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<p>Rapid urbanization threatens eco-environment quality (EEQ), in which the urban landscape pattern (ULP) plays a key role. However, the multi-scale mechanisms behind their spatial nonstationarity and nonlinear interactions remain underexplored. This study constructed an EEQ index, incorporating urban impervious surface and air pollution, based on urban ecosystem elements. Using a novel framework that integrates MGWR with a random forest model interpreted by SHAP, we explored the spatially nonstationary and nonlinear association between ULP and the EEQ index, and further quantified the contributions and thresholds of ULP both globally and locally. The results indicate that: (1) EEQ index in China’s coastal areas (CNCA) averaged 0.64, indicating a generally favorable level, with lower values in urban agglomeration distribution; (2) Urban built-up area percentage (UAP), urban built-up height (UBH), Shape, Contagion, and patch Euclidean Nearest-Neighbor Mean Distance index were the top contributors; (3) UAP and UBH have bidirectional effects on EEQ index in CNCA, reflecting characteristics of the Environmental Kuznets Curve. However, patterns were inconsistent for urban agglomerations within CNCA, indicating significant spatial discrepancies and nonlinear features, and growing inequality among urban agglomerations has heightened the complexity of their thresholds. Overall, prioritizing urban landscapes with order, strong cohesion, and effective connectivity in landscape planning can guide future urban expansion.</p>

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Investigating multi-scale associations and thresholds between eco-environment quality and urban landscape patterns: A case from coastal China

  • 期刊论文

  • 发表日期：

    2026年5月28日

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  • Linsheng Wen,
  • Manuel Esperon-Rodriguez,
  • Yun Peng,
  • Aifang Weng,
  • Yunrui Zhou,
  • Sunbowen Zhang,
  • Baoyin Li,
  • Yuying Lin

摘要

Rapid urbanization threatens eco-environment quality (EEQ), in which the urban landscape pattern (ULP) plays a key role. However, the multi-scale mechanisms behind their spatial nonstationarity and nonlinear interactions remain underexplored. This study constructed an EEQ index, incorporating urban impervious surface and air pollution, based on urban ecosystem elements. Using a novel framework that integrates MGWR with a random forest model interpreted by SHAP, we explored the spatially nonstationary and nonlinear association between ULP and the EEQ index, and further quantified the contributions and thresholds of ULP both globally and locally. The results indicate that: (1) EEQ index in China’s coastal areas (CNCA) averaged 0.64, indicating a generally favorable level, with lower values in urban agglomeration distribution; (2) Urban built-up area percentage (UAP), urban built-up height (UBH), Shape, Contagion, and patch Euclidean Nearest-Neighbor Mean Distance index were the top contributors; (3) UAP and UBH have bidirectional effects on EEQ index in CNCA, reflecting characteristics of the Environmental Kuznets Curve. However, patterns were inconsistent for urban agglomerations within CNCA, indicating significant spatial discrepancies and nonlinear features, and growing inequality among urban agglomerations has heightened the complexity of their thresholds. Overall, prioritizing urban landscapes with order, strong cohesion, and effective connectivity in landscape planning can guide future urban expansion.