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  "contact_name": "You, Liangzhi (IFPRI) Wood-Sichra, Ulrike (IFPRI) 
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  "contact_name": "You, Liangzhi (IFPRI) Wood-Sichra, Ulrike (IFPRI) 
            
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Koo, Jawoo (IFPRI)", 
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Koo, Jawoo (IFPRI)", 
            
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y-disaggregated-crop-production-statistics-data-for-2010-version-2-0", 
            
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  "notes": "\t\r\nUsing a variety of inputs, IFPRI's Spatial 
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  "notes": "\t\r\nUsing a variety of inputs, IFPRI's Spatial 
            
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Production Allocation Model (SPAM) uses a cross-entropy approach to 
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Production Allocation Model (SPAM) uses a cross-entropy approach to 
            
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make plausible estimates of crop distribution within disaggregated 
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make plausible estimates of crop distribution within disaggregated 
            
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units. Moving the data from coarser units such as countries and 
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units. Moving the data from coarser units such as countries and 
            
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sub-national provinces, to finer units such as grid cells, reveals 
29
sub-national provinces, to finer units such as grid cells, reveals 
            
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spatial patterns of crop performance, creating a global grid-scape at 
30
spatial patterns of crop performance, creating a global grid-scape at 
            
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the confluence between geography and agricultural production systems. 
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the confluence between geography and agricultural production systems. 
            
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Improving spatial understanding of crop production systems allows 
32
Improving spatial understanding of crop production systems allows 
            
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policymakers and donors to better target agricultural and rural 
33
policymakers and donors to better target agricultural and rural 
            
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development policies and investments, increasing food security and 
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development policies and investments, increasing food security and 
            
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growth with minimal environmental impacts. (2020-07-14)", 
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growth with minimal environmental impacts. (2020-07-14)", 
            
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Data for 2010 Version 2.0", 
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Data for 2010 Version 2.0", 
            
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