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U.S. Department of Agriculture National Agricultural Statistics Service Research and Development Division |
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U.S. Department of Agriculture National Agricultural Statistics Service Research and Development Division |
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of the Director |
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Cropland Data Layer Frequently Anticipated Questions Distribution
Technical Details
Previously Asked User Questions
Distribution Where can I obtain the Cropland Data Layer (CDL) and what is the cost? The entire inventory of CDL products are available free via download through the USDA NRCS Geospatial Data Gateway. The most recent CDL products are also available free for download through the USDA NASS Cropland Data Layer website. The CDL inventory can also be purchased on CD/DVD for the cost of reproduction using the CDL Order Form. The purchasable official CD/DVD contains a readme file in a text file and html format at the root of the CD/DVD that details the content. The CDL CD/DVD contains categorized imagery in two file formats: GeoTIFF (.tif) and ERDAS Imagine (.img). Two geographic projections are included on the CD/DVD: Albers Equal-Area Conic and Universal Transverse Mercator (UTM). The CD/DVD also includes metadata, image legend, and a 'confidence layer.' Prior to crop year 2007, the CD/DVD products contained the most recent two years of CDL products along with ancillary GIS data layers. Beginning with the 2007 CDL, all successive CD/DVD products contain a single year of categorized imagery and no ancillary GIS data due to space limitations. We suggest visiting the National Atlas to obtain ancillary GIS data. The NASS Agricultural Statistics Districts (ASD) are available online in an ESRI shapefile file format from the following link: ASD zip file. The most recent set of CDL products are available free for download through the NASS CDL website. The downloads are typically in a single WinZIP file and contain the CDL imagery in GeoTIFF (.tif) and ERDAS Imagine (.img) file formats projected in UTM, along with the metadata, which includes accuracy assessments, and the confidence layers. 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 WinZIP 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. The zip file will include all years of CDL data for the requested state in a GeoTIFF (.tif) file format projected in UTM, along with the accompanying metadata, accuracy assessment information and image legend. Below are instructions for downloading from the NRCS Geospatial Data Gateway (http://datagateway.nrcs.usda.gov/): 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. The CDL is used for acreage estimation purposes during the growing season. However, due to confidentiality issues, the CDL is not published until after the growing season and after the official NASS state estimates have be released. Currently, this means that the CDL is published in March of the year following. We are working to offer the CDL in December of the same year to increase the usefulness of the data. The CDL program became operational with two states (Arkansas and North Dakota) in 1997 and has expanded rapidly, especially in recent years. Please visit the Examples Section of the CDL website for sample graphics of all of the states and years of available CDL data. The purchasable official CD/DVD contains the CDL categorized imagery in two file formats: GeoTIFF (.tif) and ERDAS Imagine (.img). The GeoTIFF will have three files associated with it: .tif, .tfw, and .aux. The ERDAS Imagine format will have two files associated with it: .img and .rrd. The image legends are offered in a JPEG (.jpg) format. The metadata is offered in a HTML (.htm) format. Two geographic projections are included on the CD/DVD: Albers Equal-Area Conic with a spheroid of GRS 1980 and datum of NAD83 and the dominant Universal Transverse Mercator (UTM) zone with a spheroid and datum of WGS84. The native projection used to create the CDL is Albers. The CDL is reprojected to UTM as a final processing step in order to conform to NRCS Geospatial Data Gateway requirements. The one exception to UTM is for
Wisconsin. Wisconsin is projected using the Wisconsin Transverse
Mercator (WTM) projection. This WTM projection is based on the 1991
adjustment to NAD83, and is called WTM83/91. Projection parameters and
additional information about WTM83/91 is posted on the DNR
