Spatially non-stationary effect of underlying driving factors on surface urban heat islands in global major cities

Long Li, Yong Zha, Jiahua Zhang
2020 International Journal of Applied Earth Observation and Geoinformation  
A R T I C L E I N F O Keywords: surface urban heat island spatial non-stationarity driving factors geographically weighted regression A B S T R A C T Urban heat island (UHI) effect is among the most typical characteristics of urban climate. The analysis of surface UHI (SUHI) mechanisms has received the most extensive attention in the world. Here, we quantify the diurnal and seasonal SUHI intensity (SUHII) in global 419 major cities during the period 2003-2013. A geographically weighted
more » ... n (GWR) was established to assess the relationships between SUHII and several driving factors, and it further was compared to the ordinary least square (OLS) and stepwise multiple linear regression (SMLR) models. We show that GWR model has higher determination coefficient (R 2 ) than OLS and SMLR models (Time: summer daytime, summer night, winter daytime and winter nighttime; GWR: 0.805, 0.458, 0.699 and 0.582; OLS: 0.732, 0.347, 0.473 and 0.320; SMLR: 0.732, 0.341, 0.468 and 0.316), indicating the spatially nonstationarity in the relationships. During the day, both vegetation activity and tree cover fraction have stronger cooling effect on SUHI in the summer of Asia. At night, there are stronger albedo effects on SUHI in the summer of Eastern Asia and Western North America and in the winter of Eastern Asia. Furthermore, temperature has stronger effect on daytime SUHI in Africa, Europe and South America in summer, and precipitation has stronger effect on nighttime SUHI in Africa and Europe in summer. Our results emphasize the spatial variation of the relationships between SUHII and relevant driving factors across global major cities, further indicating that the spatially non-stationary effect of driving factors on SUHII need to be considered in the future.
doi:10.1016/j.jag.2020.102131 fatcat:aus2fxlrlvduzgymgknsgnsuwm