Seasonal Characteristics of Agricultural Product Circulation Network: A Case Study in Beijing, China

Abstract

Agricultural product circulation is an appropriate way to optimize the distribution of agricultural resources and maintain food safety. The seasonality of agriculture leads to seasonal variations in agricultural product circulation. Previous studies constructed origin–destination networks based on annual statistics to investigate the static structure of agricultural product circulation networks from a single view, failing to capture the seasonal and multi-dimensional characteristics in agricultural product circulation. This study presents a multi-view analytical framework used to investigate the seasonal characteristics of an agricultural product circulation network. First, agricultural product circulation networks in different seasons were constructed with mass freight trajectory data through trajectory mining technology. Then, the seasonal characteristics of agricultural product circulation were, respectively, analyzed from a macro-view (networks), meso-view (edges) and micro-view (nodes). A case study was conducted in Beijing, China. It is argued that: (1) The presented method for extracting agricultural trip chains based on massive freight trajectories is feasible for the construction of agricultural product circulation networks. (2) The agricultural product circulation networks in four seasons exhibit an obvious hierarchical and radial structure. South China has a higher network density in winter and spring, whereas northeast and northwest China are the opposite. (3) A total of 80% of the linkage strength is concentrated, on average, in 35.3% of city-pairs in four seasons, where the agglomeration effect and hub status of the linking cities is more prominent in summer and autumn. (4) A total of 316 cities form Beijing agricultural product circulation networks, 48.1% of which are mainly served by Beijing agricultural product circulation in winter and spring, which is 2.7 times more than cities served in summer and autumn. These findings extend the scientific understanding of the agricultural product supply chain from a dynamic and multi-dimensional view, which provides essential information for optimizing sustainable agri-food systems and ensuring food security.

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Spatiotemporal analysis of global grain trade multilayer networks considering topological clustering

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