Journal of the Korean Association of Geographic Information Studies (한국지리정보학회지)

The Korean Association of Geographic Information Studies (한국지리정보학회)
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Analysis of living population characteristics to measure urban vitality - Focusing on mobile big data -

도시활력 측정을 위한 생활인구 특성 분석 - 이동통신 빅데이터를 중심으로 -

  • Yoko Kamata (Department of Urban Planning and Engineering, Kyungsung University) ;
  • Kwang Woo NAM (Department of Urban Planning and Engineering, Kyungsung University)
  • Received : 2023.11.20
  • Accepted : 2023.12.14
  • Published : 2023.12.31
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Abstract

In an era of population decline, depopulated regions facing challenges in attracting inbound population migration must enhance urban vitality through the attraction of living populations. This study focuses on Busan, a city experiencing population decline, comparing the spatiotemporal distribution characteristics of registered residents and living populations in various administrative districts (Eup-Myeon-Dong) using mobile communication big data. Administrative districts are typified based on population change patterns, and regional characteristics are analyzed using indicators related to urban decline and vitality. Spatiotemporal distribution analysis reveals generally similar density patterns between registered residents and living populations; however, a distinctive feature is observed in the city center areas where the density of registered residents is low, while the density of living populations is high. Divergent trends in spatial patterns of change between registered residents and living populations show clusters of registered population decline in low-density areas and clusters of living population decline in high-density areas. Areas adjacent to declining living populations exhibit large clusters of population changes, indicating a spillover effect from high-density to neighboring areas. Typification results reveal that, even in areas with a decline in registered residents, there is active population influx due to commuting or visiting. These areas sustain an increase in the number of businesses, confirming the presence of industrial and economic growth. However, approximately 47% of administrative districts in Busan are experiencing a decline in both registered residents and living populations, indicating ongoing regional decline. Urgent measures are needed for enhancing urban vitality. The study emphasizes the necessity of utilizing living population data as an urban planning indicator, considering the increasing limit distance of urban activities and growing interregional interaction due to advancements in transportation and communication.

본격적인 인구감소 시대에 들어선 가운데 지방 도시들은 사회적 인구 유입도 어려운 상황을 고려하여 생활인구 유도를 통한 도시 활력 증진을 모색할 필요가 있다. 본 연구는 이동통신 빅데이터를 활용한 도시활력도 분석을 위해 인구감소 지역인 부산광역시 행정동을 대상으로 주민등록인구와 생활인구의 시공간 분포특성을 비교하였다. 다음으로 행정동을 인구증감의 변화 양상으로 유형화한 후, 도시쇠퇴 및 활력 관련 지표를 사용하여 유형별 지역 특성을 분석하였다. 시공간 분포특성 분석결과, 주민등록인구와 생활인구 밀도 분포패턴은 대체로 비슷한 패턴을 보였으나, 원도심 지역에서 주민등록인구 밀도가 낮으면서 생활인구 밀도가 높은 반대의 특성을 가지는 지역이 나타났다. 주민등록인구와 생활인구의 변화 양상은 상당한 차이를 보였으며, 주민등록인구는 밀도가 낮은 지역에서 인구가 감소하는 반면, 생활인구는 밀도가 높은 지역에서 감소하는 경향을 보였다. 생활인구 감소 군집에 인접해서 인구증감의 지역 간 격자가 큰 군집이 나타나, 인구 밀도가 높은 지역에서 주변 지역에 생활인구가 확산하는 전이효과가 나타날 가능성을 시사했다. 유형화 결과, 주민등록인구가 감소하는 지역에서도 통근·통학 또는 방문으로 인한 활발한 인구 유입이 있었으며, 이러한 지역은 사업체 수의 증가를 유지하고 있어, 산업·경제적 성장이 존재함을 확인하였다. 다만 부산의 약 47% 행정동은 주민등록인구와 생활인구가 모두 감소하고 지역 쇠퇴가 진행되고 있었으며, 이러한 지역에 대해 우선적인 도시 활력 증진을 위한 노력이 필요하다. 본 연구는 교통과 통신의 발달로 인한 도시활동의 한계거리 증가와 이동량의 증가로 지역간 교류가 날로 확대되는 점을 고려해 주민등록인구뿐만 아니라 도시계획지표로서의 생활인구 데이터의 활용 필요성을 제시하였다.

Keywords

Acknowledgement

이 논문은 2021년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(No. 2021R1I1A3056691).

