal
Platform and data responsibility
CU-CAT Maps is developed and hosted by the Clemson University Center for Agricultural Technology (CU-CAT), in partnership with Clemson Cooperative Extension Service.
CU-CAT provides the mapping platform. The hosted dataset and dataset-specific content presented on this page are maintained by Kevin Royal. CU-CAT's role in creating, verifying, or maintaining hosted data varies by page. For questions about the data presented here, contact Kevin Royal.
CU-CAT Maps and its maps, reports, and results are provided as-is for informational purposes. Accuracy and completeness are not guaranteed. Users are responsible for evaluating the source data and outputs and assume the risks arising from their use. See the Terms of Use.
Have feedback about CU-CAT Maps, want to discuss whether a dataset may be a good fit for the platform, or have a dataset or topic you would like to see mapped? Email CU-CAT. Hosting and support depend on alignment with CU-CAT's mission, project scope, and available capacity.
© 2025-2026 Clemson University Center for Agricultural Technology (CU-CAT) and Clemson Cooperative Extension Service
Use the controls above the map to choose what to display, how to display it, and what to save or report.
Start with the data
- Choose a dataset. Most pages open with a hosted dataset. Pages with an Upload data control also let you select an Excel or CSV file for your current browser session.
- Choose a sheet. The Sheet selector appears when the dataset contains more than one available worksheet.
- Choose a variable. The Variable selector lists the columns that can be mapped. Changing the variable updates the map, legend, popups, and reports.
Choose a map view
Regions
Regions colors each mapped area according to its value or category. Use it for exact regional comparisons, popups, labels, and reporting.
Surface
Surface estimates a continuous pattern from values associated with the mapped regions. Use it to explore broad spatial trends rather than to infer exact values between regions.
Start simply: choose the view and variable first. Open Advanced only when you need to adjust classification, colors, opacity, interpolation, or other display settings.
Explore the map
- Pan and zoom as you would on a standard online map.
- In Regions view, select a region to inspect its popup. The popup may also offer a report for that region.
- In Surface view, turn on points when you need to see the observations used to create the surface.
- Use the legend to interpret colors, ranges, units, totals, averages, and areas without data.
Reports and exports
- Attribute report: compares regions for the selected variable. Sort a report table before exporting when order matters.
- Region report: available from a region popup in Regions view and compares variables for that region.
- Copy map: copies the map image when the browser supports image copying.
- Download map: saves the map as a PNG image.
- Share: shares or copies the page link. It does not currently preserve the selected map settings.
Exported map images include the data layers and legend but omit third-party basemap tiles.
Interpret with care
- Check the units and source information supplied in the About tab.
- Do not assume a missing value means zero unless the dataset supports that interpretation.
- Surface maps are generalized visualizations. Classification, smoothing, clipping, and interpolation settings can change their appearance.
- When duplicate rows are present, averaging and summing answer different questions. Use the method appropriate for the data.