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A comparative analysis of global cropping systems models and maps:

Author

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  • Anderson, Weston
  • You, Liangzhi
  • Wood, Stanley
  • Wood-Sichra, Ulrike
  • Wu, Wenbin

Abstract

This study aims to explore and quantify systematic similarities and differences between four major global cropping systems products: the dataset of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000), the spatial production allocation model (SPAM), the global agroecological zone (GAEZ) dataset, and the M3 dataset developed by Monfreda, Ramankutty, and Foley. The analysis explores not only the final cropping systems maps but also the interdependencies of each product, methodological differences, and modeling assumptions, which will provide users with information vital for discerning between datasets in selecting a product appropriate for each intended application.

Suggested Citation

  • Anderson, Weston & You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike & Wu, Wenbin, 2014. "A comparative analysis of global cropping systems models and maps:," IFPRI discussion papers 1327, International Food Policy Research Institute (IFPRI).
    • Handle: RePEc:fpr:ifprid:1327
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    File URL: http://www.ifpri.org/sites/default/files/publications/ifpridp01327.pdf
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    References listed on IDEAS

    as
    1. Xiaobo Zhang & Shenggen Fan, 2001. "Estimating Crop-Specific Production Technologies in Chinese Agriculture: A Generalized Maximum Entropy Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 83(2), pages 378-388.
    2. Lence, Sergio H & Miller, Douglas J, 1998. "Estimation of Multi-output Production Functions with Incomplete Data: A Generalised Maximum Entropy Approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 25(2), pages 188-209.
    3. You, Liangzhi & Wood, Stanley, 2006. "An entropy approach to spatial disaggregation of agricultural production," Agricultural Systems, Elsevier, vol. 90(1-3), pages 329-347, October.
    4. Golan, Amos & Judge, George G. & Miller, Douglas, 1996. "Maximum Entropy Econometrics," Staff General Research Papers Archive 1488, Iowa State University, Department of Economics.
    5. You, Liangzhi & Wood, Stanley & Wood-Sichra, Ulrike, 2009. "Generating plausible crop distribution maps for Sub-Saharan Africa using a spatially disaggregated data fusion and optimization approach," Agricultural Systems, Elsevier, vol. 99(2-3), pages 126-140, February.
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    Cited by:

    1. Mr. Jorge A Alvarez & Claudia Berg, 2019. "Crop Selection and International Differences in Aggregate Agricultural Productivity," IMF Working Papers 2019/179, International Monetary Fund.
    2. Gabriel Aboyadana & Marco Alfano, 2021. "Perceived Temperature, Trust and Civil Unrest in Africa," HiCN Working Papers 344, Households in Conflict Network.
    3. Fritz, Steffen & See, Linda & Bayas, Juan Carlos Laso & Waldner, François & Jacques, Damien & Becker-Reshef, Inbal & Whitcraft, Alyssa & Baruth, Bettina & Bonifacio, Rogerio & Crutchfield, Jim & Rembo, 2019. "A comparison of global agricultural monitoring systems and current gaps," Agricultural Systems, Elsevier, vol. 168(C), pages 258-272.
    4. Rótolo, G.C. & Montico, S. & Francis, C.A. & Ulgiati, S., 2015. "How land allocation and technology innovation affect the sustainability of agriculture in Argentina Pampas: An expanded life cycle analysis," Agricultural Systems, Elsevier, vol. 141(C), pages 79-93.

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    Keywords

    farmland; Cropping systems; yield; Cartography; global cropland; harvested area; downscaling;
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