Abstrakti
Urban vitality (UV) is a commonly used concept that describes the liveliness, diversity, and attractiveness of urban spaces, which foster social interaction and activity. While the concept has received ample attention from researchers, combining big data and traditional data sources to capture UV remains underexplored. To address this gap, we build on contemporary interpretations of Jane Jacobs’s concept of vitality to develop a methodology that identifies dynamically vibrant areas. We propose a conceptual framework comprising three components: the built environment, the static residential population, and the dynamic population presence. The dynamic population presence, derived from georeferenced social media activity, serves as the main proxy for UV, reflecting the dynamic use and interaction within urban space. The built environment and static residential population dimensions are incorporated to contextualize and interpret the spatial patterns of dynamic presence. Vitality is further evaluated through four dynamic attributes: intensity, variability, consistency, and linguistic diversity that describe temporal rhythms and social heterogeneity. Applying this framework to Tallinn, Estonia, we explore the city’s spatio-temporal patterns and spatial clustering to identify its spatial hierarchy of vibrancy and relation to land-use functionality, mixed-use areas, and demographic diversity. The findings demonstrate how combining dynamic data with traditional indicators advances the understanding of UV and supports more inclusive, accessible, and socially cohesive urban planning.
| Alkuperäiskieli | Englanti |
|---|---|
| Sivumäärä | 16 |
| Julkaisu | Environment and Planning B: Urban Analytics and City Science |
| DOI - pysyväislinkit | |
| Tila | Sähköinen julkaisu (e-pub) ennen painettua julkistusta - 25 tammik. 2026 |
| OKM-julkaisutyyppi | A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä |
Rahoitus
The authors would like to thank the Digital Geography Lab, University of Helsinki, for preparing and processing the raw Twitter data for the study, and the Research Council of Finland (Flagship of Advanced Mathematics for Sensing Imaging and Modelling, FAME, grant number 359182) for supporting this article. The Future City Professorship project partners (including Mainor OÜ, Mainor Ülemiste, Telia Eesti, Ericsson Eesti, TalTech, and the City of Tallinn) funded the project. This work was also funded by the Academy of Finland (BORDERSPACE: Mobilities and Interactions of People Crossing State Borders: Big Data to Reveal Transnational People and Spaces, grant number 331549).
YK:n kestävän kehityksen tavoitteet
Tämä tuotos edistää seuraavia kestävän kehityksen tavoitteita:
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SDG 11 – Kestävät kaupungit ja yhteisöt
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