Research on Spatial Differentiation and Driving Mechanisms of Urban Typhoon Resilience: A Case Study of Zhuhai City, China

As global climate change intensifies, typhoon disasters pose growing threats to the socio-economic stability of coastal cities. Quantifying urban typhoon resilience and identifying its spatial driving mechanisms are essential for informing targeted disaster risk management and built environment optimization. This study develops an NTL-based framework to quantify urban typhoon resilience across three major typhoon events in Zhuhai from 2017 to 2020, using NTL loss rate and NTL recovery time as the primary resilience indicators and NTL loss as a descriptive measure of absolute disaster impact magnitude. OLS and GWR models are then applied to a 20-factor indicator system to identify the global drivers of resistance and recovery capacity and uncover the spatial heterogeneity of their effects across urbanization gradients, with the aim of providing both a replicable methodological framework and an empirical basis to inform differentiated resilience optimization strategies for coastal cities. The results demonstrate that urban typhoon resilience varies systematically across urbanization gradients in both dimensions. Highly urbanized areas consistently show stronger resistance, with NTL loss rates of 32–46% versus 36–50% in low-urbanized areas, as well as faster recovery, with NTL recovery times of 2.6–3.8 days versus 2.9–5.6 days. Transportation infrastructure emerges as the most consistent global driver. GWR reveals that its effects are most pronounced in less urbanized areas, where the absolute coefficient for transport station density reaches 4.804 (over 4% higher than in other zones). Blue–green infrastructure also plays a significant role, with higher NDVI values being associated with shorter recovery times. These findings provide a replicable NTL-based methodological framework and spatially explicit empirical evidence to support targeted and differentiated resilience optimization in coastal cities.