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This research aims to quantify the spatial relationships between traditional villages and covered bridge heritage in Hunan Province.

February 9, 2026SustainabilityOpen Access

Coupling–Coordination Patterns and Driving Mechanisms of Traditional Villages and Covered Bridge Heritage in Hunan Province, China

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Research demonstrates spatial relationships and driving mechanisms of heritage types in Hunan, suggesting tailored conservation efforts.

This research aims to quantify the spatial relationships between traditional villages and covered bridge heritage in Hunan Province.
Integrated heritage inventories with socioeconomic and cultural indicators
Utilized kernel density estimation for clustering analysis
Applied spatial autocorrelation to assess spatial associations
Developed a coupling–coordination model to measure coupling intensity and coordination level
Employed GeoDetector to identify dominant factors and their interactions
Found significant associations with spatial mismatch between heritage types
Identified high coupling but low coordination levels
Revealed strong intra-provincial heterogeneity
Determined socioeconomic development and urbanization as key driving factors
Highlighted the importance of factor interactions in explaining spatial patterns

Li et al. (2026) studied this question.

View Full Paper

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February 9, 2026SustainabilityOpen Access

View Full Paper

Ask AI

Bookmark

Authors

Research demonstrates spatial relationships and driving mechanisms of heritage types in Hunan, suggesting tailored conservation efforts.

This research aims to quantify the spatial relationships between traditional villages and covered bridge heritage in Hunan Province.
Integrated heritage inventories with socioeconomic and cultural indicators
Utilized kernel density estimation for clustering analysis
Applied spatial autocorrelation to assess spatial associations
Developed a coupling–coordination model to measure coupling intensity and coordination level
Employed GeoDetector to identify dominant factors and their interactions
Found significant associations with spatial mismatch between heritage types
Identified high coupling but low coordination levels
Revealed strong intra-provincial heterogeneity
Determined socioeconomic development and urbanization as key driving factors
Highlighted the importance of factor interactions in explaining spatial patterns

Li et al. (2026) studied this question.

View Full Paper

Ask AI

Bookmark