Quantifying the resilience in the food system is important for food security issues. In this work, we present a geospatial knowledge graph (GeoKG)-based method for measuring the resilience of a multi-commodity flow network. Specifically, we develop a CFS-GeoKG ontology to describe geospatial semantics of a multi-commodity flow network comprehensively, and design resilience metrics that measure the node-level and network-level dependence of single-sourcing, distant, or non-adjacent suppliers/customers in food supply chains. We conduct a case study of the US state-level agricultural multi-commodity flow network with hierarchical commodity types. The results indicate that, by leveraging GeoKG, our method supports measuring both node-level and network-level resilience across space and over time and also helps discover concentration patterns of agricultural resources in the spatial network at different geographic scales.

本研究使用基于地理知识图谱的方法，构建了一个CFS-GeoKG本体论来全面描述多商品流网络的地理语义，并设计了衡量单一供应、远程或非相邻供应商/客户的节点级别和网络级别依赖性的韧性指标。通过案例研究，我们发现，利用GeoKG，我们的方法支持在空间和时间上同时度量节点级别和网络级别韧性，并有助于发现不同地理尺度上农业资源集中的模式。

利用地理知识图谱测量网络弹性: 以美国多商品流网络为例