Abstract
ContextRelationships between spatial configuration of urban form and land surface temperature (LST) in the excess heat mitigation context are studied over larger tracts of land not allowing for micro-scale recommendations to urban design.ObjectivesTo identify spatial configuration descriptors (SCDs) of urban form and the size of zone of influence conducive to the formation of the coldest and hottest land cover (LC) patches of different types (buildings, grass, paved and trees) from 2 m resolution LC and 2 and 100 m resolution LST maps at two time-steps in the summer.MethodsRandom Forest regression models were deployed to explain the LST of individual LC patches of different types based on SCDs of core LC patches and patches in their neighbourhoods. ANOVA was used to determine significantly different values of the most important SCDs associated with the coldest and hottest LC patches, and analysis of quartiles informed specification of their ranges.ResultsUrban form in the immediate neighbourhood to the core LC patches had a strong influence on their LST. Low elevation, high proximity to water, and high aggregation of trees, being important to the formation of the coldest patches of all types. High resolution of LST contributed to a higher accuracy of results. Elevation and proximity to water gained in importance as summer progressed.ConclusionsSpatial configuration of urban form in the nearest proximity to individual LC patches and the use of fine resolution LST data are essential for issuing heat mitigation recommendations to urban planners relevant to micro-scales.
Highlights
The thermal urban environment has been widely studied in the context of the urban heat island (UHI) (Oke 1976) effect, occurring when air temperature is consistently higher in urban areas than in their rural surroundings, due to its implications on human health (Heaviside et al 2016, 2017), ecology (Yow 2007), and energy use (Santamouris et al 2015)
Accuracy of predictions of land surface temperature (LST) within land cover subtypes differed with overall aggregation level of b Fig. 4 Root mean square error (a) and R2 (b) obtained from Random Forests (RF) models relating LST at two dates (June and July 2013) and spatial resolutions (2 m and 100 m) to spatial configuration descriptors for all patches of a given LC class (ALL) and separately for LC patches contained within Tier 1 clusters (LA least aggregated, RLA relatively less aggregated, RMA relatively more aggregated, MA most aggregated)
‘Core’ refers to models constructed with spatial configuration descriptors for core patches only, whilst 10 m, etc., indicate models with addition of patches intersecting with consecutive zones around the core patches land cover patches and displayed a common trend such that small and fragmented land cover (LA) patches had a lower root mean square error (RMSE) and higher R2 than largest and most aggregated (MA) ones
Summary
The thermal urban environment has been widely studied in the context of the urban heat island (UHI) (Oke 1976) effect, occurring when air temperature is consistently higher in urban areas than in their rural surroundings, due to its implications on human health (Heaviside et al 2016, 2017), ecology (Yow 2007), and energy use (Santamouris et al 2015). Connors et al (2013); Chen et al (2014); Zhou et al (2020); Sun et al (2020a, b) Whilst these studies, due to the coarse spatial resolution of the LST imagery, focus on explanation of the LST within relatively large and variedly defined subdivisions of towns, they may lack in sufficient detail regarding spatial configuration of individual land cover patches contributing to the thermal comfort outdoors (Perini et al 2017; Li et al 2020c) or within building interiors (Futcher et al 2013; Garshasbi et al 2020), relevant to microscales rather than neighbourhoods or city districts. We adopted a flipped methodological approach that moved away from quantification of cooling distances of urban green–blue spaces, such as for example in a recent and insightful study by Sun et al (2020b), but rather investigated the size and composition of target patches’ neighbourhoods with an aspiration to provide urban design recommendations tailored to their spatial characteristics
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