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Taken as a given: Evaluating the accuracy of remotely sensed crop data in the USA

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  • Larsen, Ashley E.
  • Hendrickson, Brandon T.
  • Dedeic, Nicholas
  • MacDonald, Andrew J.

Abstract

Quantifying the extent of agricultural land is important for addressing a large range of ecological, environmental, and economic questions. In many cases, answers focused on land use change require fine scale spatial data on the arrangement of crop types. Here we take advantage of the simultaneous availability of fine resolution, geospatial cropland data—the Cropland Data Layer, and comprehensive tabulated data—the USDA Census of Agriculture, to better understand the accuracy of geospatial data and thus, how geospatial data may be used in scientific research. We compared area estimates for cropland and major US crops (corn, soybeans, wheat and small grains) at the county level for the contiguous US in 2012 and for a subset of states in 2007. We find that accuracy of the Cropland Data Layer is high in regions dominated by a few crop types. However, elsewhere in the US accuracy is highly variable with common large areal overestimates and underestimates (+/−50% or more). Before employing the CDL and other geospatial data for applications such as measuring fine scale changes in land use, users should be wary of the potentially high misclassification error.

Suggested Citation

  • Larsen, Ashley E. & Hendrickson, Brandon T. & Dedeic, Nicholas & MacDonald, Andrew J., 2015. "Taken as a given: Evaluating the accuracy of remotely sensed crop data in the USA," Agricultural Systems, Elsevier, vol. 141(C), pages 121-125.
    • Handle: RePEc:eee:agisys:v:141:y:2015:i:c:p:121-125
    DOI: 10.1016/j.agsy.2015.10.008
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    References listed on IDEAS

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    1. Nathan P. Hendricks & Aaron Smith & Daniel A. Sumner, 2014. "Crop Supply Dynamics and the Illusion of Partial Adjustment," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 96(5), pages 1469-1491.
    2. Mosnier, A. & Havlík, P. & Valin, H. & Baker, J. & Murray, B. & Feng, S. & Obersteiner, M. & McCarl, B.A. & Rose, S.K. & Schneider, U.A., 2013. "Alternative U.S. biofuel mandates and global GHG emissions: The role of land use change, crop management and yield growth," Energy Policy, Elsevier, vol. 57(C), pages 602-614.
    3. Johnson, David M., 2013. "A 2010 map estimate of annually tilled cropland within the conterminous United States," Agricultural Systems, Elsevier, vol. 114(C), pages 95-105.
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    Cited by:

    1. Reza Maleki & Falin Wu & Amel Oubara & Loghman Fathollahi & Gongliu Yang, 2024. "Refinement of Cropland Data Layer with Effective Confidence Layer Interval and Image Filtering," Agriculture, MDPI, vol. 14(8), pages 1-23, August.
    2. Kenneth Lee Copenhaver, 2022. "Combining Tabular and Satellite-Based Datasets to Better Understand Cropland Change," Land, MDPI, vol. 11(5), pages 1-20, May.

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