Identifying and understanding road-constrained areas of interest (AOIs) through spatiotemporal taxi GPS data: A case study in New York City

Urban areas of interest (AOIs) represent within the urban environment featuring high levels public interaction, with their understanding holding utility for a wide range planning applications. Within this context, our study proposes novel space-time analytical framework and implements it to taxi GPS data extent Manhattan, NYC identify describe 31 road-constrained AOIs in terms spatiotemporal distribution contextual characteristics. Our analysis captures many important locations, including but not limited primary transit hubs, famous cultural venues, open spaces, some other tourist attractions, prominent landmarks, commercial centres. Moreover, we respectively analyse these dynamics contexts by performing further clustering analysis, formulating five temporal clusters delineating dynamic evolution four representing salient