Generating global crop distribution maps: from census to grid
In order to evaluate food security, technology potential and the environmental impacts of production in a strategic and regional context, it is critical to have reliable information on the spatial distribution and coincidence of people, agricultural production, and environmental services. This paper proposes a spatial allocation model for generating highly disaggregated, crop-specific production data by a triangulation of any and all relevant background and partial information. This includes national or sub-national crop production statistics, satellite data on land cover, maps of irrigated areas, biophysical crop suitability assessments, population density, secondary data on irrigation and rainfed production systems, cropping intensity, and crop prices. This information is compiled and integrated to generate "prior" estimates of the spatial distribution of individual crops. Priors are then submitted to an optimization model that uses cross-entropy principles and area and production accounting constraints to simultaneously allocate crops into the individual pixels of a GIS database. The result for each pixel (notionally of any size, but typically from 25 to 100 square km) is the area and production of each crop produced, split by the shares grown under irrigated, high-input rainfed, low-input rainfed conditions (each with distinct yield levels). Tested in Latin America and sub-Saharan Africa, the spatial allocation model is applied here to generate a global distribution of crop area and production for 20 major crops (wheat, rice, maize, barley, millet, sorghum, potato, sweet potato, cassava and yams, plantain and banana, soybean, dry beans, other pulse, sugar cane, sugar beets, coffee, cotton, other fibres, groundnuts, and other oil crops). The detailed spatial datasets represent a truly unique and extremely rich platform for exploring the social, economic and environmental consequences of agricultural production in a strategic policy context.
|Date of creation:||2006|
|Date of revision:|
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- Kostandini, Genti & Mills, Bradford F. & Omamo, Steven Were & Wood, Stanley, 2007.
"Ex-Ante Analysis of the Benefits of Transgenic Drought Tolerance Research on Cereal Crops in Low-Income Countries,"
2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN
9940, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
- Genti Kostandini & Bradford F. Mills & Steven Were Omamo & Stanley Wood, 2009. ""Ex ante" analysis of the benefits of transgenic drought tolerance research on cereal crops in low-income countries," Agricultural Economics, International Association of Agricultural Economists, vol. 40(4), pages 477-492, 07.
- You, Liangzhi & Ringler, Claudia & Wood-Sichra, Ulrike & Robertson, Richard & Wood, Stanley & Zhu, Tingju & Nelson, Gerald & Guo, Zhe & Sun, Yan, 2011. "What is the irrigation potential for Africa? A combined biophysical and socioeconomic approach," Food Policy, Elsevier, vol. 36(6), pages 770-782.
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- Anselin, Luc, 2002. "Under the hood Issues in the specification and interpretation of spatial regression models," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 27(3), November.
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