All Issue

2020 Vol.20, Issue 3 Preview Page

Research Article

The Impacts of Urban Sprawl on the Commuting Patterns of the Metropolitan Regions in Korea

도시 스프롤이 통근 패턴에 미치는 영향: 우리나라 광역도시권을 사례로

류나영1, 홍인수2

Nayoung Ryu1, Insu Hong2

1서울대학교 교육종합연구원 객원연구원
2CJ대한통운 TES 물류기술연구소 시니어 컨설턴트
1Visiting Research Fellow, The Center for Educational Research, Seoul National University
2Senior Consultant, TES Logistics Research Center, CJ Logistics
31 December 2020. pp. 73~92
PDF Citation
Abstract
The purpose of this paper is to analyze the impacts of urban sprawl on the commuting patterns of the Metropolitan Regions in Korea. Sprawl related indexes and socio-economic metrics as explanatory variables and commuting patterns using a privately-owned car (Model 1) and public transportation (Model 2) as dependent variables construct two OLS models. Spatial regression models and GWR models reflecting spatial dependence and/or spatial heterogeneity are also executed to investigate the relationship between urban sprawl and commuting patterns. The results are as follows. First, the goodness-of-fit of both models improve from OLS to spatial regression and GWR. Second, density among sprawl indexes is strongly significant related with commuting patterns. Street accessibility in Model 1 and land use mix in Model 2 are slightly related with commuting patterns in specific regions. Third, GWR models show significant socio-economic variables in certain regions which are not detected in OLS or spatial regression models.
Keywords
Urban sprawl
Metropolitan regions
Sprawl index
Commuting patterns
Geographically Weighted Regression (GWR)
본 연구의 목적은 우리나라의 광역도시권을 대상으로 도시 스프롤이 통근 패턴에 미치는 영향을 분석하는 것이다. 다차원적 측정 방법으로 광역도시권의 시군구 스케일에서 산출된 스프롤 관련 지수들과 사회경제적 특성을 나타내는 지표들을 설명변수로 하고, 자가용 통근(모형 1) 및 대중교통이용 통근(모형 2)을 종속변수로 하여 두 개의 OLS 회귀모형을 구성하였다. 아울러 공간적 의존성과 이질성을 반영한 공간회귀모형과 지리가중회귀모형을 함께 적용함으로써 스프롤과 통근 패턴의 관련성을 고찰하였다. 두 모형 모두 OLS 분석에서 공간회귀분석 및 GWR 분석으로 진행할수록 모형의 설명력과 적합도가 전반적으로 향상되었으며, 설명변수 중 밀도지수의 영향력이 가장 큰 것으로 나타났다. 모형 1에서는 가로접근성지수가, 모형 2에서는 복합지수가 일부 지역에 대하여 유의하였으나 밀도에 비해 영향력이 크지 않았다. 또한 국지적 모형인 GWR을 통해 전역적 모형에서는 탐지하지 못하였으나 국지적으로는 유의하게 나타나는 사회경제적 변수들을 확인할 수 있었다.
키워드
도시 스프롤
광역도시권
스프롤지수
통근 패턴
지리가중회귀분석(GWR)
References
  1. 권창기･정현욱, 2007, "대도시 광역도시권 설정과 권역별 공간 특성 비교," 국토연구, 52, 39-58. 10.15793/kspr.2007.52..003
  2. 김오석, 2015, "지리가중회귀모델을 이용한 천연 라텍스 산출량 요인분석: 중국 운남성 시솽반나를 중심으로," 한국지도학회지, 15(2), 67-77. 10.16879/jkca.2015.15.2.067
  3. 류나영, 2020, "우리나라 광역도시권의 스프롤 연구: 스프롤의 측정과 스프롤이 통근에 미치는 영향을 중심으로," 서울대학교 박사학위논문.
  4. 류나영･신정엽, 2020, "광역도시권의 스프롤 변화 양상: 광역도시권의 설정과 밀도 기반의 인구 및 고용 스프롤 측정을 중심으로," 한국지리학회지, 9(2), 395-409. 10.25202/JAKG.9.2.11
  5. 신정엽･김감영･김영호 역, 2019, 「도시 공간을 보다: 35가지 시선으로 바라본 도시」, 제2판, 서울: 시그마프레스(Gottdiener, M., Budd, L., and Lehtovuori, P., 2016, Key Concepts in Urban Studies, 2nd ed., Thousand Oaks, CA: SAGE).
  6. 엄현태･우명제, 2015, "도시스프롤 현상이 중심도시 쇠퇴에 미치는 영향과 도시재생에 대한 함의," 국토계획, 50(3), 73-89.
  7. 이건학･김감영, 2016, "공간통계 기법을 이용한 현주인구 추정 모델링," 한국지도학회지, 16(2), 71-93. 10.16879/jkca.2016.16.2.071
