Comprehensive effect of the three-dimensional spatial distribution pattern of buildings on the urban thermal environment

The three-dimensional spatial distribution pattern of buildings is an important factor causing the spatial differences in the urban thermal environment. The study units were divided based on the urban road network, DEM, and building big data in Jinan. The Landsat 8 remote sensing images were used to invert the land surface temperature (LST), and Kriging interpolation was used to obtain the spatially continuous air temperature (AT). The integrated LST and AT represented the urban thermal environment. By constructing three-dimensional spatial distribution indicators of buildings and using analysis of variance and multiple correspondence analysis methods, the influence of the three-dimensional spatial distribution pattern of buildings on the urban thermal environment was comprehensively investigated. The results showed that all the indicators of the three-dimensional spatial distribution of buildings were factors that have prominent influence on the urban thermal environment. The interaction of mean DEM respectively with building density, volume ratio, mean building height, and mean building volume demonstrated significant effects on both LST and AT, and the analysis of variance results of these indicators with each temperature reached a significance level of ≤0.05. The types and levels of the main strongly correlated indicators varied with increasing temperature levels. The optimal combination of levels corresponding to the lower LST depended on the terrain, while the lower AT was affected by a combination of buildings and terrain. The height indicators contributed more to LST than to AT. • The urban thermal environment were characterized with AT and LST. • Three-dimensional spatial distribution indicators were constructed. • Factors influencing UHIs were analyzed using one-way and multi-way ANOVA. • Using MCA to explore the changes of impact indicators at different levels of UHIs. • The height indicators showed a higher influence on LST than AT.