Village-Level Spatio-Temporal Patterns and Key Drivers of Social-Ecological Vulnerability in a Resource-Exhausted Mining City: A Case Study of Xintai, China

Yi Chen, Yuan Li, Tao Liu (), Yong Lei and Yao Meng
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Yi Chen: School of Architecture, Nanjing Tech University, Nanjing 211816, China
Yuan Li: School of Architecture, Nanjing Tech University, Nanjing 211816, China
Tao Liu: College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Yong Lei: School of Architecture, Nanjing Tech University, Nanjing 211816, China
Yao Meng: School of Architecture, Nanjing Tech University, Nanjing 211816, China

Land, 2025, vol. 14, issue 9, 1-28

Abstract: Evaluation of socio-ecological vulnerability is crucial for sustainable management in mining cities. This study selected Xintai City, China, as a case and constructed a comprehensive vulnerability assessment framework based on 2010–2020 multi-source data. By integrating the Geodetector, spatial autocorrelation analysis, and ordered weighted averaging (OWA), we systematically explored the spatio-temporal patterns and driving mechanisms of socio-ecological vulnerability. The Theil index at the village level revealed finer spatial heterogeneity than large-scale analyses. The results show the following: (1) Socio-ecological vulnerability in Xintai City is generally moderate, with high-vulnerability areas concentrated in the urban center and former coal mining zones. Over the past decade, high—vulnerability levels in these areas have improved, whereas the urban-rural fringe has experienced a significant increase in vulnerability, primarily driven by industrial transfer and uneven resource allocation. (2) Geodetector analysis indicated a shift in dominant drivers from natural to socio-economic factors, with population density and construction land proportion surpassing natural conditions such as average annual rainfall by 2020. Additionally, mining land proportion, land use change, and the spatial distribution of social services played key roles in shaping vulnerability patterns, while ecological and public service factors showed weaker explanatory power. (3) Scenario simulation based on OWA demonstrated that an economic-priority pathway leads to the outward expansion of vulnerable areas into mountainous regions, while an ecological-priority approach promotes spatial contraction and optimization of vulnerability zones. These findings provide scientific guidance for identifying key vulnerable areas and formulating differentiated management strategies, offering reference value for the sustainable development of resource-exhausted mining cities.

Keywords: social-ecological vulnerability; spatial-temporal patterns; mining area; GeoDetector; OWA operators; Xintai; China (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2025
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