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Agro-Climatic Data by County: A Spatially and Temporally Consistent U.S. Dataset for Agricultural Yields, Weather and Soils

Author

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  • Seong Do Yun

    (Department of Agricultural Economics, Mississippi State University, Mississippi State, MS 39762, USA)

  • Benjamin M. Gramig

    (Department of Agricultural and Consumer Economics, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA)

Abstract

Agro-climatic data by county (ACDC) is designed to provide the major agro-climatic variables from publicly available spatial data sources to diverse end-users. ACDC provides USDA NASS annual (1981–2015) crop yields for corn, soybeans, upland cotton and winter wheat by county. Customizable growing degree days for 1 °C intervals between −60 °C and +60 °C, and total precipitation for two different crop growing seasons from the PRISM weather data are included. Soil characteristic data from USDA-NRCS gSSURGO are also provided for each county in the 48 contiguous US states. All weather and soil data are processed to include only data for land being used for non-forestry agricultural uses based on the USGS NLCD land cover/land use data. This paper explains the numerical and geo-computational methods and data generating processes employed to create ACDC from the original data sources. Essential considerations for data management and use are discussed, including the use of the agricultural mask, spatial aggregation and disaggregation, and the computational requirements for working with the raw data sources.

Suggested Citation

  • Seong Do Yun & Benjamin M. Gramig, 2019. "Agro-Climatic Data by County: A Spatially and Temporally Consistent U.S. Dataset for Agricultural Yields, Weather and Soils," Data, MDPI, vol. 4(2), pages 1-20, May.
    • Handle: RePEc:gam:jdataj:v:4:y:2019:i:2:p:66-:d:229344
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    References listed on IDEAS

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    5. Yun, Seong Do & Gramig, Benjamin M & Delgado, Michael S. & Florax, Raymond J.G.M., 2015. "Does Spatial Correlation Matter in Econometric Models of Crop Yield Response and Weather?," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205465, Agricultural and Applied Economics Association.
    6. Baylis, Katherine R. & Paulson, Nicholas D. & Piras, Gianfranco, 2011. "Spatial Approaches to Panel Data in Agricultural Economics: A Climate Change Application," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 43(3), pages 1-14, August.
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    Cited by:

    1. Park, Yunsun & Yun, Seong & Interis, Matthew G., 2023. "Valuation of Crop Diversity Benefits on Water Quality," 2023 Annual Meeting, July 23-25, Washington D.C. 335714, Agricultural and Applied Economics Association.
    2. Hrozencik, R. Aaron & Perez-Quesada, Gabriela & Bocinsky, Kyle, 2024. "The Stocking Impact and Financial-Climate Risk of the Livestock Forage Disaster Program," Economic Research Report 340568, United States Department of Agriculture, Economic Research Service.
    3. Hrozencik, Robert A. & Perez-Quesada, Gabriela, 2023. "Drought and the U.S. Livestock Sector: Assessing the Impact of the Livestock Forage Program," 2023 Annual Meeting, July 23-25, Washington D.C. 335468, Agricultural and Applied Economics Association.
    4. Chen, Bowen & Gramig, Ben & Yun, Seong Do, 2020. "A Causal Analysis of the Effect of Conservation Tillage on U.S. Corn and Soybean Yield and Profitability," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304296, Agricultural and Applied Economics Association.

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