Optimization of tree locations to reduce human heat stress in an urban park

Hao, T., Zhao, Q. and Huang, J. (2023) Optimization of tree locations to reduce human heat stress in an urban park. Urban Forestry and Urban Greening, 86, 128017. (doi: 10.1016/j.ufug.2023.128017)

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Trees provide cooling benefits through shading and evapotranspiration; they are regarded as an important measure in heat-resilient urban planning and policies. Knowing where to plant trees for maximum cooling benefits, given practical and resource constraints, remains a challenge in both practice and research. Literature in the field of tree modeling and location optimization is limited, either by the incompleteness in accounting for tree shading, evapotranspiration, and the modifying effect of wind, or by the slow-running speed of the Computational Fluid Dynamics model, making them less applicable in practice. This paper describes a novel method to search for the optimal locations for trees to maximize their cooling benefits in an urban environment. A rapid simulation model was applied to assess on-site heat stress under the influences of trees, which was evaluated using field measurements conducted under hot, temperate, and cool weather conditions in an urban park in Hong Kong. It was then linked to a genetic algorithm in search of a near-optimal tree layout. The proposed method was tested in the same park, and it can automatically identify locations to plant new trees to minimize heat stress, subject to practical constraints such as avoiding existing buildings and utilities. It can also identify the optimal locations to rearrange the existing 55 trees, hypothetically, which can cool the park by up to 0.3 ℃ in on-site average equivalent temperature compared with the worse scenario. Trees can cool the most if they are concentrated on the leeward side of the park, rather than spread evenly. The proposed method runs significantly faster than existing approaches, and it can inform research and landscape design practices concerning park cooling as a goal.

Item Type:Articles
Additional Information:The research is supported by two grants from the National Natural Science Foundation of China (#51978594 & #51708473). The study is also funded in part by the Hong Kong Research Grants Council Theme-Based Research Scheme under Grant T22–504/21-R and by the ESRC’s ongoing support for the Urban Big Data Centre (UBDC) [ES/L011921/1 and ES/S007105/1].
Glasgow Author(s) Enlighten ID:Zhao, Dr Qunshan
Authors: Hao, T., Zhao, Q., and Huang, J.
College/School:College of Social Sciences > School of Social and Political Sciences > Urban Studies
Journal Name:Urban Forestry and Urban Greening
ISSN (Online):1610-8167
Published Online:29 June 2023
Copyright Holders:Copyright © 2023 The Authors
First Published:First published in Urban Forestry and Urban Greening 86:128017
Publisher Policy:Reproduced under a Creative Commons License

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
190698Urban Big Data Research CentreNick BaileyEconomic and Social Research Council (ESRC)ES/L011921/1S&PS - Urban Big Data
304042UBDC Centre TransitionNick BaileyEconomic and Social Research Council (ESRC)ES/S007105/1S&PS - Administration