HarvestChoice generates knowledge products to help guide strategic decisions to improve the well-being of the poor in sub-Saharan Africa through more productive and profitable farming. To this end, HarvestChoice has developed and continues to expand upon a spatially explicit, landscape level evaluation framework. HarvestChoice’s evolving list of knowledge products includes maps, datasets, working papers, country briefs, user-oriented tools, and spatial and economic models designed to target the needs of investors, policymakers, and research analysts who are working to improve the food supply of the world's poor http://harvestchoice.org.
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ZIP Archive - 147.2 MB - MD5: 06db16f6e9056bbdbe8cbf0404623af9
ZIP Archive - 175.8 MB - MD5: d6955e55ea6b3addd6c853706566ab7c
ZIP Archive - 195.2 MB - MD5: c6d86de2be8ca37fdcceea5935a4a9b6
Jan 22, 2020
International Food Policy Research Institute, 2019, "Global Spatially-Disaggregated Crop Production Statistics Data for 2000 Version 3.0.7", https://doi.org/10.7910/DVN/A50I2T, Harvard Dataverse, V2, UNF:6:ikCh6KeB4r2u/p2tkbFDOw== [fileUNF]
Using a variety of inputs, IFPRI's Spatial Production Allocation Model (SPAM) uses a cross-entropy approach to make plausible estimates of crop distribution within disaggregated units. Moving the data from coarser units such as countries and sub-national provinces, to finer units such as grid cells, reveals spatial patterns of crop performance, cre...
ZIP Archive - 90.0 MB - MD5: c815e34577ea7c9a2d22ce8163daaadc
Harvested area in DBF and CSV format
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