Directionally and spatially varying relationship between land surface temperature and land-use pattern considering wind direction: a case study in central China

The spatially varying relationship between land surface temperature (LST) and land-use factors at a large scale has been widely studied by geographically weighted regression (GWR) models. However, the directionally varying relationship caused by wind directions has not yet been considered. In this study, the wind directions in the summer and the winter of Wuhan in 2017 were extracted to build a geographically-directionally weighted regression (GDWR) to identify the spatially and directionally varying relationships between them. The results indicated that both the R-2 and the significance have been improved by the GDWR model in the summer and the winter. Specially, the GDWR performed best in the winter of 2017, increasing R-2 from 0.0688 to 0.6635 provided by ordinary least squares (OLS)-based multiple linear regression (MLR) and GWR, to 0.7839 by the GDWR, with P-value lower than 0.05 all across the study area. Furthermore, the residual has been dramatically reduced in the north and southeast part of Wuhan by GDWR in the winter. It's probably due to the fact that in the winter, wind was flowed from south to north. But the GDWR did not reduce the residual in central Wuhan. It suggests that the wind would cause an obviously directionally varying relationship in the suburbs; while it would not make a significant impact on the relationship between LST and its driving factors in the central city where complex land uses existed.