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<p>Amid the dual contexts of rapid urbanization and global warming, the Surface Urban Heat Island (SUHI) effect has been identified as a pivotal climatic issue that poses severe threats to urban sustainable development and public health. Urban Resilience (UR), in turn, has been widely recognized as a systematic and holistic pathway to mitigate the SUHI effect and optimize the urban thermal environment. Based on the three-dimensional Scale-Density-Morphology theoretical framework, this study constructed a comprehensive UR evaluation system, using 2000–2024 long-time-series remote sensing and socio-economic data, combined with XGBoost-SHAP, Double Machine Learning (DML), and Geographically and Temporally Weighted Regression (GTWR) models, to systematically analyze UR’s nonlinear effects, critical thresholds, diurnal differences, and spatiotemporal differentiation on SUHI. During the study period, the SUHI in the Guanzhong Urban Agglomeration continuously intensified, increasing from 0.14&#xa0;°C to 0.48&#xa0;°C during the daytime and from 0.10&#xa0;°C to 0.22&#xa0;°C at night. Concurrently, the UR exhibited a continuous decline, dropping from 0.12 to 0.06. Urban resilience exerted a significant negative causal effect on the SUHI, demonstrating typical nonlinear and threshold characteristics. Specifically, the daytime threshold effect of UR was identified at 0.104, beyond which it began to mitigate the SUHI and gradually stabilized. The nighttime threshold was 0.018, beyond which it continuously mitigated the SUHI. Spatially, the cooling effect of UR strengthened progressively from west to east. Temporally, the mitigation threshold of UR continuously advanced from 0.108 to 0.037, accompanied by an increasing degree of mitigation. This study elucidates the complex interactive feedback mechanisms between resilience and the thermal environment in arid and semi-arid urban agglomerations. These findings provide a scientific basis for optimizing the spatial structure and enhancing climate adaptability within the Guanzhong Urban Agglomeration.</p>

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Nonlinear effect and spatiotemporal heterogeneity of urban resilience on surface urban heat Island in the Guanzhong urban agglomeration

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月6日

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  • Jiangmin Wu,
  • Wei Zhao,
  • Zhen Yan,
  • Qirui Zhang,
  • Bin Lian,
  • Zaixing Chen,
  • Jiachen Yang,
  • Yuxiang Lan

摘要

Amid the dual contexts of rapid urbanization and global warming, the Surface Urban Heat Island (SUHI) effect has been identified as a pivotal climatic issue that poses severe threats to urban sustainable development and public health. Urban Resilience (UR), in turn, has been widely recognized as a systematic and holistic pathway to mitigate the SUHI effect and optimize the urban thermal environment. Based on the three-dimensional Scale-Density-Morphology theoretical framework, this study constructed a comprehensive UR evaluation system, using 2000–2024 long-time-series remote sensing and socio-economic data, combined with XGBoost-SHAP, Double Machine Learning (DML), and Geographically and Temporally Weighted Regression (GTWR) models, to systematically analyze UR’s nonlinear effects, critical thresholds, diurnal differences, and spatiotemporal differentiation on SUHI. During the study period, the SUHI in the Guanzhong Urban Agglomeration continuously intensified, increasing from 0.14 °C to 0.48 °C during the daytime and from 0.10 °C to 0.22 °C at night. Concurrently, the UR exhibited a continuous decline, dropping from 0.12 to 0.06. Urban resilience exerted a significant negative causal effect on the SUHI, demonstrating typical nonlinear and threshold characteristics. Specifically, the daytime threshold effect of UR was identified at 0.104, beyond which it began to mitigate the SUHI and gradually stabilized. The nighttime threshold was 0.018, beyond which it continuously mitigated the SUHI. Spatially, the cooling effect of UR strengthened progressively from west to east. Temporally, the mitigation threshold of UR continuously advanced from 0.108 to 0.037, accompanied by an increasing degree of mitigation. This study elucidates the complex interactive feedback mechanisms between resilience and the thermal environment in arid and semi-arid urban agglomerations. These findings provide a scientific basis for optimizing the spatial structure and enhancing climate adaptability within the Guanzhong Urban Agglomeration.