Bridging Heritage Systems: Multi-Scale Spatial Coupling Between Tangible and Intangible Cultural Heritage in China Using Hierarchical Bayesian Model and Causal Inference

Cultural heritage systems play a crucial role in decoding human–environment interactions and social evolution. This study aims to reveal the spatial coupling characteristics of tangible and intangible cultural heritage in China, as well as the heterogeneity of their driving mechanisms. After quantifying heritage coupling at three geographic scales, we integrated a hierarchical Bayesian model with a hybrid causal inference framework to identify the correlations, causal effects, and heterogeneity of the driving factors. The empirical results indicate the following: (1) The coupling patterns exhibit scale dependence. The proportion of strongly coupled areas decreases from the prefecture-level scale to the provincial scale but increases at the cultural–geographical unit scale. This suggests that China’s cultural system has a cohesive effect that transcends administrative boundaries. (2) The hierarchical Bayesian model identifies the significant effects of mean annual temperature, population density, GDP–population interaction, transport–hydrological network interaction, and industrial structure. Effect strengths generally peak at the prefecture-level scale and decrease at the provincial scale. (3) Causal inference estimates the causal effects of mean annual temperature, transport–hydrological network interaction, mean annual precipitation, and water network density on coupling. (4) Heterogeneity tests reveal that the positive causal effect of transport–hydrological network interaction and the negative causal effect of mean annual precipitation are significant only in low-temperature regions. By integrating hierarchical modeling with causal verification, this study elucidates the mechanisms underlying heritage coupling. This provides a scientific basis for understanding the spatial patterns of cultural heritage systems and formulating differentiated conservation policies.

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Publication Details

Journal
Land
Published
2025-12-06
DOI
https://doi.org/10.3390/land14122386
Primary Topic
Conservation Techniques and Studies
Type
article
Field-Weighted Citation Impact
0.00

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article

Bridging Heritage Systems: Multi-Scale Spatial Coupling Between Tangible and Intangible Cultural Heritage in China Using Hierarchical Bayesian Model and Causal Inference

Yu Bai, Yuxi Liu, Shiliang Liu, Qibing Chen et al.
Land
Conservation Techniques and Studies
article

Bridging Heritage Systems: Multi-Scale Spatial Coupling Between Tangible and Intangible Cultural Heritage in China Using Hierarchical Bayesian Model and Causal Inference

Yu Bai, Yuxi Liu, Shiliang Liu, Qibing Chen, Xinyu Du
article en

Abstract

Cultural heritage systems play a crucial role in decoding human–environment interactions and social evolution. This study aims to reveal the spatial coupling characteristics of tangible and intangible cultural heritage in China, as well as the heterogeneity of their driving mechanisms. After quantifying heritage coupling at three geographic scales, we integrated a hierarchical Bayesian model with a hybrid causal inference framework to identify the correlations, causal effects, and heterogeneity of the driving factors. The empirical results indicate the following: (1) The coupling patterns exhibit scale dependence. The proportion of strongly coupled areas decreases from the prefecture-level scale to the provincial scale but increases at the cultural–geographical unit scale. This suggests that China’s cultural system has a cohesive effect that transcends administrative boundaries. (2) The hierarchical Bayesian model identifies the significant effects of mean annual temperature, population density, GDP–population interaction, transport–hydrological network interaction, and industrial structure. Effect strengths generally peak at the prefecture-level scale and decrease at the provincial scale. (3) Causal inference estimates the causal effects of mean annual temperature, transport–hydrological network interaction, mean annual precipitation, and water network density on coupling. (4) Heterogeneity tests reveal that the positive causal effect of transport–hydrological network interaction and the negative causal effect of mean annual precipitation are significant only in low-temperature regions. By integrating hierarchical modeling with causal verification, this study elucidates the mechanisms underlying heritage coupling. This provides a scientific basis for understanding the spatial patterns of cultural heritage systems and formulating differentiated conservation policies.

LandVol. 14(12)
Sichuan Agricultural University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 56%
Conservation Techniques and Studies
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