The importance of spatial configuration of urban form in local temperature regulation investigated from very high resolution LST and land cover data and landscape metrics

Urban thermal environment is known to be strongly affected by the composition of urban land cover, with densely built-up areas characterised with distinctly higher temperatures than densely vegetated ones. These observations come from the analysis of relatively coarse land surface temperature (LST) satellite data and conclusions are typically derived for city districts or other variedly defined mapping units. Whilst these analyses provide useful insights to excess heat mitigation at city scales, these do not describe the nuance of the thermal response of the heterogenous urban form at local levels. This study investigated the relationship between LST of variedly configured immediate neighbourhoods of single patches of different land cover types (buildings, paved, grass, trees) extending from 0 to 100m away to determine the shape and type of urban features including water that contribute to the formation of cold and hot urban spaces. The study area comprised three English towns: Milton Keynes, Bedford, and Luton, collectively comprising a wide range of urban forms that are representative for England and other European towns located in the temperate climate zone. The analysis was carried out for two summer days a month apart, capturing the different thermal responses as temperatures rise over summer.  The microscale of the analysis was enabled by downscaled LST obtained from Landsat 8 thermal bands acquired at 100m resolution down to 2m, supported by high resolution spectral indices derived from very high resolution hyperspectral aerial imagery. Patch-level landscape metrics were used to describe the shape of the different patches of urban land cover derived from land cover map at 2m resolution. K-means analysis was used to determine groups of land cover patches of a given type with common thermal and spatial properties. Random forest regression algorithm was used to identify the important descriptors of LST for these groups and ANOVA analysis to determine statistically significant effects for various spatial configuration metrics. The findings suggested that the coldest patches of buildings, grass and paved were associated with highly aggregated patches of trees in the immediate neighbourhood, with PLADJ greater than 73 to 85% and COHESION greater than 93 to 97%, and buildings requiring somewhat lower aggregation levels than grass or paved. Hottest patches of these land cover classes were associated with PLADJ smaller than 63–69% and COHESION smaller than 83–87%, with elevation and distance to water being the most important factors, whose importance increased as the summer progressed. Overall, this study provided further insights into the spatial characteristics of patches of common land cover types in urban areas that contribute to the formation of particularly hot or cold urban spaces, which can facilitate the design of climate resilient cities.