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Balancing tourism-driven urbanization (TU) with ecosystem health (EHA) remains critical for sustainable development in fragile karst regions. This study addresses three key gaps, limited spatial granularity, static assessment models, and inadequate quantification of natural attractions, through an integrated analysis of Guilin, China. Using 1-km2 grid-level data (2005–2020), we developed a CCD_GM (1,1) framework coupling coordination degree (CCD) evaluation with grey forecasting to dynamically assess TU-EHA interactions. Kernel density analysis revealed spatial heterogeneity in tourism expansion, while PSR-model-based EHA assessment highlighted ecosystem degradation hotspots. The CCD_GM (1,1) projected a 19.46% coordination improvement by 2035, yet > 75% of Guilin remains in slightly coordinated states. Geographical Detector analysis identified evolving drivers, socioeconomic factors surpassed natural constraints in influencing CCD. Spatial mismatches emerged between central zones (high TU, declining EHA) and northwestern karst areas (low TU, high ecological sensitivity). We propose differentiated zoning strategies to reconcile development pressures with karst-specific conservation.

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Coupling Coordination Dynamic of Tourism-Driven Urbanization and Ecosystem Health in Karst Regions: Evidence from Sustainable Development Innovation Demonstration Zone—Guilin, China

  • 会议论文

  • 发表日期：

    2026年

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  • Yangling Zhao,
  • Yifeng Qin,
  • Li Hong,
  • Bodzhidar Ivanov,
  • Yanka Kazakova-Mateva,
  • Shengquan Che

摘要

Balancing tourism-driven urbanization (TU) with ecosystem health (EHA) remains critical for sustainable development in fragile karst regions. This study addresses three key gaps, limited spatial granularity, static assessment models, and inadequate quantification of natural attractions, through an integrated analysis of Guilin, China. Using 1-km2 grid-level data (2005–2020), we developed a CCD_GM (1,1) framework coupling coordination degree (CCD) evaluation with grey forecasting to dynamically assess TU-EHA interactions. Kernel density analysis revealed spatial heterogeneity in tourism expansion, while PSR-model-based EHA assessment highlighted ecosystem degradation hotspots. The CCD_GM (1,1) projected a 19.46% coordination improvement by 2035, yet > 75% of Guilin remains in slightly coordinated states. Geographical Detector analysis identified evolving drivers, socioeconomic factors surpassed natural constraints in influencing CCD. Spatial mismatches emerged between central zones (high TU, declining EHA) and northwestern karst areas (low TU, high ecological sensitivity). We propose differentiated zoning strategies to reconcile development pressures with karst-specific conservation.