Articles | Volume 12, issue 4
Earth Syst. Sci. Data, 12, 3545–3572, 2020
https://doi.org/10.5194/essd-12-3545-2020
Earth Syst. Sci. Data, 12, 3545–3572, 2020
https://doi.org/10.5194/essd-12-3545-2020

Data description paper 21 Dec 2020

Data description paper | 21 Dec 2020

A cultivated planet in 2010 – Part 2: The global gridded agricultural-production maps

Qiangyi Yu et al.

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Cited articles

Anderson, W., You, L., Wood, S., Wood-Sichra, U., and Wu, W.: An analysis of methodological and spatial differences in global cropping systems models and maps, Global Ecol. Biogeogr., 24, 180–191, https://doi.org/10.1111/geb.12243, 2015. 
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Bunn, C., Läderach, P., Ovalle Rivera, O., and Kirschke, D.: A bitter cup: climate change profile of global production of Arabica and Robusta coffee, Climatic Change, 129, 89–101, https://doi.org/10.1007/s10584-014-1306-x, 2015. 
Cairns, J. E., Hellin, J., Sonder, K., Araus, J. L., MacRobert, J. F., Thierfelder, C., and Prasanna, B. M.: Adapting maize production to climate change in sub-Saharan Africa, Food Sec., 5, 345–360, https://doi.org/10.1007/s12571-013-0256-x, 2013. 
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SPAM makes plausible estimates of crop distribution within disaggregated units. It moves the data from coarser units such as countries and provinces to finer units such as grid cells and creates a global gridscape at the confluence between earth and agricultural-production systems. It improves spatial understanding of crop production systems and allows policymakers to better target agricultural- and rural-development policies for increasing food security with minimal environmental impacts.