website: http://www.dnr.state.wi.us/maps/gis/wtm8391.html. 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. 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. If you already have GIS capability, you should have no trouble working with the CDL datasets. If you do not have software capable of viewing Geotiff (.tif) or ERDAS Imagine (.img) file formats then we suggest using the freeware browser ESRI ArcReader. Some users have reported issues with viewing the CDL using ENVI software. NASS suggests using the GeoTIFF file format with ENVI and ensuring that the three associated files (.tif, .tfw, and .aux) are all kept together. Originally, field preparation and digitizing work were performed in NASS Field Offices, and the remote sensing analysis performed by the Remote Sensing Section later called the Spatial Analysis Research Section (SARS) of NASS. However, in 1997 SARS entered into a data sharing partnership with USDA's Foreign Agricultural Service and USDA's Farm Service Agency. The agreement provided access to Landsat 5 coverage in the states selected for the project by SARS. The first states covered with the data sharing partnership were Arkansas, North Dakota and South Dakota. Improvements in hardware along with software enhancements made program expansion possible for the 1999 growing season. NASS Research & Development Division solicited additional states to find outside cooperators/partners to provide an analyst and hardware to perform duties associated with the Acreage Estimation Program. The Illinois and Mississippi State Field Offices were able to obtain partnership agreements with external State/Federal Agencies. For crop year 2000, the states of Iowa and Indiana were added to the Program. North Dakota was able to obtain a partner for the 2000 crop year cooperatively with NDSU through an EPA water quality grant for 5 years. Indiana was added to the program for crop year 2000 also, but as a regional type center where the ground data collection, and digitization was performed at the Indiana State Office, and the acreage estimation was performed at the Illinois State Office. For crop year 2001, the Missouri boot heel area was added to the program. All boot heel digitizing was performed by the Missouri Ag Statistics Service, and image processing duties were performed by the Arkansas Ag Statistical Service. Nebraska and Wisconsin were added as pilot states, where all digitizing was performed by the Nebraska and Wisconsin Ag Statistics Service offices respectively, and image processing functions were performed by SARS. Maryland/Delaware were also added as a pilot program where digitizing was done by the Univ. MD Mid-Atlantic RESAC group, and image processing was performed by the SARS group. For crop year 2002, Nebraska expanded to full state coverage, and Wisconsin expanded to full state coverage in 2003. The 2002 10 State Mid-Atlantic based Cropland Data Layer product was sponsored in part by a NASA/Raytheon/Synergy Project through Towson University, with the digitizing and image analysis performed under contract by NASS. The Mid-Atlantic CDL products were based on the 2002 June Agricultural Survey and the Agriculture Coverage Evaluation Survey (ACES) that coincided with the 2002 Agricultural Census. For crop year 2004, the IRS Resourcesat-1 AWiFS sensor was used over Nebraska, Indiana and Arkansas to perform acreage analysis. The AR, IN and NE CDL's were released with both Landsat TM classifications as well as AWiFS classifications. The AWiFS sensor has 56 meters multispectral resolution, and five day repeat coverage. The best possible scene dates taken during the month of August 2004 were used to create the AWiFS CDL products. The AWiFS scenes were orthorectified to a resampled EarthSat GeoCover base of 56 meters. A Florida CDL for 2004 was released in February of 2007 using Landsat 5/7 imagery. The Florida CDL was the first CDL created exclusively with See5, and it was the first usage of the segmentation based gap filled Landsat-7 SLC-off imagery. It included the first usage of the Farm Service Agency/Common Land Unit and the Florida Citrus Grove layer for ground truth training. A cooperative partnership between Univ. of MD/Dept of Geography and SARS helped process the Louisiana 2004 CDL. For crop year 2005, the Idaho Cropland Data Layer was created with a cooperative partnership between a Utah State University, the United Potato Growers of Idaho and NASS. This partnership produced both a Landsat TM and Resourcesat-1 AWiFS classification over the Idaho Snake River Plain. The 2005 Midwestern CDL DVD update, contained new AWiFS classifications and a revised Wisconsin TM based classification. The