Unravelling the multilevel and multi-dimensional impacts of building and tree on surface urban heat islands

Abstract

The multilevel effects of landscape composition and configuration on daytime land surface temperature (LST) has been examined. However, how 2D and 3D characteristics of building and tree hierarchically interact to influence LST and how such effects vary diurnally were yet unknown. Using thermal satellite imagery, 2D and 3D characteristics of urban landscapes, and multilevel models (i.e. the random intercept model (RIM) and the random coefficient model (RCM)), we quantified the multi-dimensional and hierarchical effects of buildings and trees on LST as well as their diurnal contrast. Our results showed that combining landscape pattern and 3D urban morphology can capture more of the variation in diurnal LST than using them separately, regardless of single-level ordinary least squares (OLS) and multilevel models. Moreover, the multilevel models performed better than OLS models in explaining the impacts of landscape pattern and 3D urban morphology on LST for both day and night, and the RCM performed better than that the RIM. During the day, the standard deviations of the residual and autocorrelation in the residual for the RCM were 1.315 and 0.131, respectively, but 1.715 and 0.312 for OLS, respectively. Similarly, a smaller autocorrelation in the residual was produced by the RCM (0.155) than by OLS (0.366) at night. The spatial heterogeneity of LST was linked tightly to the percent cover of trees and the largest patch index of tree during the day, but was primarily dominated by the edge density of the buildings and the mean building height at night. Moreover, we found significant differences in the random effects of the composition and 3D urban morphology on the LST at the block level. The random impacts of the percent cover of buildings on both daytime and nighttime LSTs varied most across urban blocks. These findings provide urban planners and researchers a more thorough picture of LST-landscape associations from multi-dimensional and multilevel perspectives.