Spatial Association Between Rural Cultural Landscape Quality and Social-Ecological System Resilience and Its Differentiation Patterns: A Case Study of Shanxi Province, China

The spatial association between rural cultural landscape quality (CLQ) and social-ecological system resilience (SESR) influences the pathways and effectiveness of integrating heritage conservation with rural revitalization. Drawing on a sample of 1339 township-level spatial units in Shanxi Province, this study employs a suite of spatial and statistical methods—including cluster analysis, ANOVA, Lee’s L statistic, the coupling coordination degree (CCD), the optimal parameters-based geographical detector (OPGD), and a spatial regression model—to examine the spatial association between CLQ and SESR and the factors associated with its differentiation. This study yields the following key conclusions: (1) Overall, areas with higher CLQ tend to be associated with a higher overall SESR level; the association between CLQ and ecological resilience appears stronger than that between CLQ and social resilience. (2) CLQ and SESR exhibit significant positive global bivariate spatial autocorrelation, and at the local level, they present significant spatial copatterning clustering. (3) Over 90% of the province’s areas exhibit incoordination between CLQ and SESR; spatially, CCD exhibits a pattern of lower values in western and northern Shanxi and higher values in eastern and southern Shanxi. (4) The CCD differentiation is associated with locational conditions, urbanization rate, regional economic development level, topographic environment, and cultural heritage conservation policies.

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Journal
Land
Published
2026-10-05
DOI
https://doi.org/10.3390/land15101878
Primary Topic
Regional Development and Environment
Type
article
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article

Spatial Association Between Rural Cultural Landscape Quality and Social-Ecological System Resilience and Its Differentiation Patterns: A Case Study of Shanxi Province, China

Wang Xue, Kai Cui
Land
Regional Development and Environment
article

Spatial Association Between Rural Cultural Landscape Quality and Social-Ecological System Resilience and Its Differentiation Patterns: A Case Study of Shanxi Province, China

Wang Xue, Kai Cui
article en

Abstract

The spatial association between rural cultural landscape quality (CLQ) and social-ecological system resilience (SESR) influences the pathways and effectiveness of integrating heritage conservation with rural revitalization. Drawing on a sample of 1339 township-level spatial units in Shanxi Province, this study employs a suite of spatial and statistical methods—including cluster analysis, ANOVA, Lee’s L statistic, the coupling coordination degree (CCD), the optimal parameters-based geographical detector (OPGD), and a spatial regression model—to examine the spatial association between CLQ and SESR and the factors associated with its differentiation. This study yields the following key conclusions: (1) Overall, areas with higher CLQ tend to be associated with a higher overall SESR level; the association between CLQ and ecological resilience appears stronger than that between CLQ and social resilience. (2) CLQ and SESR exhibit significant positive global bivariate spatial autocorrelation, and at the local level, they present significant spatial copatterning clustering. (3) Over 90% of the province’s areas exhibit incoordination between CLQ and SESR; spatially, CCD exhibits a pattern of lower values in western and northern Shanxi and higher values in eastern and southern Shanxi. (4) The CCD differentiation is associated with locational conditions, urbanization rate, regional economic development level, topographic environment, and cultural heritage conservation policies.

LandVol. 15(10)
Taiyuan University of Technology (CN)
Openalex Percentile: Top 5%
Regional Development and Environment
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Spatial Association Between Rural Cultural Landscape Quality and Social-Ecological System Resilience and Its Differentiation Patterns: A Case Study of Shanxi Province, China — Wang Xue, Kai Cui · Land (2026) | TGRS Research Map | TGRS