资源环境科技发展态势分析平台

Food consumption and production are separated in space through flows of food along complex supply chains. These food supply chains are critical to our food security, making it important to evaluate them. However, detailed spatial information on food flows within countries is rare. The goal of this paper is to estimate food flows between all county pairs within the United States. To do this, we develop the Food Flow Model, a data-driven methodology to estimate spatially explicit food flows. The Food Flow Model integrates machine learning, network properties, production and consumption statistics, mass balance constraints, and linear programming. Specifically, we downscale empirical information on food flows between 132 Freight Analysis Framework locations (17 292 potential links) to the 3142 counties and county-equivalents of the United States (9869 022 potential links). Subnational food flow estimates can be used in future work to improve our understanding of vulnerabilities within a national food supply chain, determine critical infrastructures, and enable spatially detailed footprint assessments.