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This chapter used the boosted regression tree (BRT) model to explore the relative contribution and marginal effects of the driving factors on LST and to quantify the warming/cooling effects of buildings and UGS. Results show that (1) building coverage ratio (BCR) is the most influential factor among seven building metrics. Besides, high-rise buildings tend to alleviate LST, while low- and mid-rise buildings heat the surroundings. (2) Green coverage ratio (GCR), edge density (ED), and patch density (PD) are the most influencing factors among six UGS metrics. (3) Comprehensively considering 13 metrics, the dominant driving factor of LST is BCR, while the regulation amplitudes to LST of aggregation index (AI) and GCR dramatically lessened.

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Urban Landscape Marginal Effects on Land Surface Temperature

  • 章节

  • 发表日期：

    2025年

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  • Liang Zhou,
  • Bo Yuan,
  • David López-Carr,
  • Fengning Hu

摘要

This chapter used the boosted regression tree (BRT) model to explore the relative contribution and marginal effects of the driving factors on LST and to quantify the warming/cooling effects of buildings and UGS. Results show that (1) building coverage ratio (BCR) is the most influential factor among seven building metrics. Besides, high-rise buildings tend to alleviate LST, while low- and mid-rise buildings heat the surroundings. (2) Green coverage ratio (GCR), edge density (ED), and patch density (PD) are the most influencing factors among six UGS metrics. (3) Comprehensively considering 13 metrics, the dominant driving factor of LST is BCR, while the regulation amplitudes to LST of aggregation index (AI) and GCR dramatically lessened.