Urban dynamic in high spatiotemporal resolution: The case study of Porto

Abstract

Cities that prioritize sustainability leverage data from daily urban activities to make informed decisions. Research has shown the effectiveness of indicators regarding traffic, public transport, shared mobility, and air quality data to manage and monitor urban systems. However, there has been limited effort to develop composite indicators that represent multiple phenomena in a single metric. We propose a high-resolution spatiotemporal indicator to measure urban dynamic (UDI). We collected hourly data on traffic, public transport usage, e-scooter trips, and air quality in Porto, Portugal. Factor analysis was applied to extract the composite indicator and provide a holistic view of the city's dynamic. Results revealed higher dynamic in the northwest and southwest areas in the Aldoar, as well as in some areas in Cedofeita and Bonfim parishes. The UDI showed higher values on business days than on weekends, the afternoon period displayed the highest dynamic, while traffic flow was the variable with the highest impact. Using mobile phone location data, we evaluated the UDI's values, demonstrating its ability to support data-driven decision-making and inform interventions by city planners.