Study on the Response of the Summer Land Surface Temperature to Urban Morphology in Urumqi, China

Increases in urban temperature affect the urban ecological environment and human health and well-being. In urban morphology, building characteristics are important factors affecting the land surface temperature (LST). Contemporary research focuses mainly on the effects of land use, urban tissue configuration, and street networks on the LST, and the effects of building characteristics on the LST need to be further understood. The mean LST and the urban morphology indicators of a single grid were calculated via a remote sensing inversion and a spatial analysis, and a geographically weighted regression (GWR) model was established to explore the influence of the building coverage ratio (BCR), mean building height (BH_mean), floor area ratio (FAR), and mean sky view factor (SVF_mean) on the LST. The results show that the correlations between the urban morphology indicators and the LST at a scale of 100~500 m are of different degrees, and the correlations are more significant at a scale of 200 m. Therefore, the optimal spatial scale for studying the influence of urban morphology indicators on the LST is 200 m. The fitting effect of the GWR model is significantly better than that of the ordinary least squares (OLS) method, and the effects of each indicator on the thermal environment have spatial non-stationarity. The BCR, BH_mean, FAR, and SVF_mean differ in their ability to raise and lower the temperature in different spatial zones, and the order of influence is as follows: BCR > SVF_mean > FAR > BH_mean. This study will provide a reference for the urban planning of Urumqi.