References

  1. An, S.H., Lee, S.J., Min, S.H., Kim, M.A., Jeon, B.G., Kang, M.S., Lee, T., Jo, Y.A. 2022. A study on the Direction of Regional Policy in the Era of Population Decline. Sejong: Korea Research Institute for Human Settlements.
  2. Bell, M., Ward, G. 2000. Comparing temporary mobility with permanent migration. Tourism Geographies, 2(1):87-107. https://doi.org/10.1080/146166800363466
  3. Busan BigData Innovation Center. 2018, 2019. KT Living Population Data. https://busanbigdata.kr/. (Accessed October 20, 2023).
  4. Busan Metropolitan City. 2023. Busan Urban Master Plan. https://www.busan.go.kr/. (Accessed November 6, 2023).
  5. Busan Open Data Potal. 2019. National Urban Rail Station Information Standard Data. http://data.busan.go.kr/. (Accessed October 20, 2023).
  6. Cabinet Secretariat. 2020. The secondterm Comprehensive Strategy for Urban, People, and Employment Revitalization (Revised in 2020), Tokyo, Japan.
  7. Cao, Y., Lee, S.G. 2021. Analysis of Urban Vitality and Its Determinant Factors Using POI Bigdata in Seoul, Korea. Journal of Korea Planning Association, 56(7):87-102. https://doi.org/10.17208/jkpa.2021.12.56.7.87
  8. Jacobs, J. 1961. The Death and Life of Great American Cities. Vintage Books, New York.
  9. Jung, J.H., Nam, J. 2019. Types and Characteristics Analysis of Human Dynamics in Seoul Using Location-Based Big Data. Journal of Korea Planning Association, 54(3):75-90. https://doi.org/10.17208/jkpa.2019.06.54.3.75
  10. Kamata, Y. and Kang, J.E., 2020. A Study on the Occurrence, Persistence, and Reuse of Vacant Houses in Deteriorated High-density Residential Areas of Old Downtowns of Large Cities : Focused on Ami-dong and Chojang-dong in Busan. Journal of the Korea Planning Association, 56(7):73-86. https://doi.org/10.17208/jkpa.2021.12.56.7.73
  11. Kim, K.J., Cho, M.H., Lee, C.J., Lee, Y.S. 2023. A Study on the Determinants of Hypermarket Sales using Membership Mileage Accumulation Data: Comparing Resident Registration Population with De Facto Population. Social Science Review, 54(1):93-111.
  12. Korea Railway Industry Information Center. 2019. Standard Data Station Information. https://data.kric.go.kr/. (Accessed October 20, 2023).
  13. Korean Statistical Information Service. 2018, 2019. Busan Metropolitan City Basic Statistics. https://kosis.kr. (Accessed September 25, 2023).
  14. Korean Statistical Information Service. 2019. National Business Survey. https://kosis.kr. (Accessed October 3, 2023).
  15. Lee, J.H., Kim, H.J. 2019. Identification of Spatial Distribution of an Aged Population and Analysis on Characterization of the Cluster: Focusing on Seoul Metropolitan Area. Journal of Digital Contents Society, 20(7):1365-1371. https://doi.org/10.9728/dcs.2019.20.7.1365
  16. Lee, S.H. 2021. Analysis of the Impact of Particulate Matter and Spatial Characteristics on Urban Vitality using Spatio-temporal Big Data: Focused on Seoul. Ph.D. Thesis, Pusan National University, Busan, Korea.
  17. Park, J.S., Kim, S.J., Lee, S.G. 2022. Analysis of Determining Factors of Urban Vitality with Mobile Phone Location-Based Origin-Destination Bigdata by Travel Purpose: Using the PageRank Algorithm and SHAP Machine Learning. Journal of Korea Planning Association, 57(5):72-89. https://doi.org/10.17208/jkpa.2022.10.57.5.72
  18. Son, K.M. 2021. The Effect of Spatial Distribution of De Facto Population on Commercial Sales Volume in Seoul. Master's Thesis, Chung-Ang University, Seoul, Korea.
  19. Urban Regeneration Information System, 2021. 도시재생전략계획 수립 가이드라인. https://www.city.go.kr/.
  20. V-World. 2018, 2019. Building Age Spatial Information. https://www.vworld.kr. (Accessed October 4, 2023).
  21. V-World. 2018, 2019. Land Characteristics Information. https://www.vworld.kr. (Accessed October 20, 2023).
  22. Yu, H.J. 2022. Analysis of the Relationship between the Living Population and Land-Use Characteristics: Focused on the Seoul Area. Journal of the Korean Urban Geographical Society, 25(3):67.