The effects of building density on land surface temperature (LST) and its spatial patterns remain poorly understood over large areas. Using Landsat 8 satellite imagery, we quantified the effects of building density on land surface temperature (K) across 21 cities in China and analysed their spatial patterns, possible factors, and mechanisms. Results showed that the effects of building density on LST were more significant in areas with dry climates compared to humid climates. The spatial variability in the effects of building density on LST was closely related to climate conditions, soil type, and vegetation. The results from stepwise regression analysis showed that precipitation (climate) controlled the spatial variability, indicating that there is a complex mechanism underlying these potential factors. Furthermore, the results from climatic zoning statistics revealed that the K-values of northern Chinese cities were positively correlated with the areas of local water bodies. However, the K-values of southern Chinese cities were significantly and positively correlated with the mean annual temperature and aridity and were negatively correlated with population density. Stepwise regression results further indicated that the mean annual temperature may be the most influential factor for southern cities. These results highlight the spatial variance and different determinants of K and suggest that climate-adapted urban design and planning standards are needed in different climate zones.