Abstract The COVID-19 pandemic served as a catalyst for increased stress, revealing underlying systemic urban inequalities and transforming daily routines. To help achieve Sustainable Development Goal 11, we present a comprehensive, open-data dual-layer framework for assessing Urban Mobility Resilience (UMR) that integrates longitudinal mobility dynamics with multivariate neighbourhood contexts. Analysing New York City’s for-hire vehicle records from 2019 to 2023, we delineate distinct resilience trajectories: Stability, Recovery, and Adaptation. Our findings demonstrate a significant centre-periphery divide; affluent centres remained predominantly stable, whereas peripheral transitional neighbourhoods adapted through changes in temporal rhythms rather than returning to pre-pandemic norms. This reproducible framework offers evidence-based insights for policymakers to recognise socio-spatial inequalities and execute targeted interventions, moving beyond a simple “return to normal” to foster equitable urban resilience.
Liu et al. (Thu,) studied this question.