new AWiFS classifications cover Nebraska and North Dakota. The Wisconsin revision was performed under contract for the Wisconsin State, Bureau of Environmental & Occupational Health and Department of Health and Family Services. The Wisconsin CDL is now a complete statewide classification that is nearly cloud free, additional small acreage crops are identified and the non-ag land uses across the state are better defined. The 2005 Mississippi Delta CDL DVD product contains four states: Arkansas, Louisiana, Mississippi and the Missouri (bootheel). This is truly a unique product where the intensely cultivated Delta Region was classified using regression tree classifier See5.0 available from www.rulequest.com over the 2001 NLCD defined mapping Zone 45 http://www.mrlc.gov/ for the States of Arkansas, Louisiana and Missouri. The Zone 45 classification results from See5.0 were overlaid on top of the Arkansas, Louisiana and Missouri bootheel, resulting in an accurate ag classification and an enhanced non-ag land use classification leveraging results from the 2001 NLCD products. The traditional pixel based PEDITOR classification covers the remaining parts of these states. Additionally, 2005 AWiFS classifications of these four states are provided as well. The 2006 Delta/Midwestern/Pacific Northwest CDL products covered eleven states: AR, IL, IN, IA, LA, MO, MS, NE, ND, WA, WI. Illinois and Indiana were processed with Peditor. The remaining States were processed using See5 decision tree software. The Mississippi Delta CDL and the remaining Midwestern and Prairie States were processed exclusively with See5 using the FSA Common Land Unit for ground truth. The 2007 CDL product became operational in NASS delivering for the first time in-season acreage estimates for the October 2007 Crop Report across all speculative corn and soybean states. Twenty-one states total (AR, CA, IL, IN, IA, ID, KS, LA, MI, MN, MO, MS, MT, ND, NE, OH, OK, OR, SD, WA, WI) were processed into CDL's, a new record for the program. Additionally, new CDL's were created for crop year '06 for KS, MN, MO, OH, OK, SD. Michigan State University/Land Policy Institute entered into a cooperative partnership with SARS obtained funding to provide an image analyst to process Michigan. The 2008 crop year produced real-time CDL acreage estimates for the June Ag Survey for winter wheat, the August Crop Report and the October Crop Report for corn and soybeans. Eighteen states (AR, CO, IA, IL, IN, KS, LA, MI, MN, MO, MS, OH, OK, ND, NE, SD, TX, WI) were processed during the crop year with additional CDL production possible over the Southeastern and Southwestern US. The CDL was created as an offshoot of the Acreage Estimation Program, which was historically used for its statistical methodology and ability to derive acreage estimates. Functionality was extended to GIS mapping in the late 1990's. The CDL product provides orthorectified data for agribusiness and researchers in the GIS and remote sensing communities. The CDL is available free for download through the Geospatial Data Gateway. Yes, the NASS Cropland Data Layer has no copyright restrictions. The CDL is considered public domain and free to redistribute. However, NASS would appreciate acknowledgment for the usage of our CDL product. Metadata for the entire CDL inventory is stored online by state and year. The metadata is created from software produced by the USGS and can be found at http://geology.usgs.gov/tools/metadata/. The metadata files contain information on the sensor types, dates of observation, and the accuracy statistics, such as percent correct, user and producer accuracy and kappa coefficients. The accuracy statistics are for agricultural land cover classes only. The accuracy of the non-agricultural land cover classes within the Cropland Data Layer are entirely dependent upon the USGS, National Land Cover Dataset (NLCD 2001). We recommend that users consider the NLCD for studies involving non-agricultural land cover. For more information please reference the NLCD. Please visit the NASS CDL website for updates on the proposed CDL states for the upcoming year. The CDL Program remains focused on the major crops of the Midwest and Mississippi Delta regions: corn, soybeans, rice and cotton. We are now working to expand the CDL Program to include the major wheat states of the Great Plains region. Distribution issues can be directed to the NASS Customer Service Hotline at 1-800-727-9540. Content questions can be directed to the NASS Spatial Analysis Research Section (SARS) at 703-877-8000 or email HQ_RDD_GIB@nass.usda.gov.
