Generating Plausible Crop Distribution Maps for Sub-Saharan Africa Using a Spatially Disagreggated Data Fusion and Optimization Approach

Large gaps exist in our knowledge of the current geographic distribution and spatial patterns of performance of crops, and these gaps are unlikely to be filled.

Generating Plausible Crop Distribution and Performance Maps for Sub-Saharan Africa Using a Spatially Disaggregated Data Fusion and Optimization Approach

Agricultural production statistics reported at country or sub-national geopolitical scales are used in a wide range of economic analyses, and spatially explicit (geo-referenced) production data are increasingly needed to support improved approaches to the planning and implementation of agricultural development. However, it is extremely challenging to compile and maintain collections of sub-national crop production data, particularly for poorer regions of the world.

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