본 연구에서는 부산시의 대표적인 주거지역이면서 워터프런트지역을 포함하고 발전해 온 수영구와 해운대구를 중심으로 지가와 주거환경요소의 상관성 및 주거환경요소가 지가에 미치는 영향을 고찰해 보고자 했다. 이를 위해 지가를 종속변수로 하고 주거환경요소를 설명변수로 하여 상관분석 및 회귀분석을 실시하였다. 먼저 지가와 각 변수간의 상관성을 보면 모든 대상지역에서 토지이용과 간선도로와의 거리, 지하철역까지의 거리가 공통적으로 지가와 상관성이 높은 변수로 밝혀졌고, 회귀분석을 통해 각 변수별 설명력을 알아본 후 지가에 대한 변수의 설명력이 높은 순으로 누적 설명력을 살펴본 결과 7개의 변수로 수영구는 67%, 해운대구는 50.5%의 설명력이 있는 것으로 드러났다. 또한 본 연구에서 특히 관심을 가지고 설정해 본 해안까지의 거리변수는 지가와 상관분석 결과 모든 대상지역에서 그다지 상관성이 높지 않았으며, 회귀분석 결과에서도 각 지역별로 6.4%~7.6%의 설명력을 갖는 것으로 밝혀져 지가를 설명하는 변수로서 중요도도 높지 않은 것으로 나타났다.
This paper attempted to investigate not only the correlativity of land price and residential environment elements but also the effect that the residential environment elements influence on the land price, focusing on the Suyoung-Gu and Haeundae-Gu which are representative residential and waterfront area in Pusan. For this purpose, regression analysis and correlation analysis as the residential environment elements in independent variable and the land price in dependent variable were carried out. First of all, from the correlation analysis between the land price and the residential environment elements, it become clear that the variables such as the land use, the distance to arterial road and, the distance to subway station have high correlativity with land price in all the research area. Then from the individual power of explanation and accumulative power of explanation of the each variable to the land price through the regression analysis, it was become clear that 7 variables which are the land use, the distance to trunk road, the distance to subway station etc. have 67% of the power of explanation to land price at the Suyoung-Gu, and 50.5% at the Haeundae-Gu. Moreover, researchers had an special interest in the correlativity between the distance to the coastal line and land price as well as the power of explanation of the distance to the coastal line for the land price. It means that researchers expected the variable of the distance to the coastal line have a strong correlativity and high power of explanation for land price. However, from the regression analysis and correlation analysis, it was become clear that the variable of the distance to the coastal line have a weak correlativity, and low power of explanation which is just form 6.4% to 7.6% in all the research area. In other words, it might be said that the variable of the distance to the coastal line is not so important one to presume the land price.
