Abstract
본 연구는 지역간 형평성을 분석하기 위하여 교통인프라지표와 통행행태를 통합적으로 고려하였다. 교통인프라지표로는 도로시설, 대중교통시설, 지역특수지수를 이용하였다. 통행행태는 1일자의 버스교통카드데이터를 이용하였다. 공간군집 분석과 전역적 국지적 분석을 통해 얻은 결과 분석단위를 읍 면 동으로 하였을 때 해당지역과 주변지역의 인프라수준이 높은지역(High-High)에서 모두 낮은지역(Low-Low)등 4개의 수준으로 구분되었다. HH type의 지역에서는 버스이용자, 통행, 환승 수가 높고, LL Type의 지역은 내부통행수, 통행시간, 통행거리, 통행속도, 요금항목이 높게 나타났다. 전역적 회귀분석에 의해 교통인프라 수준을 통행행태 변수로 회귀한 결과, 버스이용자수(bus users), 평균환승수(mean_trans), 평균내부통행수(mean_inside), 평균통행속도(mean_speed), 총 4개의 통행특성 변수가 유의하게 추출되었다. 이들 변수를 적용하여 국지적 회귀분석(GWR)을 수행한 결과 전역적 회귀분석에 비해 AIC와 ANOVA 결과 모두 모형의 결과를 유의하게 향상시켜, 경기도 내 통행행태 특성이 교통인프라 수준을 설명하는 데 있어 지역 간 차이가 많이 존재하는 것을 다시 한 번 확인시켜주었다. This study aims at analyzing transportation equity between geographical areas of Gyonggi Province, by taking both the transportation infrastructure and travel behavior into account. Indicators of transportation infrastructure include the indices of road infrastructure, transit infrastructure and regional characteristics. Travel behavior concerns information from bus card data on a survey day. The hot-spot analysis conducted included spatial cluster analysis and global/local regression analyses. The analysis results identified geographical areas of four different classes of transportation equity, from the area with high level infrastructure surrounded by the areas with high level infrastructure (HH) to the area with low level surrounded by the areas with low level (LL). The area of HH type showed big numbers of passengers, trips and transfers, whereas the area of LL type shows big figures of internal trip frequency, travel time, travel distance, travel speed and transit fare. Global regression analysis showed that number of passengers, number of transfers, number of internal trips and mean travel speed are important to the level of transportation infrastructure. GWR with these four significant variables significantly improved the AICs and ANOVA results, which implies that the infrastructure is likely explained by travel characteristics differently between geographical areas in Gyonggi Province.
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