Resilient Urban Expansion : Identifying Critical Conflict Patches by Integrating Flood Risk and Land Use Predictions - a Case Study of Min Delta Urban Agglomerations in China

The increasing occurrence of floods due to global climate change poses challenges to the growth of urban resilience. However, research on how to avoid flood risks in the process of long-term and detailed land use development is limited. To address this issue, this paper proposes a method that integrates flood risk and land use predictions to identify critical conflict patches that impact urban resilience. Then, differentiated development strategies based on the attributes of these critical conflict patches were formulated. Taking the Min Delta Urban Agglomeration (MDUA) in China as a case study, we utilized a multi-source data set, a random forest (RF) algorithm, and a patch-generating land use simulation model (PLUS) coupled with cellular automata (CA) to identify critical conflict patches for urban expansion resilience. The results demonstrated that most conflicting patches were located in bare land within built-up areas, urban-rural intersection zones, and remote suburban areas with high traffic accessibility. The identified conflicting patches applied to three different land use patterns: intra-city renewal, urban edge expansion, and the creation of derived cities. Throughout the various stages of growth, each type of conflicting patch demonstrated a fairly constant quantitative structure and spatial distribution characteristics. In all development scenarios, the optimized land use pattern provided resilient growth space for urban development while maintaining the stability of the flood disaster environment. Based on our methodology and case study, we proposed a decision-making framework that can help cities or potential urban regions to avoid water-related problems and derivative issues