Applied Geography, cilt.170, 2024 (SSCI)
Urban mobility research is crucial due to the complex and dynamic nature of cities. Traditional zoning methods often overlook the temporal dynamics of urban space usage. This paper aims to investigate the daily rhythm of urban space usage and how built environmental features affect spatiotemporal mobility. The methodology integrates various urban data sources, including street and building vectors and points of interest (POI). In Ankara, Türkiye, temporal usage types were identified using principle component analysis and k-means algorithms via Google Maps location-based service data. Multinomial logistic regression model was used to examine the impact of built-environment factors on daily mobility patterns. Results reveal distinct daily usage rhythms, categorizing busy areas into morning, noon, early evening, late evening, diurnal, and nocturnal zones. The study finds: (1) temporal usage is closely associated with spatial characteristics and resident income; (2) work-related activities drive morning mobility, while nighttime mobility relates to residence, income, and accessibility; and (3) population density alone does not guarantee continuous activities; diverse POIs alongside high density are crucial. The identified relationship between mobility measures and urban built environment indicators provides a comprehensive understanding of spatiotemporal variations, offering insights for critical policy evaluations and proposals for the future of urban areas.