Urban Public Service Analysis by GIS-MCDA for Sustainable Redevelopment: A Case Study of a Megacity in Koreaopen access
- Authors
- Chae, Ji Seong; Choi, Chang Hyun; Oh, Jeong Hoon; Chae, Young Tae; Jeong, Jae-Weon; Lee, Dongkyu
- Issue Date
- Feb-2021
- Publisher
- MDPI
- Keywords
- sustainable redevelopment; urban shrinkage; urban regeneration; public service; transit-oriented development (TOD); geographic information system (GIS); entropy method
- Citation
- SUSTAINABILITY, v.13, no.3, pp.1 - 19
- Journal Title
- SUSTAINABILITY
- Volume
- 13
- Number
- 3
- Start Page
- 1
- End Page
- 19
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/84728
- DOI
- 10.3390/su13031472
- ISSN
- 2071-1050
- Abstract
- With the rapid industrialization and urbanization, suburban areas have been developed to accommodate the sudden demand of the population. However, recent problems such as low fertility and aging induces urban shrinkage by reducing the urban population and the economy in old areas around the suburbs. As urban shrinkage causes inequality among residents in terms of the opportunities to access public services, the enhancement of the accessibility of public services is crucial to achieve inclusive growth. This paper proposes a framework for supplying public services based on the transit-oriented development (TOD) concept with geographic information system (GIS) analysis technique. A total of 24 indices, 4 criteria for 6 public services, are measured and weighted by the entropy method to find vulnerable residential buildings with a poor environment in Jung-nang district, Seoul. With a spatial analysis based on this weight value of residential buildings and the TOD concept, old commercial buildings are selected as candidate buildings for public services. According to the derived results, one candidate building as a public service can improve the environment of 3% to 8% of vulnerable residential buildings. The proposed decision-making methods can provide a valuable reference for selecting the location of public services by computational analysis with GIS.
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