Spatial analysis of socio-economic and demographic factors influencing urban flood vulnerability

Rapid urbanization and climate change require a thorough understanding of flood vulnerability in order to assure urban safety and resilience. Understanding the factors that contribute to flood vulnerability, allows us to develop effective initiatives that could mitigate the destructive consequences of flooding, while also protecting communities. The objective of this research is to identify and model the socio-economic and demographic factors that significantly influence flood vulnerability in the floodplains of Jackson, Mississippi, and Birmingham, Alabama, USA. First we analyzed the correlation between socio-economic and demographic factors then employed Principal Component Analysis (PCA) to address multicollinearity, a common challenge in multivariate statistical modeling. Subsequently, PCs-based global regression (PCR) and geographically weighted regression (PCGWR) analysis are used to identify key drivers of flood vulnerability. The findings demonstrate that a significant proportion of the variance (>80%) of these factors can be captured by first two to three Principal Components (PCs). Consistent with existing research, African American, poverty, seniors, and the number of less educated people positively correlate with flood vulnerability, while income and housing prices exhibit a negative correlation. Additionally, PCGWR outperformed the Principal Component Regression (PCR) in most cases, highlighting the spatial heterogeneity of flood vulnerability. This study focuses on two U.S. cities, and the methodology is applicable to other cities with similar characteristics. The identified factors align with global research on flood vulnerability, making the proposed research and findings valuable worldwide. The findings of this research are useful for local governments, policymakers, and urban developers to make detailed location specific flood vulnerability plan to reduce impact of flood and improve urban resilience.