4.7 Article

Separate and combined effects of 3D building features and urban green space on land surface temperature

期刊

JOURNAL OF ENVIRONMENTAL MANAGEMENT
卷 295, 期 -, 页码 -

出版社

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2021.113116

关键词

3D building metrics; Landscape metrics; Thermal environment; Boosted regression tree; Blocks

资金

  1. Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resource [KF-2020-05-067]
  2. National Natural Science Foundation of China [41961027]
  3. Key Talent Projects in Gansu Province [2021]
  4. LZJTU EP [201806]

向作者/读者索取更多资源

The study found that building coverage ratio is one of the most influential factors in urban land surface temperature, with high-rise buildings helping to alleviate LST, while low- and mid-rise buildings contribute to heating the surrounding areas. Green coverage ratio, edge density, and patch density are the most important factors in urban green spaces, with the cooling effect of UGS being obscured when buildings have a large coverage. The key to alleviating the heat island effect lies in the reasonable planning and optimization of the 3D built environment.
Deduction of urban green space (UGS) and the multidimensional growth of building have exacerbated the urban heat island (UHI). Yet thorough investigations into how 3D building features and UGS combinedly influence urban land surface temperature (LST) are limited, especially at the road-based blocks scale. Therefore, the study uses the boosted regression tree (BRT) model to explore the relative contribution and marginal effects of the influential factors on LST, and 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 with a relative contribution of 44.6%. 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 influential factors among six UGS metrics, with the relative contribution of 21.0%, 20.9%, and 20.4%, respectively. (3) Comprehensively considering 13 metrics, we find that the dominant influential factor is BCR with a relative contribution of 28.3%, while the regulation amplitudes to LST of aggregation index (AI) and GCR dramatically reduced. These findings indicate that the cooling effect of UGS will be obscured when the buildings coverage is large. Hence, only relying on UGS to alleviate the heat island effect seems inadequate, the keys are the reasonable planning and optimization of 3D built environment.

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