Assessing the influence of green space morphological spatial pattern on urban waterlogging: A case study of a highly-urbanized city.

The extensive expansion of impervious surfaces encroaches on green spaces and causes frequent urban waterlogging disasters. Previous studies have focused mainly on the influence of green space landscape pattern on waterlogging, with less attention given to green space morphological spatial pattern (MSPA). MSPA can be used to differentiate various types of land use morphologies from a microscopic perspective and reveal visualized spatial characteristics. Therefore, this study selected Shenzhen, a city with serious waterlogging problems, as the study area. The anthropogenic/natural environments and green space morphological spatial pattern were considered. Pearson correlation analysis and random forest regression were combined to investigate the influence of these drivers on the density of waterlogging hotspots and quantify the degree of importance for each driver. The results were supplemented with explanations using SHapley Additive exPlanations and Partial Dependence Plots. Pearson correlation analysis revealed that green space morphological spatial pattern, the proportion of green spaces, and the proportion of impervious surfaces were the dominant drivers. Additionally, the random forest regression showed that incorporating green space morphological spatial pattern and average tree height as potential drivers could strengthen the model's goodness-of-fit. While the proportion of impervious surfaces, the proportion of green spaces, and population density were important drivers, the green space morphological spatial pattern, specifically the "loop", "edge", and "core", was even more crucial and had an optimal design range. Therefore, green space morphological spatial pattern should be emphasized during the planning of "sponge cities" to maximize the ability of green spaces to mitigate waterlogging. In summary, our findings are expected to provide feasible suggestions for waterlogging control and green space planning.