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The geospatial data product called the Cropland Data Layer (CDL) is hosted on CropScape ( ). The CDL is a raster, geo-referenced, crop-specific land cover data layer created annually for the continental United States using moderate resolution satellite imagery and extensive agricultural ground truth. All historical CDL products are available for use and free for download through CropScape. For more information about the CDL Program please refer to the metadata for the particular state and year you are interested at the following web page: (/Research_and_Science/Cropland/metadata/meta.php).
The Cropland Data Layer (CDL) was created by the USDA, National Agricultural Statistics Service, Research and Development Division, Geospatial Information Branch, Spatial Analysis Research Section. The most current data is available free for download along with extensive metadata, FAQs, and other detailed technical information at the following website: /Research_and_Science/Cropland/SARS1a.php. NASS developed both the CropScape and VegScape web services in cooperation with the Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA.
Zoom to the national scale map, choose the year that you want to download and click on the "Download Defined Area of Interest Data" button on the toolbar. Respond "yes" to the download confirmation question. The downloadable file will be a Winzip compressed file containing the CDL in a GeoTIFF (TIF) file format. As an alternative to CropScape, a national CDL mosaic in an Erdas Imagine IMG file format is available for download on the SARS National Download webpage.
The following downloadable jpeg files are color legends by year for the Continental United States CDLs: US_2022_CDL_legend.jpg US_2021_CDL_legend.jpgUS_2020_CDL_legend.jpgUS_2019_CDL_legend.jpgUS_2018_CDL_legend.jpgUS_2017_CDL_legend.jpg US_2016_CDL_legend.jpg US_2015_CDL_legend.jpg US_2014_CDL_legend.jpg US_2013_CDL_legend.jpg US_2012_CDL_legend.jpg US_2011_CDL_legend.jpg US_2010_CDL_legend.jpg US_2009_CDL_legend.jpg US_2008_CDL_legend.jpg
The strength and emphasis of the CDL is crop-specific land cover categories. The accuracy of the CDL non-agricultural land cover classes is entirely dependent upon the USGS, National Land Cover Database (NLCD). Thus, the USDA, NASS recommends that users consider the NLCD for studies involving non-agricultural land cover.The training and validation data used to create and accuracy assess the CDL has traditionally been based on ground truth data that is buffered inward 30 meters. This was done 1) because satellite imagery (as well as the polygon reference data) in the past was not georeferenced to the same precision as now (i.e. everything "stacked" less perfectly), 2) to eliminate from training spectrally-mixed pixels at land cover boundaries, and 3) to be spatially conservative during the era when coarser 56 meter AWiFS satellite imagery was incorporated. Ultimately, all of these scenarios created "blurry" edge pixels through the seasonal time series which it was found if ignored from training in the classification helped improve the quality of CDL. However, the accuracy assessment portion of the analysis also used buffered data meaning those same edge pixels were not assessed fully with the rest of the classification. This would be inconsequential if those edge pixels were similar in nature to the rest of the scene but they are not as they tend to be more difficult to classify correctly. Thus, the accuracy assessments as have been presented are inflated somewhat.Beginning with the 2016 CDLs we published both the traditional "buffered" accuracy metrics and the new "unbuffered" accuracy assessments. The purpose of publishing both versions is to provide a benchmark for users interested in comparing the different validation methods. For the 2017 CDL season we are now only publishing the unbuffered accuracy assessments within the official metadata files and offer the full "unbuffered" error matrices for download on this FAQs webpage. We plan to continue producing these unbuffered accuracy assessments for future CDLs. However, there are no plans to create these unbuffered accuracy assessments for past years. It should be noted that accuracy assessment is challenging and the CDL group has always strived to provide robust metrics of usability to the land cover community. This admission of modestly inflated accuracy measures does not render past assessments useless. They were all done consistently so comparison across years and/or states is still valid. Yet, by now providing both scenarios for 2016 gives guidance on the bias.The full error matrices are included in the downloadable links below.
To create a pixel "count" field in the attribute table of the downloaded CDL use the "Build Raster Attribute Table" Function in ESRI ArcGIS. In ESRI ArcGIS Version 9.3 and 10 this function is located at ArcToolbox > Data Management Tools > Raster > Raster Properties > Build Raster Attribute Table. Specify the downloaded CDL tif file as the Input Raster and accept all other defaults and click OK. After it has run successfully, a new "Count" data field is added to the attribute table. Count represents a raw pixel count. To calculate acreage multiply the count by the square meters conversion factor which is dependent upon the CDL pixel size. The conversion factor for 30 meter pixels is 0.222394. The conversion factor for 56 meter pixels is 0.774922.
You first must build statistics for the TIF file as outlined in the question above. To add category names, open the TIF in a Viewer and select Raster > Attributes. In the Raster Attribute Editor select Edit > Add Class Names. This new "Class Names" column can be populated manually or you can download this prepared DAT file located at: /Research_and_Science/Cropland/docs/cdl_class_names.zip. Unzip the CDL names and colors file and save the DAT files to your computer. Then in the Raster Attribute Editor highlight the "Class Names" column by left-clicking on the header of the Class Names column. Next, right-click on the Class Names column and select the Import option. Specify the CDL_Names DAT file as the file to import and this will add all possible CDL class names to your TIF attribute table. You can add colors by importing the CDL_Colors DAT file similar to the steps used to add the class names.
CropScape allows users to analyze and interact with areas less than 2,000,000 square kilometers. However, users can download the entire national CDL by year by following the instructions in this FAQ question in this FAQ question (Click Here) which could then be used to perform analysis using their own GIS or image processing software.
This issue is caused by security controls of Internet Explorer when rendering a state with a large boundary file, which can take a long time depending on your internet connection speed. There are three possible solutions: Solution 1: If you get a window that says "...Do you want to abort the script?", click the "NO" button to continue. Solution 2: Follow the technical support at to download a patch and fix this problem automatically. Solution 3: Try using another browser, such as Firefox, Safari, or Google Chrome.
The CropScape/CDL data are in raster format. Raster data layer is one layer with all crop types in the same layer. Therefore, WMS map has only one layer. You cannot use layerDefs and SLD in WMS to extract individual crop land cover. If you want to extract the individual crop cover, you have to download the CDL data and then extract crop type by specific attribute value(s).
If you receive a "HTTP Error 500", then check that you are using a static link rather than dynamic. If you are using BOX then this link may help with creating a static link ( -Forum/How-to-mass-download-Static-Share-Links/td-p/11973).
CropScape currently does not have the capability to create PDF maps with only one specific crop or group of crops shown. However, the user can export the actual CDL data with only a single crop or subset of crops in a Geotiff (TIF) format using the CropScape "Area of Interest Statistics" tool. That downloaded data can then be used to create a more polished PDF map using ESRI ArcGIS software. Below are the procedures:1.Select your area of interest;2.Use the "Area of Interest Statistics" tool to calculate statistics;3.Check the box of the crop type(s) you wish to display in the pop-up statistical result window;4.Click "Export the selected crop(s) for mapping";5.Click the "Download" button to download the resulting image in a Geotiff (TIF) file format;6.Load the downloaded TIF file in ArcGIS where you can then add additional data, such as boundaries and/or legends, to create your own map that can then be exported to a PDF file. 2b1af7f3a8