Prediction models of urban heat island based on landscape patterns and anthropogenic heat dynamics

Abstract

The influence of landscape patterns on urban thermal environment has received remarkable attention with the rapid urbanization process worldwide. Although numerous studies have revealed the relationship between landscape patterns and the urban thermal environment, there is limited effort to quantify the contributions of landscape patterns and anthropogenic heat to urban heat islands (UHI) under the seasonal and daily dynamics. This study aims to identify the effects of landscape patterns and anthropogenic heat on UHI intensity in the daytime and nighttime as well as in different seasons. We first used remotely sensed images to extract the landscape patterns and land surface temperature. Anthropogenic heat was quantified through energy consumption data. Multivariate stepwise regression was used to quantify the effects of landscape patterns and anthropogenic heat on UHI intensity. Eight models were constructed for daytime and nighttime UHI intensity in spring, summer, fall, and winter, respectively. Results demonstrated that the presence of buildings is the main factor affecting UHI intensity in urban area for three seasons except summer. Basically, the contributions of landscape configuration to the UHI in the daytime is higher than landscape composition, while the opposite is true at night. The contribution of anthropogenic heat was low in all seasons due to the high correlation with non-monolayer buildings. The nighttime UHI intensity models fit better than the daytime, especially in the winter. This study contributes to the understanding of landscape influence on UHI intensity and provides practical guidelines for landscape planning to mitigate UHI effects.