Journal of the Architectural Institute of Korea (대한건축학회논문집)

Architectural Institute of Korea (대한건축학회)
권호 표지
DOI QR코드

DOI QR Code

Defining Seoul's 15-minute Neighborhood Boundaries for Evaluating Administrative Community Area Boundaries - Using the Personal Travel Survey Data and Community Detection Algorithms -

서울시 15분 근린생활권의 실증과 지역생활권 경계 비교 - 개인통행실태조사 데이터와 커뮤니티 탐지 알고리즘의 활용 -

  • Kim, Jung Woo (Department of Architecture & Architectural Engineering, Seoul National University) ;
  • Kang, Bumjoon (Department of Architecture & Architectural Engineering, Seoul National University)
  • Received : 2024.04.15
  • Accepted : 2024.05.31
  • Published : 2024.06.30
⟨ Previous Next ⟩

Abstract

Seoul, South Korea, has a total of 116 officially determined Community Areas based on administrative boundaries and static demographic data. Residents' local activity spaces may not follow these administrative boundaries, which often creates difficulties in neighborhood planning and policy development. In this study, we define a 15-minute neighborhood as residents' collective boundaries delineated by their active transportation using the 2021 Personal Travel Survey data and community detection algorithms. Then, the detected 15-minute neighborhoods are clustered and compared against Seoul Metropolitan Government's official 2030 Community Areas. We evaluate boundary disagreement between the 15-minute neighborhoods and Community Areas using the Jaccard Index. We find that only 15 out of the neighborhood clusters have boundary agreement with the 2030 Community Areas, showing an 87% boundary disagreement rate. This study demonstrates that Seoul's official Community Areas do not align with residents' actual local travel patterns, suggesting that local neighborhood or community planning should consider residents' actual living areas.

Keywords

Acknowledgement

이 논문은 2023년 대한민국 교육부와 한국연구재단의 인문사회기초연구사업의 지원을 받아 수행된 연구임. 과제번호: NRF-2023S1A5A8079680

