Understanding the relationship between different essential urban land use categories and the urban thermal environment is essential for urban planning, resource allocation and decision support. However, most of the spatiotemporal correlations between land use types and LST are focused on industrial land use and urban green space, and there are fewer discussions on the totality of urban land use types. Here, using multi-source remote sensing images, correlation analysis and the stepwise regression method, we elaborate the relationship between landscape structure and land surface temperature (LST) across the different seasons of 850 planning management units in Jiaozuo, China. Our results show that the degree of explanation of surface temperature by landscape structure increased with a fine division of land use. The imprint of urban–rural gradients on LST was largely masked by the land use categories at the regional scales. Moreover, the tridimensional structure of buildings significantly affected the LST of residential regions, and the large number of low-rise buildings in urban planning practice contributes to high LSTs. This study provides a comprehensive analysis of the effects of each land use type and landscape structure on surface temperature in urban space and also provides strategies and methods for urban planning in rapidly developing regions of the country.

Green infrastructure is imperative for efficiently mitigating flood disasters in urban areas. However, inadequate green space planning under rapid urbanization is a critical issue faced by most Chinese cities. Aimed at theoretically understanding the rainwater storage capacity and improvement potential of urban green spaces, a synthetic simulation model was developed to quantify rainfall surface flow accumulation (FA) based on the morphological factors of a flow basin: the area, circumference, maximum basin length, and stream length sum. This model consisted of applying the Urban Forest Effects-Hydrology model (UFORE-Hydro) to simulate the actual precipitation-to-surface runoff ratio through a procedure involving canopy interception, soil infiltration, and evaporation; additionally, a relatively accurate multiple flow direction-maximum downslope (MFD-md) algorithm was applied to distribute the surface flow in a highly realistic manner, and a self-built “extraction algorithm” extracted the surface runoff corresponding to each studied basin alongside four fundamental morphological parameters. The various nonlinear regression functions were assessed from both univariable and multivariable perspectives. We determined that the Gompertz function was optimal for predicting the theoretical quantification of surface FA according to the morphological features of any given basin. This article provides parametric vertical design guidance for improving the rainwater storage capacities of urban green spaces.