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<p>Spatial distribution of Intangible Cultural Heritage exhibits significant complexity shaped by diverse geographical and socio-cultural contexts, yet conventional analyses often overlook its intricate heterogeneity and scale effects. Using Geographically Weighted Regression (MGWR) on 3610 Chinese national ICH items, we simultaneously address spatial non-stationarity and scale effects. Results show: (1) Significant spatial clustering (Moran’s I = 0.337, <i>p</i> &lt; 0.01) exists in ICH distribution, confirming an “east-dense, west-sparse” pattern. (2) Pronounced spatial heterogeneity exists; temperature and per capita GDP exhibit opposing effects in different regions, challenging simplistic assumptions. (3) Drivers operate at distinct scales: NDVI functions broadly (bandwidth&gt;360), while topography and economic indicators operate locally (bandwidth&lt;100). These findings reveal complex multi-scalar dynamics, resolving the methodological challenge of concurrently capturing spatial heterogeneity and factor-specific scale effects. Theoretically, it reveals fundamental ICH distribution patterns and mechanisms in China; Practically, it provides a basis for spatially differentiated conservation strategies in China and globally.</p>

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MGWR reveals scale heterogeneity shaping intangible cultural heritage distribution in China

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月25日

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  • Fengling Wang,
  • Tongyan Zhang,
  • Shengrui Zhang

摘要

Spatial distribution of Intangible Cultural Heritage exhibits significant complexity shaped by diverse geographical and socio-cultural contexts, yet conventional analyses often overlook its intricate heterogeneity and scale effects. Using Geographically Weighted Regression (MGWR) on 3610 Chinese national ICH items, we simultaneously address spatial non-stationarity and scale effects. Results show: (1) Significant spatial clustering (Moran’s I = 0.337, p < 0.01) exists in ICH distribution, confirming an “east-dense, west-sparse” pattern. (2) Pronounced spatial heterogeneity exists; temperature and per capita GDP exhibit opposing effects in different regions, challenging simplistic assumptions. (3) Drivers operate at distinct scales: NDVI functions broadly (bandwidth>360), while topography and economic indicators operate locally (bandwidth<100). These findings reveal complex multi-scalar dynamics, resolving the methodological challenge of concurrently capturing spatial heterogeneity and factor-specific scale effects. Theoretically, it reveals fundamental ICH distribution patterns and mechanisms in China; Practically, it provides a basis for spatially differentiated conservation strategies in China and globally.