Categorising neighbourhoods using OpenStreetMap POIs: Affinity propagation clustering of 7,213 subdistricts in Thailand
The effective categorisation of neighbourhoods is a critical component of urban planning and development, providing a systematic framework for identifying and addressing the distinct characteristics and needs of different areas. This study utilises data from the open-source platform OpenStreetMap (OSM) to propose a novel approach to neighbourhood categorisation, with a focus on amenities as key elements. Data were collected on 4,121,900 points of interest (POIs) across 7213 subdistricts in Thailand, and the categorisation was conducted using the Affinity Propagation (AP) clustering technique. Through this approach, ten distinct neighbourhood clusters in Thailand were identified, demonstrating the efficacy of integrating OSM data with AP clustering. The findings underscore the necessity for more evidence-based planning policies aimed at enhancing amenities, vibrancy, and overall quality of life in neighbourhoods by promoting innovation and the development of creative districts. Furthermore, the study advocates for the consideration of ecological urbanism as an alternative pathway for neighbourhood development, a concept that has yet to be thoroughly explored in Thailand. • Utilises OpenStreetMap data to categorise neighbourhoods based on amenities. • Presents first nationwide amenity-based categorisation of neighbourhoods. • Clusters 7213 neighbourhood-level subdistricts using Affinity Propagation. • Identifies ten distinct amenity-based neighbourhood clusters across Thailand. • Highlights the absence of ecological urbanism in Thai neighbourhood development pathways.
Authors
- Viriya Taecharungroj (ORCID: https://orcid.org/0000-0002-0527-7629)
- Nikos Ntounis (ORCID: https://orcid.org/0000-0003-2517-3031)
Institutions
- Manchester Metropolitan University (GB)
- Mahidol University (TH)
Publication Details
- Journal
- Journal of Urban Management
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1016/j.jum.2024.11.005
- Citations
- 2
- Primary Topic
- Human Mobility and Location-Based Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.37