  8. 임수진･김감영, 2017, "밀도-공간구조 기반 도시 스프롤 측정치 개발," 한국지도학회지, 17(1), 87-101. 10.16879/jkca.2017.17.1.087
  9. 진장익･진은애･이우종, 2013, "도시스프롤이 통근통행에 미치는 영향에 관한 연구: 수도권 도시를 대상으로," 국토계획, 48(5), 269-283.
  10. Aurand, A., 2013, Does sprawl induce affordable housing?, Growth and Change, 44(4), 631-649. 10.1111/grow.12024
  11. Bereitschaft, B. and Debbage, K., 2013, Urban form, air pollution, and CO2 emissions in large U.S. metropolitan areas, The Professional Geographer, 65(4), 612-635. 10.1080/00330124.2013.799991
  12. Brueckner, J., 2000, Urban sprawl: Diagnosis and remedies, International Regional Science Review, 23(2), 160-171. 10.1177/016001700761012710
  13. Camagni, R., Gibelli, M.C., and Rigamonti, P., 2002, Urban mobility and urban form: The social and environmental costs of different patterns of urban expansion, Ecological Economics, 40(2), 199-216. 10.1016/S0921-8009(01)00254-3
  14. Cutsinger, J., Galster, G., Wolman, H., Hanson, R., and Towns, D., 2005, Verifying the multi-dimensional nature of metropolitan land use: Advancing the understanding and measurement of sprawl, Journal of Urban Affairs, 27(3), 235-259. 10.1111/j.0735-2166.2005.00235.x
  15. Ewing, R., 1997, Is Los Angeles-style sprawl desirable?, Journal of the American Planning Association, 63(1), 107-126. 10.1080/01944369708975728
  16. Ewing, R., 2008, Characteristics, causes, and effects of sprawl: A literature review, in Marzluff, J.M., Shulenberger, E., Endlicher, W., Alberti, M., Bradley, G., Ryan, C., Simon, U., and ZumBrunnen, C. eds., Urban Ecology, New York, NY: Springer, 519-535.
  17. Ewing, R. and Hamidi, S., 2014, Measuring Sprawl 2014, Washington, DC: Smart Growth America.
  18. Ewing, R., Hamidi, S., Grace, J.B., and Wei, Y.D., 2016, Does urban sprawl hold down upward mobility?, Landscape and Urban Planning, 148, 80-88. 10.1016/j.landurbplan.2015.11.012
  19. Ewing, R., Meakins, G., Hamidi, S., and Nelson, A.C., 2014, Relationship between urban sprawl and physical activity, obesity, and morbidity: Update and refinement, Health & Place, 26, 118-126. 10.1016/j.healthplace.2013.12.008 24434082
  20. Ewing, R., Pendall, R., and Chen, D., 2002, Measuring Sprawl and Its Impact, Washington, DC: Smart Growth America.
  21. Ewing, R., Pendall, R., and Chen, D., 2003, Measuring sprawl and its transportation impacts, Transportation Research Record: Journal of the Transportation Research Board, 1831, 175-183. 10.3141/1831-20
  22. Ewing, R. and Rong, F., 2008, The impact of urban form on US residential energy use, Housing Policy Debate, 19(1), 1-30. 10.1080/10511482.2008.9521624
  23. Fallah, B.N., Partridge, M.D., and Olfert, M.R., 2011, Urban sprawl and productivity: Evidence from US metropolitan areas, Papers in Regional Science, 90(3), 451-472. 10.1111/j.1435-5957.2010.00330.x
  24. Fallah, B.N., Partridge, M.D., and Olfert, M.R., 2012, Uncertain economic growth and sprawl: Evidence from a stochastic growth approach, Annals of Regional Science, 49(3), 589-617. 10.1007/s00168-011-0466-0
