Multi-scale impact of urban building function and 2D/3D morphology on urban heat island effect: a case study in Shanghai, China

In the process of urbanization, building functions and morphologies affect the urban heat island (UHI) effect. However, existing studies lack influence analysis of the building function and cross-scale effects on UHI. In this study, the land surface temperature (LST) of Shanghai was retrieved using Radiative Transfer Equation (RTE), Mono-Window (MW), and Split Window (SW) algorithms. Building functions were classified, and influencing factors of building morphology and function were calculated at various scales. Finally, a multi-scale analysis was conducted using Pearson correlation coefficient and Random Forest model. The results show that: 1) MW algorithm had the highest accuracy in LST retrieval. Among the building classification results, residential buildings were the most (65.11 %), while transportation buildings were the least (1.9 %). 2) As the analysis scale increased, although the correlation coefficients generally showed an increasing trend, have a downward trend at 3000–4000 m. The correlation coefficients of residential and commercial type proportion, building density and coverage ratio all transition from moderate to strong correlations and were larger than those of other factors at almost every scale, with a significant impact on LST. 3) The dominant factors influencing LST varied across different scales. The contribution of building coverage ratio and industrial type proportion to LST at all scales has been large. These findings provide scientific references for urban planning, architecture, and thermal environment governance.