What amenities drive footfall in UK town centres? A machine learning approach using OpenStreetMap data
Issued Date
2024-01-01
Resource Type
ISSN
23998083
eISSN
23998091
Scopus ID
2-s2.0-85206940475
Journal Title
Environment and Planning B: Urban Analytics and City Science
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SCOPUS
Bibliographic Citation
Environment and Planning B: Urban Analytics and City Science (2024)
Suggested Citation
Taecharungroj V., Ntounis N. What amenities drive footfall in UK town centres? A machine learning approach using OpenStreetMap data. Environment and Planning B: Urban Analytics and City Science (2024). doi:10.1177/23998083241290343 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/101784
Title
What amenities drive footfall in UK town centres? A machine learning approach using OpenStreetMap data
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Author's Affiliation
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Abstract
In the United Kingdom, town centres face significant economic and social challenges, with amenities playing a crucial role in their vitality. However, no existing study has thoroughly investigated the relationship between amenities and footfall, a key measure of place vitality. This research addresses this gap by examining which amenities drive footfall in UK town centres. The study employs the random forest modelling, to analyse data from OpenStreetMap (OSM) and footfall data from 960 counters across the United Kingdom. Our findings reveal that OSM data can effectively predict footfall, highlighting the importance of diverse amenities. Key amenities identified include hotels, pedestrian ways, and retail establishments. Furthermore, the study identifies critical inflection points where the presence of certain amenities significantly boosts urban vitality. These insights offer valuable guidance for urban planning and development, suggesting that a mix of diverse amenities at appropriate levels can enhance the attractiveness and vitality of town centres.