Multi-Scale High-Resolution Urban Flood Susceptibility Mapping Using MaxEnt and Multi-Source Geospatial Data

Urban flood susceptibility mapping is essential for disaster risk management in rapidly urbanizing regions. Although high-resolution Earth observation (EO) data provide detailed information for fine-scale flood analysis, existing studies are often limited by inadequate representation of drainage capacity, inappropriate spatial scales, and model uncertainty under sparse flood sample conditions. To address these issues, this study develops a multi-scale urban flood susceptibility mapping framework based on the Maximum Entropy (MaxEnt) model, integrating multi-source high-resolution geospatial data. A three-tier spatial unit system, including catchment, street, and grid scales, was constructed. Two models were developed at each scale using per capita drainage density (PCDD) and pipe density (PipeDen) as drainage capacity indicators. The results reveal significant scale-dependent differences in spatial autocorrelation, model performance, and variable responses. Compared with the PipeDen-based model, the standard deviation of AUC decreased by 37.5% and 25.0% at the catchment and street scales, respectively, and the model produced a more physically consistent relationship between drainage capacity and urban flood susceptibility. Considering the combined results of model performance, spatial autocorrelation, and response-curve analysis, the street scale PCDD-based model achieved the best overall performance among the six multi-scale models. Impervious area ratio, distance to roads, and annual maximum daily precipitation were identified as dominant factors influencing urban flood susceptibility. Based on the optimal street scale PCDD-based model, a 2 m resolution susceptibility map was generated, showing that high-susceptibility areas are mainly concentrated in highly urbanized central districts and along major transportation corridors. This study highlights the importance of spatial scale and drainage capacity representation in high-resolution urban flood susceptibility mapping.