References

  1. Adam, A., Delvenne, J. C., & Thomas, I. (2018). Detecting communities with the multi-scale Louvain method: robustness test on the metropolitan area of Brussels. Journal of Geographical Systems, 20(4), 363-386. 
  2. Cho, Y., & Sung, H. (2021). Establishing the daily living areas based on travel patterns: focused on the ChungCheong area. Journal of Korea Planning Association, 56(3), 92-103. 
  3. De Montis, A., Caschili, S., & Chessa, A. (2013). Commuter networks and community detection: a method for planning sub regional areas. European Physical Journal Special Topics, 215(1), 75-91. 
  4. Ha, J. (2023). Analysis Of Functional Living Zones And Factors Influencing Travel Distance Using Mobile Phone Location-Based Od Big Data And Community Detection In Seoul, Korea, Thesis, Hanyang University, 1-70. 
  5. Ha, J., & Lee, S. (2016). A study on the designation of living zones by its spatial hierarchy using OD data and community detection technique - focused on the 2010 Household Travel Survey Data of the Seoul Metropolitan Area. Journal of Korea Planning Association, 51(6), 79-98. 
  6. Jang, M., Seong, E., Jung, I., & Byun, E. (2022). Policy proposal for introduction and utilization of neighborhood based on the daily life. Architecture & Urban Research Institute. 
  7. Jeong, Y. Y., & Moon, T. H. (2014). Analysis of Seoul urban spatial structure using pedestrian flow data - comparative study with 2030 Seoul Plan. Journal of The Korean Regional Development Association, 26(3), 139-158. 
  8. Jung, C. H., Lee, T. G., & Ahn, J. R. (2014). A study on the Regional Settlement Areas by intercity travel - the focus on Busan・Ulsan・Gyeongnam. residential environment. Journal of the Residential Environment Institute of Korea, 12(3), 363-373. 
  9. Kim, K., Lee, D., Kim, D. H., Won, M., Hong, S., & Song, T. J. (2021). A study on the classification and understanding of travel boundary by city population scale based on mobile travel data. Journal of Korean Society of Transportation, 39(5), 662-679. 
  10. Kim, S., Lim, H. J., & Heo, J. (2020). Analysis of Seoul Living Sphere using origin-destination data from a mobile phone network. Journal of Korean Society for Geospatial Information Science, 28(1), 3-10. 
  11. Korea Transport Database. (n.d.). National Transport Surveys. Retrieved May 12, 2024 from https://www.ktdb.go.kr 
  12. Kwon, Y. S. (2011). The transition in the spatial structure of neighborhood unit in Korean New Town Masterplan - focused on Changwon-si, Bundang Newtown, and Sejong-si in Korea. Journal of Korea Planning Association, 46(2), 193-210. 
  13. Maeng, D. M., Yang, J. S., & Sung, S. (2023). Realizing The "Daily Walking Area" That Reduces Travel Time And Enhances Quality Of Life By Utilizing Various Urban Planning And Systems And Preserving The Unique Characteristics Of Seoul. Seoul Institute. 
  14. Ministry of Land, Infrastructure and Transport Urban Policy Division. (2023). Urban planning innovation measures [Press release]. Retrieved from May 14, 2024 https://www.molit.go.kr/USR/NEWS/m_71/dtl.jsp?lcmspage=1&id=95087743 
  15. Moreno, C., Allam, Z., Chabaud, D., Gall, C., & Pratlong, F. (2021). Introducing the "15-minute city": sustainability, resilience, and place identity in future post-pandemic cities. Smart Cities, 4(1), 93-111. 
  16. National Institute of the Korean Language. (n.d.). Standard korean language dictionary. Retrieved May 12, 2024 from https://stdict.korean.go.kr/search/searchResult.do 
  17. National Law Information Center. (n.d.). Guideline for Formulating Urban or Gun Master Plan: Chapter 13, Living Area Plan, Section 4-13-1. Retrieved May 12, 2024 from https://www.law.go.kr 
  18. Newman, M., & Girvan, M. (2004). Finding and evaluating community structure in networks. Physical review E, Statistical, Nonlinear, and Soft Matter Physics, 69(2). 
  19. Oh, P. R. (2014). A study on travel characteristics and the establishment of criterion for the size of the neighborhood unit by using the data of Household Travel Diary Survey in Seoul. Seoul Studies, 15(3), 1-18. 
  20. Park, S., Koo, Y., Kim, K., Kim, M., Kim, J., Park, K., Park, B., Byun, J., Son, H., Yeo, W., Oh, D., Yoon, J., Lee, S., Jang, J., Heo, Y., & Hwang, Y. (2022). The concept plan of the 15-minute city in Busan. Busan Development Institute. 
  21. Poorthuis, A. (2018). How to draw a neighborhood? the potential of big data, regionalization, and community detection for understanding the heterogeneous nature of urban neighborhoods. Geographical Analysis, 50(2), 182-203. 
  22. Seoul Metropolitan Government. (2013). Guidelines for Establishing Living Area Plans(Draft). Seoul Metropolitan Government. 
  23. Seoul Metropolitan Government. (2014). 2030 Seoul Urban Basic Plan. Seoul Metropolitan Government. 
  24. Seoul Metropolitan Government. (2019). 2030 Seoul Living Area Plan. Seoul Metropolitan Government. 
  25. Seoul Metropolitan Government. (2023). 2040 Seoul Urban Basic Plan, Seoul Metropolitan Government. 
  26. Seoul Metropolitan Government. (n.d.). Easy urban planning terminology search. Retrieved May 12, 2024 from https://urban.seoul.go.kr/view/mainPop/term.pop 
  27. Seong, E., Kang, H., & Her, J. (2021). N-minute city: An empirical study and implementation strategies. Architecture & Urban Research Institute. 
  28. Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: guaranteeing well-connected communities. Scientific Reports, 9, 5233. 
  29. Wei, S., & Wang, L. (2021). Community detection, road importance assessment, and urban function pattern recognition: a big data approach. Journal of Spatial Science, 68(1), 23-43. 
  30. Yang, J. S., Han, J. H., & Ban, Y. K. (2022). Operational diagnosis and improvement direction of the Neighbourhood Plan in Seoul. The Seoul Institute. 
  31. Yu, Q., Li, W., Yang, D., & Zhang, H. (2020). Mobile phone data in urban commuting: a network community detection-based framework to unveil the spatial structure of commuting demand. Journal of Advanced Transportation, 2020, 1-10.