COST AND BENEFIT ANALYSIS OF A CROPLAND DATA LAYER 

George Hanuschak, Chief, Geospatial Information Branch 

 Rick Mueller, Mathematical Statistician 

National Agricultural Statistics Service, U.S. Department of Agriculture 

3251 Old Lee Highway, Fairfax, VA 22030 

ghunschak@nass.usda.gov 

rmueller@nass.usda.gov 

 

ABSTRACT 

 In the last several years, the National Agricultural Statistics Service (NASS) has developed a Cropland Data 

Layer (CDL) in geographic information system (GIS) format (See Figure 1) for public use. It is being used by over 

1000 GIS proficient users for watershed monitoring, agribusiness planning, prairie water pothole monitoring, crop 

rotation pattern analysis and animal habitat monitoring and value added analysis by private sector remote 

sensing/GIS industry. The CDL can be viewed and ordered on CD at the 

http://www.nass.usda.gov/research/Cropland/SARS1a.htm address. The benefits to GIS proficient data users seem 

to easily outweigh the program costs. State governments especially are saving considerable resources by partnering 

with NASS in the Cropland Data Layer Program. As the number of States continue to expand, the costs per State 

will continue to decline and the benefits will be expanding with more data users and uses. 

 

THE OLD ECONOMICS (1970's-1980's) 

The economics has changed rather substantially over the last three decades. The initial statistics and software 

research in the early 1970's was dominated by research staff costs and computer processing costs. The first full 

State project, Illinois in 1975, cost $750,000 but still included substantial research and statistical and software 

development costs. The first applications costs were established for processing the State of Iowa (1978) in time for 

end of season crop area estimation. At that time, the total cost per State was estimated at $300,000 and the data 

source was Landsat Multi-Spectral Scanner (MSS) at 60-80 meter resolution, with 4 spectral bands of data. 

 

By the early 1980's, there were eight States being processed. The total cost per State was $150,000. Major item 

costs were associated with remote sensing analyst staff (although spread out over eight States which increased 

efficiency substantially over one or two States with about the same staffing levels) and the cost of processing the 

data on mini-computers and on the ILLIAC and Cray supercomputers. Data costs were $300 per Landsat scene and 

generally a small portion of the total project cost. When Landsat thematic mapper became available in 1982 at 30 

meter resolution with seven spectral bands of data, the program faced a fork (applications continued or a research 

program and switch to Landsat TM) in the road and only had resources to go in one chosen direction. At first, 

NASS continued the eight State application using Landsat MSS data, with a small amount of resources devoted to 

research on Landsat TM. Even with the limited research program resources, it became apparent that the accuracy 

levels could be improved substantially by using Landsat TM but at a higher cost for the data and for the information 

extraction (more bands and better resolution). Thus in 1988 due to budget cuts and U.S. government plans to not 

have MSS data on future Landsat or other earth resource observing satellites, NASS abandoned the eight State 

application using Landsat MSS but increased the research program with Landsat TM. 

 

A new applications program was initiated in 1991 in Arkansas and Mississippi. In 1992 Louisiana was added to 

the program. Budget cuts hit again and Louisiana and Mississippi were dropped from the program. In fact in 1995, 

the program was only intact for Craighead county in Arkansas. Needless to say is that the program had a very rocky 

road at that point in time. Thus, it was apparent that NASS had to partner and resource share with other Federal and 

State government Agencies in order to continue and expand the program again and add a public cropland data layer 

for distribution as well as the internal statistical products. In preparation for this, NASS analyst staff emphasized a 

more automated and more expert system like version of PEDITOR to ease the labor burden on analysts. When this 

was adequately accomplished, NASS was in position to seek out Federal, State and University partnerships.

 
Resource Leveraging Partnerships 

Starting in 1997, a new and key data license partnership between NASS and USDA’s Foreign Agricultural 

Service (FAS) and the Farm Services Agency (FSA) was established. Landsat 5 data could be used for projects that 

serviced these agencies programs. Thus, the Landsat data costs for a program expansion were reduced. In addition, 

with Landsat 7, data costs at EROS Data Center were set at $600 for a system geo-referenced data set without 

licensing restrictions. USDA FAS has a USDA-wide license for Landsat 7 with Radarsat for $405 per scene. Thus, 

the Landsat data costs were no longer a major constraint as when the cost for Landsat 4&5 peaked for government 

buyers at $4,400 per Landsat scene in the early 1990's. 

