Abstract/Summary

With global warming and rapid urban growth, cities get warmer, which poses additional stress on human thermal comfort and health. Complex three-dimensional (3D) urban forms change radiation fluxes and shade patterns in cities, but most studies that link urban form to thermal exposure have traditionally investigated the horizontal, two-dimensional composition and configuration of urban landscapes. Supported by high-precision airborne LiDAR data and IKONOS satellite data, this study calculates 3D urban landscape metrics for central Nanjing, China, including vegetation above ground biomass (AGB), building volume (VB), standard deviation of building and vegetation heights (HSDB, HSDV), the building normalized compactness radio (nCR), sky view factor (SVF), surface roughness (SR), and shadow patterns (SP). Diurnal hourly mean radiant temperature (Tmrt) is simulated using the UMEP (Urban Multi-scale Environmental Predictor) tool forced with fixed-point observation data for a typical hot summer day. Correlation and multiple regression analyses are conducted to investigate the relationship between the 3D form metrics and Tmrt and to identify key factors that influence the thermal environment. Tmrt varies spatially and diurnally and is strongly related to SP during the day, revealing the importance of solar access for modulating the thermal environment. AGB is negatively, but SVF, SP, and building nCR are positively correlated with daytime Tmrt. At night, Tmrt is more homogeneous across space and mainly impacted by the urban fabric's ability to lose heat. Open areas cool faster than areas with low SVF and complex urban forms with high building nCR. Findings from this study have great scientific and practical significance for optimizing urban landscape patterns from a human-centered heat exposure perspective and will guide planning and design strategies to promote thermally comfortable urban environments.