대한지리학회지 (Journal of the Korean Geographical Society)

대한지리학회 (The Korean Geographical Society)
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Regression-Kriging 모형을 이용한 인구분포 추정에 관한 연구

Population Distribution Estimation Using Regression-Kriging Model

  • 투고 : 2010.11.09
  • 심사 : 2010.12.15
  • 발행 : 2010.12.31
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초록

센서스 단위의 인구자료는 기초적인 인문사회 자료로 행정구역 단위로 요약되어 공간분석에 시용된다. 정밀한 인구 분포를 추정하기 위해 기존의 연구에서는 위성영상과 회귀분석 모형을 이용하였다. 하지만 회귀식에 의한 추정치는 공간자료의 공간적자기상관과 잔차 때문에 정확도에 있어 한계가 있었다. 본 연구는 회귀모형과 회귀모형에서 추출된 잔차에 대해 공간적자기상관을 고려하도록 크리깅 보간하는 RK모형(Regression Kriging Model)을 이용하여 인구분포의 추정 정확도를 향상하였다. RK모형을 적용하여 서울시의 4개구를 대상으로 사례분석을 하였으며, 모형의 효율성을 검증하기 위해 회귀분석만을 이용한 예측 결과와 RK모형을 이용한 예측 결과를 서로 비교하였다. 비교한 결과로 상관관계 계수 평균제곱근 오차, G 통계량 수치에서 RK모형의 추정 정확도가 기존의 회귀모형에 비해 높게 나온 것을 확인할수 있었다. 향후 정확한 인구추정을 위해 RK모형이 많이 활용될 수 있을 것이다.

Population data has been essential and fundamental in spatial analysis and commonly aggregated into political boundaries. A conventional method for population distribution estimation was a regression model with land use data, but the estimation process has limitation because of spatial autocorrelation of the population data. This study aimed to improve the accuracy of population distribution estimation by adopting a Regression-Kriging method, namely RK Model, which combines a regression model with Kriging for the residuals. RK Model was applied to a part of Seoul metropolitan area to estimate population distribution based on the residential zones. Comparative results of regression model and RK model using RMSE, MAE, and G statistics revealed that RK model could substantially improve the accuracy of population distribution. It is expected that RK model could be adopted actively for further population distribution estimation.

키워드

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