  25. Fotheringham, A.S., Kelly, M., and Charlton, M., 2010, Model Selection in Geographically Weighted Regression, Joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science, May 26-28, Hong Kong.
  26. Frost, M. and Spence, N., 2008, Energy consumption and work-travel trips: London, Birmingham, and Manchester, 1981-2001, Environment and Planning A, 40(9), 2238-2258. 10.1068/a39294
  27. Galster, G., Hanson, R., Ratcliffe, M.R., Wolman, H., Coleman, S., and Freihage, J., 2001, Wrestling sprawl to the ground: Defining and measuring an elusive concept, Housing Policy Debate, 12(4), 681-717. 10.1080/10511482.2001.9521426
  28. Gillham, O., 2002, The Limitless City: A Primer on the Urban Sprawl Debate, Washington, DC: Island Press.
  29. Gordon, P. and Richardson, H.W., 2000, Defending suburban sprawl, Public Interest, 139, 65-71.
  30. Hamidi, S. and Ewing, R., 2014, A longitudinal study of changes in urban sprawl between 2000 and 2010 in the United States, Landscape and Urban Planning, 128, 72-82. 10.1016/j.landurbplan.2014.04.021
  31. Kahn, M.E., 2001, Does sprawl reduce the black/white housing consumption gap?, Housing Policy Debate, 12(1), 77-86. 10.1080/10511482.2001.9521399
  32. Lopez, R., 2004, Urban sprawl and risk for being overweight or obese, American Journal of Public Health, 94(9), 1574-1579. 10.2105/AJPH.94.9.1574 15333317 PMC1448496
  33. Nguyen, D., 2010, Evidence of the impacts of urban sprawl on social capital, Environment and Planning B: Planning and Design, 37(4), 610-627. 10.1068/b35120
  34. Sultana, S. and Weber, J., 2007, Journey-to-work patterns in the age of sprawl: Evidence from two midsize southern metropolitan areas, The Professional Geographer, 59(2), 193-208. 10.1111/j.1467-9272.2007.00607.x
  35. Sultana, S. and Weber, J., 2014, The nature of urban growth and the commuting transition: Endless sprawl or a growth wave?, Urban Studies, 51(3), 544-576. 10.1177/0042098013498284
  36. Torrens, P.M., 2008, A toolkit for measuring sprawl, Applied Spatial Analysis and Policy, 1(1), 5-36. 10.1007/s12061-008-9000-x
  37. Zolnik, E.J., 2011, The effects of sprawl on private- vehicle commuting distances and times, Environment and Planning B: Planning & Design, 38(6), 1071-1084. 10.1068/b35105
  38. 국토교통부 실거래가 공개시스템, http://rt.molit.go.kr
  39. 통계청 국가통계포털, http://kosis.kr
  40. 통계청 통계지리정보서비스, http://sgis.kostat.go.kr
  41. 행정안전부 도로명주소 안내시스템, http://www.juso.go.kr
Information
  • Publisher :The Korean Cartographic Association
  • Publisher(Ko) :한국지도학회
  • Journal Title :Journal of the Korean Cartographic Association
  • Journal Title(Ko) :한국지도학회지
  • Volume : 20
  • No :3
  • Pages :73~92
  • DOI :https://doi.org/10.16879/jkca.2020.20.3.073
Journal Informaiton Journal of the Korean Cartographic Association Journal of the Korean Cartographic Association
Online Submission
  • NRF
  • KCI 문헌 유사도 검사
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close