 

The highest cost historically was for expert remote sensing and statistical analysts to run the complex PEDITOR 

package for both remote sensing outputs and for statistical estimates with relative sampling error outputs as well. 

NASS had a small group of expert analysts in its’ Research Division who were doing centralized analysis for several 

States. However, it was recognized that a decentralized analysis staff directly in NASS State Statistical offices 

would expand the Agency’s analytical capabilities. In addition the analyst will have the advantage of more 

localized knowledge of the crops and cropping practices and other sources of data to evaluate the relative 

contribution of the Landsat to the NASS crop area estimation program at the State and county level. 

 A local analyst (with a stable position and longevity) and State office management will be in a better position to 

service other State government and university and farm organizations and agribusinesses by providing them a 

Cropland Data layer in geographic information system (GIS) format. For example, the analyst in Illinois did both 

Illinois and Indiana in a regional concept which is the most cost efficient. Small two to four State regions will likely 

be the most cost efficient model. 

 This data layer has already proven valuable to data users of NASS who often combine the NASS cropland data 

layer with other data layers. Some examples are for water quality assessments for watersheds, and location plans 

for a new agribusiness facility, such as a soybean crushing plant and for grain storage and transportation planning 

and for prairie water pothole monitoring in North Dakota. 

 Since 1998, NASS has added the States of Illinois, Indiana, Mississippi, New Mexico, and Iowa and continued 

to do North Dakota and Arkansas as well. Florida A&M University and NASS also entered into a cooperative 

program for minority student outreach in remote sensing and GIS by analyzing a portion of northern Florida. 

Establishing and maintaining effective and win-win partnerships for the Cropland Data Layer is challenging though. 

The analyst position needs to be strongly supported by all the partnering organizations and needs some longevity ( 5 

years or so) to be effective. Some of the partnerships are stronger and more stable in terms of longevity than others. 

A companion paper by Craig (ASPRS 2001) entitled “A Resource Sharing Approach to Crop Identification and 

Estimation “ goes into more detail about each partnership for the Cropland Data Layer program.

 

THE NEW ECONOMICS (LATE 1990's AND 2000 ) 

 NASS has entered into a new economics for crop area estimation and a Cropland Data Layer for public 

consumption through the new resource leveraging partnerships. The total cost per State is now $75,000 and should 

drop further with the addition of more States. See the attached Figures 2 and 3 for the graphic representation of the 

cost reduction over time (inflation adjusted and non-inflation adjusted). Major reductions were realized in the cost 

of the Landsat data and even more dramatic in the cost of data processing which has gone from mini-computers and 

supercomputers to high end PC desktops now. All the processes, including full Landsat scene multi-temporal pixel 

categorization, are done on PC’s. The non-inflation adjusted total project cost has been cut in half (See Figure 2). 

When adjusting for inflation (See Figure 3), the cost reduction is more than fivefold from the first large scale 

application in the early 1980's. The current program and the early 1980's are the only comparable periods to 

compare costs over. The reason is that the number of States that labor costs are being spread over are very similar in 

number and scope of effort. Dramatic cost reductions have been achieved in the cost of the Landsat data and for the 

data processing of the Landsat data to categorize it into most likely crop types (See Figure 4). Spreading out the 

labor costs over as many States as possible and having co-funding partners is the key to future cost reductions. 

 
Perhaps more importantly, there are now more accurate and valuable output products, both internal to NASS 

and external to NASS data users. These include a State level estimate with relative sampling error reductions on the 

order of two to five compared to the ground sample data only. County level (small area) estimates with measurable 

sampling errors which have been recently improved with several alternative estimators. Third, a new publicly 

available Cropland Data Layer at the 30 meter pixel level categorized by crop type and formatted for standard 

geographic information systems input. 

 

The use of the Cropland Data Layer by GIS proficient data users outside of NASS is a major new thrust. In 

North Dakota, the NASS State Statistical Office (SSO), the North Dakota State University and an agri-business firm 

used the Cropland Data Layer as one input into a key agri-business decision. The location of a wheat strain 

processing plant was being evaluated. By combining the Cropland Data Layer with a transportation network layer, a 

decision model was built by the University and used in the agri-business decision for the plant location. Another 

anticipated major use of the Cropland Data Layer is in watershed monitoring and in fact is one of the major reasons 

for the North Dakota State government interest in the program. The State of Illinois chose to add to the Cropland 

Data Layer by adding other ground data on land covers and converting it to a Land Cover Layer. 