Technical Details The classification process used to create the CDL prior to 2006 was based on a maximum likelihood classifier approach using an in-house software package. The CDL relied mainly on data from the Landsat TM/ETM satellite which had a 16-day revisit. And the in-house software limited the use of only two scenes per classification. The only available ground truth was through the NASS June Area Survey (JAS). The JAS data was collected by field enumerators so it was fairly accurate but was limited in coverage due to the cost and time constraints of such a massive survey. It was also very labor intensive to digitize and label all of the collected field data for use in the classification process. Non-agricultural land cover was based solely on image analyst interpretation. Beginning in 2006, we began using a new satellite sensor, new software, more extensive training/validation data, and began using the NLCD to help identify non-agricultural land cover. The in-house software was phased out in favor of a commercial software suite. This improved processing efficiency and, more importantly, allowed for unlimited classification inputs. Combined with the rapid revisit of the AWiFS satellite sensor, this has nearly eliminated cloud contamination issues that plagued the CDL products prior to 2006. The new satellite is the AWiFS sensor that is on the Resourcesat-1 satellite. It has a resolution is 56 meters, or .77 acres, and revisits the same area approximately every 5 days. We are now collecting AWiFS data year round and supplement the CDL classification process with MODIS data. We now use USDA Farm Service Agency (FSA) Common Land Unit (CLU) data for training our classifier in the agricultural domain. We use the USGS NLCD 2001 dataset to train over the non-agricultural domain. The new methodology uses a decision tree classifier as opposed to the maximum likelihood classifier. 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. Prior to the 2006, the CDL processing was done entirely with in-house maintained software called PEDITOR. The PEDITOR classification was based on a maximum likelihood classifier. Limitations to the software also made it impossible to use more than two satellite scenes per classification, which was a significant hindrance when trying to minimize cloud coverage. Beginning with the 2006 CDL products, the CDL program phased out the use of PEDITOR and transitioned to a commercial software suite. 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. The CDL Program uses medium resolution satellites. CDL products prior AWiFS to 2006 relied primarily on Landsat 4/5/7. Beginning with the 2006 CDL products, the CDL program transitioned to using the senor on the IRS-P6 Resourcesat-1 satellite. Currently, it is too costly to use higher resolution satellites to perform crop acreage estimation over large areas. Beginning in 2006, the MODIS, 250 meter resolution 16-day composite Normalized Difference Vegetation Index (NDVI) from the NASA Terra satellite is used as an ancillary input to the CDL classification process. Beginning with the 2006 CDL products, detailed accuracy assessment tables are published within the official metadata files. Generally, the dominant agricultural crop types have accuracies ranging from mid 80% to mid 90%. The accuracy tables for 2005 CDL products and older were published on the official CD/DVD in an accompanying “stats” file in an htm file format. The “stats” files are also included in the free downloadable zip files from the NRCS Geospatial Data Gateway. Western Arkansas and Northern Missouri were not fully covered in the program until crop year 2006. Cloud coverage, during any given year, may limit the extent of the area coverage. However, beginning in crop year 2006, the CDL Program transitioned from using the Landsat TM/ETM satellite to AWiFS. The high revisit rate of the AWiFS sensor has reduced issues with cloud coverage so most CDL states will be cloud-free and full state coverage where possible. Prior to 2006, the Landsat TM/ETM categorized images were co-registered to MDA/EarthSat Inc's ortho-rectified GeoCover Stock Mosaic images using automated block correlation techniques. The resulting correlations were applied to each categorized image and then added to a master image or mosaic using NASS' in-house software, PEDITOR. The GeoCover Stock Mosaics are within 50 meters root mean squared error overall. See MDA/EarthSat's http://www.mdafederal.com/home website for further details. The AWiFS images purchased beginning in 2005 were all orthorectified by GeoEye, so NASS does not ortho correct the AWiFS-based CDL imagery. The CDL retains 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 AWiFS distance. The following presentations related to the spatial accuracy of the imagery were presented at the 2007 FAS PECAD Seminar by Mary Pagnutti and Gyanesh Chander. Distribution issues can be directed to the NASS Customer Service Hotline at 1-800-727-9540. Content questions can be directed to the NASS Spatial Analysis Research Section (SARS) at 703-877-8000 or email HQ_RDD_GIB@nass.usda.gov.
