Examining resilience of taxi ridership during rainstorms and its non-linear associations with built environment

In the era of climate change, increasingly intense and frequent extreme weather events pose grave threats to urban life. Being a critical part of urban transportation system, taxis can facilitate understanding of human mobility and its variations during extreme weather events. Nevertheless, limited studies have delved into how taxi ridership responds to and recovers from the shocks induced by such events. Using Xiamen, China, as the case and employing random forest method, this study delves into resilience of taxi ridership and its non-linear relationships with built environment factors in the face of a rainstorm. Results show that (1) distance to city center, building density, and property price (as a proxy for socioeconomic features) are the most important contributors; (2) all the independent variables have salient non-linear effects on taxi ridership resilience, and obvious threshold effects exist; and (3) synergistic effects exist between certain independent variables, such as population density and land use mix. These findings can provide a solid knowledge base for formulating and executing nuanced intervention strategies for resilience promotion.