Assessing Community Resilience to Hurricanes in the Guangdong–Hong Kong–Macao Greater Bay Area, China from 2013 to 2023

: Hurricanes, one of the most devastating natural phenomena in coastal regions, pose significant risks to infrastructure, environment, and human lives. Understanding and monitoring the resilience capacity to the hurricane hazard are crucial for building an adaptable and sustainable society. This study employed the Resilience Inference Measurement (RIM) model to assess the community resilience level at the township level in the southern China mega-city region, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Using empirical data on hurricane threat, damage, and recovery from 656 townships in the region, K-means clustering and stepwise discriminant analysis were conducted to classify resilience levels and validate the framework. The continuous resilience scores derived from these classifications were further analyzed through ordinary least squares (OLS) regression to identify key socio-environmental predictors influencing the resilience level. The results reveal four resilience types—susceptible, recovering, resistant, and usurper—with a cross-validation accuracy of 68.1%. High resilience areas were concentrated in coastal and well-developed cities, while low resilience communities were primarily in the inland areas or rapidly expanding edge cities. Regression analysis identified nine critical factors affecting the resilience levels, including four social, four infrastructural, and one economic factor. Notably, the proportion of elderly residents showed a positive correlation with resilience, particularly in Hong Kong, where strong community networks, low out-migration, and supportive urban policies may have contributed to faster recovery and stability. These findings provide valuable insights for policymakers and urban planners to develop targeted adaptation strategies to enhance community resilience and promote long-term sustainability in coastal regions.