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  "conforms_to": "http://www.opengis.net/def/crs/OGC/0/4326", 
            
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  "contact_name": "Liangzhi You (IFPRI), Ulrike Wood-Sichra (IFPRI), 
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  "contact_name": "Liangzhi You (IFPRI), Ulrike Wood-Sichra (IFPRI), 
            
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Jawoo Koo (IFPRI)", 
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Jawoo Koo (IFPRI)", 
            
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  "contact_uri": "https://orcid.org/0000-0001-7930-8814, 
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  "contact_uri": "https://orcid.org/0000-0001-7930-8814, 
            
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https://orcid.org/0000-0002-0546-2074; 
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https://orcid.org/0000-0002-0546-2074; 
            
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https://orcid.org/0000-0003-3424-9229", 
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https://orcid.org/0000-0003-3424-9229", 
            
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  "documentation": 
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pernicus.org/articles/12/3545/2020/essd-12-3545-2020-discussion.html", 
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pernicus.org/articles/12/3545/2020/essd-12-3545-2020-discussion.html", 
            
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  "license_title": "", 
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  "metadata_modified": "2021-10-25T13:38:02.309880", 
            
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  "name": 
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  "name": 
            
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y-disaggregated-crop-production-statistics-data-for-2010-version-2-0", 
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y-disaggregated-crop-production-statistics-data-for-2010-version-2-0", 
            
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  "notes": "\"Using a variety of inputs, IFPRI's Spatial Production 
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  "notes": "\"Using a variety of inputs, IFPRI's Spatial Production 
            
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Allocation Model (SPAM) uses a cross-entropy approach to make 
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Allocation Model (SPAM) uses a cross-entropy approach to make 
            
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plausible estimates of crop distribution within disaggregated units. 
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plausible estimates of crop distribution within disaggregated units. 
            
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Moving the data from coarser units such as countries and sub-national 
31
Moving the data from coarser units such as countries and sub-national 
            
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provinces, to finer units such as grid cells, reveals spatial patterns 
32
provinces, to finer units such as grid cells, reveals spatial patterns 
            
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of crop performance, creating a global grid-scape at the confluence 
33
of crop performance, creating a global grid-scape at the confluence 
            
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between geography and agricultural production systems. Improving 
34
between geography and agricultural production systems. Improving 
            
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spatial understanding of crop production systems allows policymakers 
35
spatial understanding of crop production systems allows policymakers 
            
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and donors to better target agricultural and rural development 
36
and donors to better target agricultural and rural development 
            
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policies and investments, increasing food security and growth with 
37
policies and investments, increasing food security and growth with 
            
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minimal environmental impacts. (2020-07-14)\" <br> \r\n*Global 
38
minimal environmental impacts. (2020-07-14)\" <br> \r\n*Global 
            
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Spatially-Disaggregated Crop Production Statistics Data for 2010 
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Spatially-Disaggregated Crop Production Statistics Data for 2010 
            
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Version 2.0: 
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  "theme": "https://inspire.ec.europa.eu/theme/am", 
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  "theme": "https://inspire.ec.europa.eu/theme/am", 
            
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  "title": "MapSPAM Global Spatially-Disaggregated Crop Production 
            
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Statistics Data for 2010 v2.0", 
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Statistics Data for 2010 v2.0", 
            
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  "type": "dataset", 
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r-dmp.geo.tu-dresden.de/dataset/b0e5c26c-7762-4f99-8234-b793ce13d19c", 
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r-dmp.geo.tu-dresden.de/dataset/b0e5c26c-7762-4f99-8234-b793ce13d19c", 
            
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