대한공간정보학회지 (Journal of Korean Society for Geospatial Information Science)

  • 제23권3호
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  • Pages.77-84
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  • 2015
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  • 1598-2955(pISSN)
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  • 2287-6693(eISSN)
대한공간정보학회 (Korea Spatial Information Society)
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서울시 유동인구 분포의 공간 패턴과 토지이용 특성에 관한 지리가중 회귀분석

Geographically Weighted Regression on the Characteristics of Land Use and Spatial Patterns of Floating Population in Seoul City

  • 윤정미 (충남연구원 농촌농업연구부) ;
  • 최돈정 (충남연구원 농촌농업연구부)
  • Yun, Jeong Mi (Dept. of Rural & Agricultural Research, Chung Nam Institute) ;
  • Choi, Don Jeong (Dept. of Rural & Agricultural Research, Chung Nam Institute)
  • 투고 : 2015.08.21
  • 심사 : 2015.09.14
  • 발행 : 2015.09.30
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초록

본 연구의 핵심적인 목적은 유동인구 분포의 공간 패턴의 영향요인 분석을 위한 공간회귀모형 적용의 효용성을 검토하는 것이다. 이를 위해 서울시 유동인구 조사 자료를 활용하여 조사지점별 유동인구의 전역적, 국지적 공간 자기상관 측정을 실시하였다. 그 결과 분석에 적용된 공간자기상관 측도인 Moran's I, Getis-Ord-$Gi^*$ 그리고 Local Moran's I 모두에서 통계적으로 유의한 수준의 공간적 유사성과 이질성이 발견되었다. 이를 근거로 유동인구분포와 토지이용 특성과의 관계를 파악하기 위한 통계적 모형으로 공간회귀모형인 지리가중회귀모형(GWR : Geographically Weighted Regression, 이하 GWR)을 채택하였다. 모형의 설명변수로써 서울시 전체에 대한 400m*400m 격자망기반에 토지이용혼합도, 주거 밀도, 상점밀도, 녹지 밀도와, 추가적으로 각 격자별 버스노선밀도, 교차로 밀도, 교통 결절점 접근성, 평균 도로폭, 평균 보도넓이를 산출 및 집계 하였다. 동일한 방식으로 격자망에 집계된 유동인구 정보와 토지이용 및 교통 특성과의 GWR모형 결과를 Ordinary Least Square(OLS) 분석 결과와 비교한 결과 GWR모형의 주요 통계량 수치에서 개선된 결과를 도출하였다. 또한 구획된 격자망의 각 셀별로 도출된 GWR모형의 추론 결과를 검토한 결과 적용된 설명변수의 유동인구 분포에 대한 효과가 국지적으로 변동하는 양상을 파악할 수 있었다.

The key objective of this research is to review the effectiveness of spatial regression to identify the influencing factors of spatial distribution patterns of floating population. To this end, global and local spatial autocorrelation test were performed using seoul floating population survey(2014) data. The result of Moran's I and Getis-Ord $Gi^*$ as used in the analysis derived spatial heterogeneity and spatial similarities of floating population patterns in a statistically significant range. Accordingly, Geographically Weighted Regression was applied to identify the relationship between land use attributes and population floating. Urbanization area, green tract of land of micro land cover data were aggregated in to $400m{\times}400m$ grid boundary of Seoul. Additionally public transportation variables such as intersection density transit accessibility, road density and pedestrian passage density were adopted as transit environmental factors. As a result, the GWR model derived more improved results than Ordinary Least Square(OLS) regression model. Furthermore, the spatial variation of applied local effect of independent variables for the floating population distributions.

키워드

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피인용 문헌

  1. Investigating the Factors Influencing Pedestrian-Vehicle Crashes by Age Group in Seoul, South Korea: A Hierarchical Model vol.12, pp.10, 2020, https://doi.org/10.3390/su12104239
  2. Analysis on the Determinants of Hourly-based Mixed Level of De Facto Population in Seoul, Korea vol.56, pp.1, 2015, https://doi.org/10.17208/jkpa.2021.02.56.1.22