Presentation by Dr. Qunshan Zhao

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Abstract: 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 modelling 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 for reducing human heat stress. 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 under the Hong Kong climate conditions if they are concentrated on the leeward side of the park, rather than spread evenly. The proposed method can inform research and landscape design practices concerning park cooling as a goal.

Speaker Bio: Dr. Qunshan Zhao is a Senior Lecturer (Associate Professor) in Urban Analytics in Urban Studies and Urban Big Data Centre (UBDC) in the School of Social and Political Sciences at the University of Glasgow. He holds the Ph.D. in GIScience from the Arizona State University. Qunshan's research interest focuses on creating a sustainable urban future and tackling related social, economic, and environmental problems by using new forms of data and related analytical approaches. Ongoing research efforts include urban infrastructure location optimization, human mobility analysis by using mobile phone app data, urban resilience and fuel poverty, 3D city modelling and digital twins, and open-source spatial optimization methods development (pysal/spopt). He has been the PI/Co-PI of multiple research projects from the UK Economic and Social Science Council (ESRC), Bill & Melinda Gates Foundation, Royal Society, American Association of Geographers, National Nature Science Foundation of China, and Glasgow City Council. 

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