• 환경사랑
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• s.27
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• pp.4-5
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• 2001

• Journal of the Economic Geographical Society of Korea
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• v.16 no.1
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• pp.86-98
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• 2013

This study began with the fact that the relationship between eductional environments and housing price needs to be understood in the context of the structuring of socio-spatial disparity. In other words, this paper focuses on the fact that the eduction with public features and functions plays a role of housing price determination and the rising price is privatized only to cause socio-spatial inequality. The study first examines how the education factors determine the housing price and cause increasing social inequality in Seoul at the macro level. It also carried out more detailed quantitative analysis on the relationship between educational environment factors and housing price with the case study of Yangcheon-gu, Seoul. This study found out that the close relationship between educational environment, housing price and social disparity at various spatial scales. It also figured out the the educational environment factors play an important role of housing price determination as much as material features per se. This means that the relationship between education, housing price and inequality needs to be dealt with not just socially but also in spatial perspective. In addition, the housing price determination is not just technical research but an social science issue in the context of rising socio-spatial disparity. This study is of only significance as a starting point of promising related researches in the future and much more efforts will be needed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.859-867
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• 2019

Severe weather conditions, such as heavy snowfall, rain, heatwave, etc., may affect travel behaviors of people and finally change traffic patterns in transportation networks. To deal with those changes and prevent any negative impacts on the transportation system, understanding those impacts of severe weather conditions on the travel patterns is one of the critical issues in the transportation fields. Hence, this study has focused on the impacts of a weather condition on travel patterns of public transportations, especially when a heavy snowfall which is one of the most critical weather conditions. First, this study has figured out the most significant weather condition affecting changes of public transport ridership using weather information, card data for public transportation, mobile phone data; and then, developed a decision-tree model to determine complex inter-relations between various factors such as socio-economic indicators, transportation-related information, etc. As a result, the trip generation of public transportations in Seoul during a heavy snowfall is mostly related to average access times to subway stations by walk and the number of available parking lots and spaces. Meanwhile, the trip attraction is more related to business and employment densities in that destination.