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<p>Urban densification affects local land surface temperature (LST) and can potentially exacerbate heat waves within urban areas with negative impacts on human health. Effective urban climate management requires a good understanding of the main drivers of intra-urban LST variability, such as urban tree height and coverage, building types, height, and density, as well as the proportions of roads and water bodies. Unlike traditional urban heat island studies, which typically compare urban and rural temperature differences, this study exploits high-resolution remote sensing-based datasets and machine learning models to analyze variations in LST within urban areas across Europe. Our results reveal that increasing building density, particularly non-residential structures, consistently leads to higher local LST. However, enhancing urban tree coverage emerges as a highly effective strategy to counteract this heat intensification, particularly in warmer southern European climates during summer. Notably, a modest increase in tree cover (around 15%) can substantially mitigate heat, effectively neutralizing the temperature rise from expanding non-residential built areas by up to 40%. These findings highlight the critical role of urban greenery in climate management, emphasizing that strategically increasing tree cover can significantly offset heat impacts associated with urban expansion. This insight provides practical guidance for urban planners and policymakers aiming to implement targeted, nature-based solutions for more resilient urban environments.</p>

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A remote sensing-based assessment of the cooling effects of urban trees in European cities

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年4月28日

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  • Yang Su,
  • David Makowski,
  • Xianglin Zhang,
  • Siyu Liu,
  • Ke Yu,
  • Yidi Xu,
  • Haotian Chen,
  • Shuaishuai Deng,
  • Tianqi Shi,
  • Chuanlong Zhou,
  • Songchao Chen,
  • Haoruo Li,
  • Peng Zhu,
  • Wenfeng Liu,
  • Chaohui Yin,
  • Nikola Besic,
  • Martin Brandt,
  • Alexandre d’Aspremont,
  • Philippe Ciais

摘要

Urban densification affects local land surface temperature (LST) and can potentially exacerbate heat waves within urban areas with negative impacts on human health. Effective urban climate management requires a good understanding of the main drivers of intra-urban LST variability, such as urban tree height and coverage, building types, height, and density, as well as the proportions of roads and water bodies. Unlike traditional urban heat island studies, which typically compare urban and rural temperature differences, this study exploits high-resolution remote sensing-based datasets and machine learning models to analyze variations in LST within urban areas across Europe. Our results reveal that increasing building density, particularly non-residential structures, consistently leads to higher local LST. However, enhancing urban tree coverage emerges as a highly effective strategy to counteract this heat intensification, particularly in warmer southern European climates during summer. Notably, a modest increase in tree cover (around 15%) can substantially mitigate heat, effectively neutralizing the temperature rise from expanding non-residential built areas by up to 40%. These findings highlight the critical role of urban greenery in climate management, emphasizing that strategically increasing tree cover can significantly offset heat impacts associated with urban expansion. This insight provides practical guidance for urban planners and policymakers aiming to implement targeted, nature-based solutions for more resilient urban environments.