Agricultural heritage preservation and rural vitality promotion: analyzing structural features and driving mechanisms in spatial correlation networks

Abstract

Rural population contraction and vitality decline pose universal challenges amid global industrialization and urbanization. This study adopts an integrated framework combining entropy weight method, gravity model, social network analysis, and exponential random graph models to quantify rural vitality and its spatial correlation networks in 163 counties of China’s nationally important agricultural heritage systems (NIAHS) from 2010 to 2023. Our findings reveal three key patterns: First, rural vitality shows an overall rise with marked regional gradients (Eastern > Central > Western > Northeastern). Second, the spatial network reveals a core–periphery structure with hierarchical stratification and spatial disequilibrium. Third, ERGM identifies industrialization levels, green innovation capacity, and social equity as fundamental drivers shaping these networks, operating through an efficiency–resilience–equity interactive mechanism that fosters multi‑scale collaboration. The framework bridges heritage preservation and rural development, offering actionable insights for sustainable heritage management and global applicability to culturally significant landscapes.

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