Satellite Data Sources 

NASS staff have a very strong preference for the Landsat data. The nadir look, the wide area image swaths, 

and the spatial resolution and spectral bands are virtually ideal for the NASS Cropland Data Layer and crop 

estimation program. The only issue with Landsat is the temporal frequency. NASS staff desires eight day coverage 

as a minimum and would prefer even better temporal coverage. Backup to the Landsat for the NASS program is the 

Indian IRS satellite series, which have many Landsat-like features. SPOT has not proven to be a cost effective 

backup for the NASS program. NASS has used SPOT for area sampling frame construction, on occasion, where 

price reductions are available through State consortiums or now under a USDA-wide license or existing credits from 

USDA/FAS. 

 

NASS gets questions about its’ plans for using very high resolution satellite data. At this time there are no 

major plans to use very high resolution data, such as IKONOS and QUICKBIRD in the NASS program other than 

for occasional small quality control checks. NASS has farmer reported data from a stratified area frame sample to 

evaluate the Landsat data. The swath width of IKONOS is too small for wall-to-wall coverage needed for the 

Cropland Data Layer and the cost per square mile too high relative to Landsat. There is one small scale research 

project in NASS and FAS for citrus tree counting where very high resolution data will be used at the request of the 

Florida Department of Citrus. 

BENEFITS 

The public use Cropland Data Layer GIS files are definitely of value to the GIS proficient data users who order 

them. It is difficult to put an exact, or even approximate, dollar value on the use of the files but here are some very 

important uses of the Cropland Data Layer. Among the important uses are: watershed and water quality monitoring 

(State of North Dakota government and the EPA and USDA and North Dakota State U.), grain transportation and 

storage planning, crop rotation pattern analysis across years, use in university teaching of remote sensing and GIS, interaction of soils and crops over large areas, further enhancements by the private sector remote sensing/GIS 

industry for custom solutions for their clients, quality control for other Landsat categorizations, official State of 

Illinois Land Characterization Map, animal habitat monitoring, prairie water pothole monitoring in North Dakota, 

evaluation of where to build a wheat straw processing plant in North Dakota, identifying catfish ponds in 

Mississippi, agribusiness planning for seed, fertilizer, pesticide, fungicide and crop insurance, etc. 

Several of these applications have saved the user or generated additional revenue for the user in significant 

dollar terms. The States of Illinois and North Dakota, in particular, have saved considerable resources by partnering 

with NASS on the Cropland Data Layer. The uses and number of users is also growing rapidly and is still in the 

development stage. Again, while it is difficult to quantify the benefits to society, the authors believe that the 

benefits to date easily outweigh the program costs. In addition, NASS gets additional statistical inputs for crop 

county acreage estimates as well in a real time fashion. The Cropland Data Layer is the lowest level of aggregation 
that NASS provides and thus gives a very good look at the spatial distribution of crops, which is of considerable 

interest in the crop sector of the U.S. economy. 

 

FUTURE PERSPECTIVE (2001-2010) 

NASS will continue to pursue partnerships, primarily with State governments, to expand the crop area 

estimation and Cropland Data Layer program to more States. The desires are for program expansion to the top 

15-20 total cropland States in the United States. The Midwest, the Delta and the Great Plains are the likely areas for 

expansion as resources allow for. As the number of States continue to expand, the costs per State will continue to 

decline and the benefits will be expanding with more data users and uses. 

 

Acknowledgements 

The authors would like to extend their thanks and appreciation to all the analysts in the States involved. Those 

are Patrick Willis in Illinois, Dath Mita in North Dakota, and Ken Akins in Mississippi, and analysts in Washington, 

D.C., Mike Craig, Jim Mergerson, Charles Day and PEDITOR programmer Martin Ozga and ground data 

programmer, Jeff Johnson and Section Head, Robert Hale. In addition, the State Statisticians and their staffs for 

extensive ground data preparations for the States in the program. Thanks also go to Martin Ozga for recent 

improvements in PEDITOR aimed at reducing analyst labor, including a new mosaicking algorithm. Thanks to 

several members of the Area Frame Section and State office staffs for assisting in analysis preparations or analysis. 

 The authors would also like to extend their appreciation to Carol House, Fred Vogel, Joe Reilly, Rich Allen and 

Ron Bosecker of NASS for their headquarters executive management support of this program and to Allen 

Vandergriff of USDA/FAS and Glenn Bethel of USDA/FSA. 

 
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