Previously Asked User Questions The simple answer is no. As explained in the Program Methodology section, NASS adjusts the CDL results by using a regression estimator and ground gathered data from farm operators. The farmer reported data is strictly confidential and only available to NASS employees in a secure NASS site location. The regression estimates are only one input to official state and county crop acreage estimates. In addition to regression estimates, NASS staff use the results of farmer reported data from surveys, Farm Service Agency data where available, agri-business data and the Census of Agriculture data. Thus, the official estimate is the single best number that NASS can come up with giving all of the inputs some representation. The one major advantage of the classified data is that it is available at a geographic level well below the county level. However, it is possible to pixel count and return acreage numbers close to the official estimate, but pixel counting does not account for cloud covered areas as well as the inaccuracies associated with a pixel based classification. NASS
says this is a Cropland data layer product, what about the areas that
are not agriculturally intensive?
The strength of the CDL is in its agricultural classifications. Due to the extensive agricultural training data provided by the FSA, CLU Program, the major crop types for a CDL state will normally have a classification accuracy of 85% to 95%. However, the FSA CLU data does not contain much, if any, non-agricultural data. The only source of non-ag training available at the scale required to meet the needs of the CDL Program is the USGS 2001 National Land Cover Dataset (NLCD). We sample the non-ag categories of the NLCD proportionate to the available FSA CLU data for a state and include this in the CDL classification process. Thus, the accuracy of the non-agricultural land cover classes within the Cropland Data Layer are entirely dependent upon the NLCD. We recommend that users consider the NLCD for studies involving non-agricultural land cover. For more information please reference the NLCD. The FSA CLU data does contain a small amount of nonagricultural data and this nonag FSA data was used in the classification process. Thus, there are some 2007 CDL states that may have multiple categories for the same nonag land cover type, such as category 87 (FSA-sampled wetland) and category 190 and 195 (NLCD-sampled wetlands). This is should only be an issue in the 2006 and 2007 CDL products. Beginning in 2008, the use of the FSA CLU non-ag for classification training was discontinued. Prior to 2006, the field level training data was collected solely through the June Agricultural Survey (JAS). The JAS is an annual national survey of randomly selected areas of land. The selected areas are targeted toward cultivated parts of each state based on its area frame. Our enumerators are given questionnaires to ask the farmers what, where, when and how much are they planting. Our surveys focus on cropland, but the enumerators record all land covers within the sampled area of land whether it is cropland or not. NASS uses broad land use categories to define land that is not under cultivation, including; non-agricultural, pasture/rangeland, waste, woods, and farmstead making it difficult to know what specific type of land use/cover actually is on the ground. Thus, non-agricultural land cover contained within the 2005 and older CDL products were based solely on an individual analyst’s best interpretation. Does
the CDL differentiate between grassland types such as pasture, urban
grassland, CRP grassland and other grass-related land cover types?
Unfortunately, the grassland-related categories have traditionally had very low classification accuracy in the CDL. This is an issue of land use versus land cover. The satellite sensor and classification process can only identify land cover types. It cannot differentiate specific land uses, such as urban open space, shrubland, pasture for grazing, or CRP. We continue to search for program enhancements and ancillary datasets that may help improve the identification of grassland and pasture categories within the CDL. Differences in the CDL can also arise from the use of the NLCD Pasture/Hay category. We use Farm Service Agency (FSA) to identify the ag land cover and the NLCD to identify the nonag. So, we ignore NLCD code 82 (Cultivated Crops) during the CDL classification process. It is left up to the individual analyst for a specific CDL state as to whether or not to use the NLCD code 81 (Pasture/Hay). Typically, it is used for training because there is not much pasture or hay available in the FSA data in these areas. In states where there is a lot of pasture/hay in the FSA data, such as the Great Plains States, then the analysts typically ignore NLCD code 81 and rely entirely on the FSA data to identify pasture/hay categories. How
do I determine how much area of a certain crop is grown within a
certain radius of a given location?
