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Lookup NU author(s): Dr Tatiana Alvares-SanchesORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2019. The urban heat island effect is an important 21st century issue because it intersects with the complex challenges of urban population growth, global climate change, public health and increasing energy demand for cooling. While the effects of urban landscape composition on land surface temperature (LST) are well-studied, less attention has been paid to the spatial arrangement of land cover types especially in smaller, often more diverse cities. Landscape configuration is important because it offers the potential to provide refuge from excessive heat for both people and buildings. We present a novel approach to quantifying how both composition and configuration affect LST derived from Landsat imagery in Southampton, UK. First, we trained a machine-learning (generalized boosted regression) model to predict LST from landscape covariates that included the characteristics of the immediate pixel and its surroundings. The model achieved a correlation between predicted and measured LST of 0.956 on independent test data (n = 102,935) and included predictors for both the immediate and adjacent land use. In contrast to other studies, we found adjacency effects to be stronger than immediate effects at 30 m resolution. Next, we used a landscape generation tool (Landscape Generator) to alter landscape configuration by varying natural and built patch sizes and arrangements while holding composition constant. The generated neutral landscapes were then fed into the machine learning model to predict patterns of LST. When we manipulated landscape configuration, the average city temperature remained the same but the local minima varied by 0.9 °C and the maxima by 4.2 °C. The effects on LST and heat island metrics correlated with landscape fragmentation indices. Moreover, the surface temperature of buildings could be reduced by up to 2.1 °C through landscape manipulation. We found that the optimum mix of land use types is neither at the land-sharing nor land-sparing extremes, but a balance between the two. In our city, maximum cooling was achieved when ~60% of land was left natural and distributed in 7–8 patches km−2 although this could be location dependent and further work is needed. Opportunities for urban cooling should be required in the planning process and must consider both composition and configuration at the landscape scale if cities are to build capacity for a growing population and climate change.
Author(s): Osborne PE, Alvares-Sanches T
Publication type: Article
Publication status: Published
Journal: Computers, Environment and Urban Systems
Year: 2019
Volume: 76
Pages: 80-90
Print publication date: 01/07/2019
Online publication date: 17/04/2019
Acceptance date: 12/04/2019
Date deposited: 08/02/2024
ISSN (print): 0198-9715
ISSN (electronic): 1873-7587
Publisher: Elsevier Ltd
URL: https://doi.org/10.1016/j.compenvurbsys.2019.04.003
DOI: 10.1016/j.compenvurbsys.2019.04.003
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