Effects of block morphology on the surface thermal environment and the corresponding planning strategy using the geographically weighted regression model

Abstract

Although an increasing number of studies have explored how spatial morphology influences the urban heat island (UHI) effect in different regions with the spatial regression methods, few studies further explored the potential significance of the identified spatial differences at the block level. In this study, 410 regulatory management units with diverse block features in Xi'an, China were screened as the research samples, and 14 block morphological indicators from three categories of land cover, building group, and distance to cold and heat sources were calculated with multi-source data. The Geographically Weighted Regression (GWR) model combined with spatial autocorrelation analysis was applied to quantitatively explore the spatial heterogeneity of land surface temperature (LST) and its relationship to various morphological factors. Results confirm that the GWR model with the better modeling fit (R2 = 0.836, Adj.R2 = 0.785, AICc = 977.510, RMSE = 0.696, and MAPE = 0.013) is an effective method for addressing the spatial relationship between block morphology and LST. Furthermore, the target control strategy was finally proposed in five zoning blocks according to the contribution of morphological variables. ISR is the most influential factor that intensifies the UHI effect, while GR is a critical factor that form the cool urban island in different blocks. Immediate improvement measures should be taken for Zone 1 with the most severe UHI effect by controlling the key indicators of ISR, BD, and GR. This study sheds new light on the spatial variations of the morphology-LST linkage at the block level and provides heat-mitigation regulation recommendations for urban planners and policy makers.