A user can summarize the area of a certain crop within a certain radius, but they should be aware of the potential limitations of pixel counting. Most land cover classification datasets will contain some level of counting bias (typically downward). There is also the issue of potential cloud contamination or incomplete state coverage. We make our best efforts to keep the major and minor crop classes (class names and category numbers) for a state consistent throughout; however, there may be inconsistencies/errors in the minor crop types, either historically or currently. CDL products prior to 2006 were dependent upon the NASS June Area Survey for ground truth. Attribute codes 50 – 59 were reserved for those state specific small area crops recorded in the JAS, which we do not use or even have access to anymore. So, our minor classes may have changed a little, we've enhanced our non-ag coverage and the quality of our program has grown and has now reached a stable point, partly since we have covered most all of the large ag intensive states, as it is difficult to account for all crop types that are grown across the US in a single product that keeps expanding and our method has matured with decision tree analysis. We will continue to strive to make our products more consistent. Please reference the Attribute Section of the metadata file for the most current list of attribute codes and class names. For older CDL products the attribute information was contained in the associated “stats” file rather than the metadata file. The “stats” files for CDL products prior to 2006 are available within the downloadable zip files at the NRCS Geospatial Data Gateway and on the official CD/DVD. Some users have reported issues with viewing the CDL using ENVI software. NASS suggests using the GeoTIFF file format with ENVI and ensuring that the three associated files (.tif, .tfw, and .aux) are all kept together. While it would be nice to have complete coverage of all crops in all states during the growing season, it is just not possible at this time in terms of funding and manpower. We are looking to possibly expand coverage through resource partnerships and hope to increase productivity through technological innovation. With continued budgetary support from NASS, a robust satellite imaging system such as Resourcesat-1 and improved technology, national coverage may become a reality in the future. Beginning with crop year 2006, the CDL program covered all of the NASS speculative corn and soybean states, because of the newly developed program efficiencies, the large swath width and rapid repeat times of AWiFS, and the availability and coverage of the FSA Common Land Unit Program. Please visit the NASS CDL website for updates on the proposed CDL states for the upcoming year. The CDL Program remains focused on the major crops of the Midwest and Mississippi Delta regions: corn, soybeans, rice and cotton. We are now working to expand the CDL Program to include the major wheat states of the Great Plains region. A Microsoft Word document was created to provide step-by-step instructions on how to create a CDL legend using ArcGIS. The document is located at: http://www.nass.usda.gov/research/Cropland/docs/CDL_Create_Legend.doc. No smoothing or filtering is done to the final CDL classification. The original 2006 CDL products did contain a small level of smoothing through the use of a minimum mapping unit (MMU). Within cropland areas, pixel groups of 10 acres (13 AWiFS pixels) or less were eliminated and replaced with the neighboring majority value. Within, non-cropland areas a smaller value of 4 acres (5 pixels) was used. This was inconsistent with older CDL products that never used any smoothing/MMU. So, in March of 2009 all of the 2006 CDL products with any smoothing were re-released with no smoothing/MMU. The one exception is the 2006 Washington CDL which was not re-released and still contains the smoothing/MMU as described above. Please visit the Charts and Maps Section of the NASS website for information about other spatial datasets. Of particular note are the vegetation condition images, state land use strata, and crop progress charts. The Agricultural Statistics Districts (ASD) for the entire U.S. are available in an ESRI shapefile format at ASD shapefile. An ASD is defined as a contiguous group of counties having relatively similar agricultural characteristics. The ASD's used by NASS usually divide each state into as many as nine Agricultural Statistics Districts to make data comparison easier. Each district is more homogeneous with respect to agriculture than the state as a whole. Many NASS research reports are available online at the following website: http://www.nass.usda.gov/research/reportsxdate.htm. To whom do I address
concerns about the Cropland Data Layer?
Distribution issues can be directed to the NASS Customer Service Hotline at 1-800-727-9540. Content questions can be directed to the NASS Spatial Analysis Research Section (SARS) at 703-877-8000 or email HQ_RDD_GIB@nass.usda.gov.
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