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Categorising neighbourhoods using OpenStreetMap POIs: Affinity propagation clustering of 7,213 subdistricts in Thailand

  • Manchester Metropolitan University

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)362-378
Number of pages17
JournalJournal of Urban Management
Volume14
Issue number2
DOIs
Publication statusPublished - Jun 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

Keywords

  • Affinity propagation
  • Neighbourhood development
  • OpenStreetMap
  • Place development
  • Thailand
  • Urban analytics

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