Assessing the impact of urban morphological parameters on land surface temperature in the heat aggregation areas with spatial heterogeneity: A case study of Nanjing

• Published in: Building and environment 2023-05, Vol.235, p.110232, Article 110232
• Main Authors: Wu, Zihao, Tong, Ziyu, Wang, Mingzhu, Long, Qianhui
• Format: Article
• Language: English
• Subjects: Geographically weighted regression model; Heat aggregation areas; Land surface temperature; Spatial heterogeneity; Urban heat island; Urban morphology
• ISSN: 0360-1323; 1873-684X
• DOI: 10.1016/j.buildenv.2023.110232

In recent years, many studies on urban morphology have investigated the urban heat island. However, most of the studies have focused on the whole city rather than on heat aggregation areas. Also, their assessments rarely consider local variations of LST impacting factors, and their results lack planning applicability. In this study, the main urban area of Nanjing was used as a case study. Using open data, heat aggregation areas were identified and the impact of urban morphological parameters on LST in daytime was assessed. Based on the urban morphological parameters and their responses to LST, some morphological optimization strategies for heat aggregation areas with spatial heterogeneity were proposed. The results show that forest index (FI) (91.71%), water index (WI) (90.23%) and floor area ratio (FAR) (91.94%) suggest a negative effect on LST, while impervious surface index (ISI) (79.31%) and building density (BD) (95.55%) seem to have a positive effect on LST. And the correlation with the indicators in three dimensions and LST is unclear. Spatial heterogeneity within heat aggregation areas also exists. Based on this, this study suggests targeted local strategies for LST mitigation based on the overall optimization strategy. This study contributes to sustainable urban planning by providing useful insights into the influence of urban morphological parameters on LST. •A method for identifying the heat aggregation areas in the city was proposed.•Impact of urban morphological parameters was analyzed with local regression model.•It is suggested that FI, WI, and FAR negatively impacted LST, while ISI and BD impacted positively.•Indicators were found spatial heterogeneous in heat aggregation areas.•Targeted morphological optimization strategies for heat aggregation areas were suggested.