FamPred is a forecasting tool utilizing machine learning techniques to project food insecurity 30 days in advance. It has been successfully validated in Yemen, Mali, Syria, and Nigeria.
The Future of Food and Agriculture – Drivers and Triggers (FFA-DDT) report offers qualitative narratives and interactive quantitative analysis.
FAO provides qualitative narratives and quantitative information through web-based tools, supporting policy formulation globally and transforming agrifood systems.
Finnish startup SoilWatch enhances World Food Programme’s satellite data to help communities withstand hardships and external shocks.
A WFP collaboration with Google Research to predict agricultural market prices in areas with limited data availability. The project provides estimates for market prices, leveraging spatial interpolation and crop data.
Combining foresight and data approaches, FAO provides an innovative dataset of long-term projections for agrifood systems.
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