What Kind of Urban Spatial Form Is More Conducive to Disaster Risk Reduction: An Empirical Analysis from 32 Cities in China

As urban disasters intensify, the relationship between urban spatial form and disaster risk is increasingly important. Different spatial configurations reflect varying levels of resilience to disasters. However existing research offers limited quantitative evidence linking spatial form indicators and disaster risk indices. This study addresses this gap by developing a quantifiable, city-scale framework to analyze the form–risk relationship across 32 Chinese cities. Urban spatial form is quantified using fractal dimension to measure boundary complexity and compactness to assess internal structure, supplemented by a diagrammatic classification of urban patterns. A comprehensive disaster risk index is developed based on four dimensions: hazards, exposure, vulnerability, and resilience. Regression analysis is then applied to quantify the direction and magnitude of correlations between spatial-form indicators and the comprehensive risk index. The results reveal three major findings: (1) Disaster risk increases with fractal dimension, indicating that cities with more complex and irregular boundaries tend to be more vulnerable. In contrast, compactness has no statistically significant effect on disaster risk. (2) Spatial patterns are strongly associated with risk levels: cluster-type and block-type cities generally experience lower risks than radial-type and constellation-type cities. (3) City size and geography also influence risk, as larger cities typically exhibit lower risks, whereas southern cities face higher risks than those in northern regions. These results highlight the critical role of urban spatial structure in shaping disaster resilience. Managing boundary complexity, fostering polycentric and block-based spatial layouts, and improving road-network redundancy can effectively enhance urban adaptive capacity. These insights provide theoretical foundations and practical guidance for resilience-oriented spatial optimization and disaster-risk reduction in vulnerable cities.