Developing mobility zones based on heat exposure and vegetation condition: a tale of two transportation modes

Understanding how environmental conditions influence urban mobility patterns is crucial for developing climate-resilient transportation systems. This study introduces a new mobility zoning framework to examine how environmental conditions and mobility patterns in New York City interrelate and compare different transportation modes (taxi and bike-share) in 2018 and 2023. Through comprehensive spatial analysis combining Land Surface Temperature and Normalized Difference Vegetation Index, we identify distinct environmental zones and their evolution, which reveals concerning expansion of high heat-low vegetation (HL) zones. Moreover, this study demonstrates contrasting mobility adaptations between transportation modes: bike-share riders show increased environmental responsiveness with dominant Cooling-Priority Movement, while taxi passengers maintain stable Status Quo Movement. Our explainable machine learning analysis reveals shifting influences from infrastructure-dominated factors to stronger socioeconomic considerations for bike-share usage, while taxi passengers become more closely aligned with urban form and infrastructure. These findings provide crucial insights into urban resilient planning and suggest the need for mode-specific transportation strategies and targeted interventions in heat vulnerable areas.