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Feature Mapping the Seoul Metro Station Areas Based on a Self-Organizing Map

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  • Keemin Sohn

Abstract

Land in the vicinity of railway stations in the Seoul metropolitan area has been spotlighted as a target for redevelopment in accordance with the principles of transit-oriented development (TOD). In order to understand the nature of station areas as a whole, it is required to identify their current status with respect to their built environments, demographic characteristics, socioeconomic status, and transport aspects. Most of the previous studies that have focused on characterizing urban areas assumed that clearly separable clustering is possible and tried to find a robust methodology for that. Many researchers have used either supervised classifiers requiring a pre-classified dataset for training, or K-means-like unsupervised classifiers demanding a predetermined number of clusters. The present study focused on the fact that it was hard to find such a clear separation in station areas in Seoul. A more abstract technology was necessary to position the current status of each station area and to find how different station areas are from one another. A robust unsupervised classifier, called the self-organizing map (SOM), was employed to investigate the similarities and differences among station areas in Seoul. The SOM results revealed many informative findings for policy development without any classification.

Suggested Citation

  • Keemin Sohn, 2013. "Feature Mapping the Seoul Metro Station Areas Based on a Self-Organizing Map," Journal of Urban Technology, Taylor & Francis Journals, vol. 20(4), pages 23-42, October.
    • Handle: RePEc:taf:cjutxx:v:20:y:2013:i:4:p:23-42
    DOI: 10.1080/10630732.2013.855514
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    References listed on IDEAS

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    1. Gregory J. Costello, 2001. "A Spatial Approach to Price Segmentation in Housing Markets," ERES eres2001_139, European Real Estate Society (ERES).
    2. Goodman, Allen C. & Thibodeau, Thomas G., 2003. "Housing market segmentation and hedonic prediction accuracy," Journal of Housing Economics, Elsevier, vol. 12(3), pages 181-201, September.
    3. Bourassa, Steven C. & Hoesli, Martin & Peng, Vincent S., 2003. "Do housing submarkets really matter?," Journal of Housing Economics, Elsevier, vol. 12(1), pages 12-28, March.
    4. Zhuo Chen & Seong-Hoon Cho & Neelam Poudyal & Roland K. Roberts, 2009. "Forecasting Housing Prices under Different Market Segmentation Assumptions," Urban Studies, Urban Studies Journal Limited, vol. 46(1), pages 167-187, January.
    5. Tom Kauko, 2004. "A Comparative Perspective on Urban Spatial Housing Market Structure: Some More Evidence of Local Sub-markets Based on a Neural Network Classification of Amsterdam," Urban Studies, Urban Studies Journal Limited, vol. 41(13), pages 2555-2579, December.
    6. Bourassa, Steven C. & Hamelink, Foort & Hoesli, Martin & MacGregor, Bryan D., 1999. "Defining Housing Submarkets," Journal of Housing Economics, Elsevier, vol. 8(2), pages 160-183, June.
    7. Tom Kauko, 2009. "Classification of Residential Areas in the Three Largest Dutch Cities Using Multidimensional Data," Urban Studies, Urban Studies Journal Limited, vol. 46(8), pages 1639-1663, July.
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    Cited by:

    1. Liu, Yunzhe & Singleton, Alex & Arribas-Bel, Daniel, 2020. "Considering context and dynamics: A classification of transit-orientated development for New York City," Journal of Transport Geography, Elsevier, vol. 85(C).
    2. Shereen Wael & Abeer Elshater & Samy Afifi, 2022. "Mapping User Experiences around Transit Stops Using Computer Vision Technology: Action Priorities from Cairo," Sustainability, MDPI, vol. 14(17), pages 1-20, September.

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