Exploring Urban Heat Distribution and Thermal Comfort Exposure Using Spatiotemporal Weighted Regression (STWR)

Abstract

With rapid urbanization, many cities have experienced significant changes in land use and land cover (LULC), triggered urban heat islands (UHI), and increased the health risks of citizens’ exposure to UHI. Some studies have recognized residents’ inequitable exposure to UHI intensity. However, few have discussed the spatiotemporal heterogeneity in environmental justice and countermeasures for mitigating the inequalities. This study proposed a novel framework that integrates the population-weighted exposure model for assessing adjusted thermal comfort exposure (TCEa) and the spatiotemporal weighted regression (STWR) model for analyzing countermeasures. This framework can facilitate capturing the spatiotemporal heterogeneities in the response of TCEa to three specified land-surface and built-environment parameters (i.e., enhanced vegetation index (EVI), normalized difference built-up index (NDBI), and modified normalized difference water index (MNDWI)). Using this framework, we conducted an empirical study in the urban area of Fuzhou, China. Results showed that high TCEa was mainly concentrated in locations with dense populations and industrial regions. Although the TCEa’s responses to various land-surface and built-environment parameters differed at locations over time, the TCEa illustrated overall negative correlations with EVI and MNDWI while positive correlations with NDBI. Many exciting spatial details can be detected from the generated coefficient surfaces: (1) The influences of NDBI on TCEa may be magnified, especially in rapidly urbanizing areas. Still, they diminish to some extent, which may be related to the reduction in building construction activities caused by the COVID-19 epidemic and the gradual improvement of urbanization. (2) The influences of EVI on TCEa decline, which may be correlated with the population increase. (3) Compared with NDBI, the MNDWI had more continuous and stable significant cooling effects on TCEa. Several mitigation strategies based on the spatiotemporal heterogeneous relationships also emanated. The effectiveness of the presented framework was verified. It can help analysts effectively evaluate local thermal comfort exposure inequality and prompt timely mitigation efforts.

Keywords

• thermal comfort exposure
• mitigation countermeasure analysis
• spatiotemporal heterogeneity
• spatiotemporal weighted regression (STWR)