Abstract
ContextRelationships between land surface temperature (LST) and spatial configuration of urban form described by landscape metrics so far have been investigated with coarse resolution LST imagery within artificially superimposed land divisions. Citywide micro-scale observations are needed to better inform urban design and help mitigate urban heat island effects in warming climates.ObjectivesThe primary objective was to sub-divide an existing high-resolution land cover (LC) map into groups of patches with distinct spatial and thermal properties suitable for urban LST studies relevant to micro-scales. The secondary objective was to provide insights into the optimal analytical unit size to calculate class-level landscape metrics strongly correlated with LST at 2 m spatial resolution.MethodsA two-tiered unsupervised k-means clustering analysis was deployed to derive spatially distinct groups of patches of each major LC class followed by further subdivisions into hottest, coldest and intermediary sub-classes, making use of high resolution class-level landscape metrics strongly correlated with LST.ResultsAggregation class-level landscape metrics were consistently correlated with LST for green and grey LC classes and the optimal search window size for their calculations was 100 m for LST at 2 m resolution. ANOVA indicated that all Tier 1 and most of Tier 2 subdivisions were thermally and spatially different.ConclusionsThe two-tiered k-means clustering approach was successful at depicting subdivisions of major LC classes with distinct spatial configuration and thermal properties, especially at a broader Tier 1 level. Further research into spatial configuration of LC patches with similar spatial but different thermal properties is required.
Highlights
IntroductionRecent decades have seen a rise in research (Wu and Ren 2019) regarding spatial configuration of urban form and its relationship to urban heat island (UHI) (Oke 1976) or surface urban heat island (SUHI) (Barring et al 1985) effects, deriving from concerns over climate change impacts on increased incidence of heatwaves (Perkins et al 2012; Wouters et al 2017) and related negative impacts on human health (Lin et al 2009; Basara et al 2010; Milojevic et al 2011; Heaviside et al 2016, 2017), among others, aggravated by urban growth (Chapman et al 2017; United Nations 2019).The impact of urban form on UHI is often described through direct measurements of air temperature across different urban gradients (Schwarz et al 2012; Lin et al 2019) or through street-scale simulations (Sodoudi et al 2018; Ramyar et al 2019) allowing for micro-scale assessments
At 100 m window size for 2 m land surface temperature (LST) in June, the strongest correlations were observed for greenspaces, with grass and trees being positively correlated with LSI (0.57 and 0.53) and negatively correlated with COHESION (- 0.59 and - 0.60) and PLADJ (- 0.62 and - 0.66)
Whilst investigation of all effects of spatial configuration of urban form on the LST observed in Tier 2 clusters is still ongoing (Zawadzka et al In Preparation), this study has revealed that relationships between class-level landscape metrics and 2 m resolution LST are strongest at smaller parcels of land than in the case of coarser resolution LST datasets investigated in other studies, and that these relationships weaken as the summer progresses
Summary
Recent decades have seen a rise in research (Wu and Ren 2019) regarding spatial configuration of urban form and its relationship to urban heat island (UHI) (Oke 1976) or surface urban heat island (SUHI) (Barring et al 1985) effects, deriving from concerns over climate change impacts on increased incidence of heatwaves (Perkins et al 2012; Wouters et al 2017) and related negative impacts on human health (Lin et al 2009; Basara et al 2010; Milojevic et al 2011; Heaviside et al 2016, 2017), among others, aggravated by urban growth (Chapman et al 2017; United Nations 2019).The impact of urban form on UHI is often described through direct measurements of air temperature across different urban gradients (Schwarz et al 2012; Lin et al 2019) or through street-scale simulations (Sodoudi et al 2018; Ramyar et al 2019) allowing for micro-scale assessments. The relationship of urban form and the SUHI effect is typically investigated from remotely sensed land surface temperature (LST) imagery at medium (30 m) to very coarse (1 km) spatial resolutions, offering an opportunity for city-wide assessments, compromising applicability of the results to micro-scales by summarising the results over larger subdivisions of land (Zhou et al 2011, 2020; Kong et al 2014; Liu et al 2016; Simwanda et al 2019; Masoudi et al 2019). Use of medium to coarse resolution LST imagery within artificially superimposed land divisions allows for neighbourhood to district-scale assessments whose aggregated character may lack in detail specific to urban design conducive to thermal comfort outdoors (Perini et al 2017; Li et al 2020) or within building interiors (Futcher et al 2013; Garshasbi et al 2020)
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