Speaker
Description
Recent studies have explored the "15-minute city" concept, which aims to provide essential urban services within a short distance of residents. Researchers have developed various methodologies to evaluate accessibility, including network-based frameworks considering human mobility patterns (Zhang et al., 2022) and GIS-based approaches to measure proximity at the neighborhood level (Chiaradia et al., 2024). These studies have revealed disparities in accessibility between urban and suburban areas, as well as within a city (Akrami et al., 2024). The methodology of this study integrates open data, GIS-based tools and spatial analysis techniques to create accessibility indicators with the objective of evaluate access levels to urban services in five cities (Vienna, Lisbon, Munster, Groningen and Ankara), with the aim of operationalizing the "15-minute city" concept an assess accessibility to urban services. It focuses on measuring walking, cycling, and public transport proximity to four categories of amenities: healthcare, education, recreation and sport facilities, and retail and other services. Data collection and processing were structured around three main components: urban amenities, population data, and transport networks. Primary data sources include open platforms such as OpenStreetMap (OSM) and Google Maps, mapping approximately 27,000 points of interest. Population data from national statistical agencies were used to estimate populations served by amenities at fine spatial units, such as census blocks. Transport and road networks were derived from OSM, focusing on walkable streets, bike lanes, and public transport stops sourced from GTFS specifications. Moreover, the analytical model employs accessibility measures. Distance-based indicators calculate the percentage of the population with access to at least one amenity within 15 minutes. Diversity and density metrics are also included, assessing the variety of services available within specific areas. The analytical framework comprises several steps: defining origin units (residences), selecting target amenities, and applying average travel speeds (e.g., 4-5 km/h for walking and 13 km/h for cycling). Road networks simulate real-world conditions using network distances, ensuring higher accuracy. Amenities were categorized into four main types, enabling direct comparisons across cities. The methodological findings demonstrate that using open data is effective in producing replicable accessibility measures. Integrating detailed population data with urban networks provides granular insights for policymaking. The methodology also allows to identify significant inequalities in cities with low density and peri-urban development. The proposed approach can be applied in future studies to compare accessibility in urban areas and foster solutions for active and inclusive mobility.
References
Akrami, M., Sliwa, M. W., & Rynning, M. K. (2025) 'Walk further and access more! Exploring the 15-minute city concept in Oslo, Norway', Journal of Urban Mobility, 6, p.100077. DOI: 10.1016/j.urbmob.2024.100077.
Chiaradia, F., Lelo, K., Monni, S., & Tomassi, F. (2024) 'The 15-Minute City: An Attempt to Measure Proximity to Urban Services in Rome'. Sustainability, 16(21), p.9432. DOI: 10.3390/su16219432.
Zhang, S., Zhen, F., Kong, Y., Lobsang, T., & Zou, S. (2023) 'Towards a 15-minute city: A network-based evaluation framework', Environment and Planning B: Urban Analytics and City Science, 50(2), pp.500-514. DOI: 10.1177/23998083221118570.
| Keywords | Accessibility analysis; urban amenities; spatial analysis; 15-minute city |
|---|---|
| Best Congress Paper Award | No |
