• Proceedings of the Korean Society of Crop Science Conference
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• 1992.05a
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• pp.78-79
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• 1992

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.595-600
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• 2011

This study analyzed passenger's access modes that connect to regional railway station and developed a model of access mode choice based on transit smart card data of Seoul station as a case study. The study boundary includes sixteen bus stops around the station. The results show that most passengers access to station have less than two transfers. Of total 15000, eighty percent of passengers use metro and the rest of people take a bus. Interestingly, it is found that almost same proportions of passengers use metro and bus for egress the station. Consequently, metro is found to be most likely used mode compared to bus for both access and egress trips.

• Journal of Korean Society of Transportation
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• v.24 no.2 s.88
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• pp.147-156
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• 2006

Metropolitan Subway, tke volume of station, distance between station is short. when the demand is concentrated during moving peak periods, the Headway that than Line Headway in which Station Headway is applied to Station Capacity computation be. The factors to determine the Station Headway have a fixing Price of the machine and the Dwell time. Other factors aye decided already or fixing price but the Dwell time that change according to demand cause the biggest effect at Station Headway. After analyze constituents that influence to Station Headway in this study calculated correct Station Capacity drawing estimating dwell time model that change according to demand.

• 한국가스학회:학술대회논문집
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• 1998.09a
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• pp.13-18
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• 1998

• 한국가스학회:학술대회논문집
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• 1999.09a
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• pp.14-19
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• 1999

• Proceedings of the Korean Society of Crop Science Conference
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• 2004.04a
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• pp.72-73
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• 2004

• The Plant Pathology Journal
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• v.17 no.6
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• pp.389.5-390
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• 2001

• Journal of the Korean Society for Railway
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• v.7 no.2
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• pp.155-162
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• 2004

In order to account for a price variation of apartment that places near a newly constructed subway station, a spatial hedonic model was developed to examine spacial characteristics that affect a purchasing price of an apartment using a White Estimator. In particular, the paper aims to examine various effects of subway 7 construction on an apartment price in Seoul Metropolitan Area. As explanatory variables, an apartment size, distance to a closest subway station, distance to the Central Business District (CBD) of Seoul, the number of years after building, and a lagged variable of the apartment purchasing price were used. The lagged variable plays a role of representing a spatial weighted average of previous prices of other apartments that locate within 3 km from the apartment. For a precise study, an entire sample was divided into two sets, southern area and southwestern area of Seoul, and two different spatial hedonic models were estimated. Not only before and after analysis, but also with and without analysis were conducted to compare with different effects of the spatial characteristics of two areas. The results show that before the construction of the subway 7, the prices of the apartments in the southern area were more sensitive to the apartment size, the distance to a closest subway station, the distance to the CBD, and the prices of the other apartments locating within 3km rather than those in the southwestern area. After the construction, on contrast, it is found that the apartment purchasing prices in the southwestern area are more sensitive than those in the southern area due to people's expectation regarding a new development around the subway station. In addition, the prices of the apartments locating closely with a transfer station are more likely to go up by increase in the apartment size, the distance to the station, and the prices of the other apartments within 3 km. Compared with the negative effects of the distance to the station on the prices in the other models, the positive effect of the distance to the transfer station might be caused by the characteristics of commercial area in which people are not likely to live.

• Journal of Environmental Health Sciences
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• v.45 no.2
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• pp.186-191
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• 2019

Objectives: Subway is one of the most common transportation modes in Seoul, Korea. The objectives of this study were to determine characteristics of in-cabin $PM_{2.5}$ concentration in Seoul Metro Line Number 2 and to identify factors of the $PM_{2.5}$ concentration. Methods: In-cabin $PM_{2.5}$ concentrations in Seoul Metro Line Number 2 were measured using real-time monitors and the factors affecting $PM_{2.5}$ concentration in cabin were observed. Linear regression analysis of in-cabin $PM_{2.5}$ concentration and indoor/outdoor (I/O) ratio were performed. Results: In-cabin $PM_{2.5}$ concentration was associated with the in-cabin $PM_{2.5}$ concentration in previous station. In-cabin $PM_{2.5}$ concentration was correlated with ambient $PM_{2.5}$ concentration and associated with underground station with control of the in-cabin $PM_{2.5}$ concentration in previous station. I/O ratio increased as the number of passengers increased and when passing through the underground station with control of I/O ratio in previous station. Conclusion: In-cabin $PM_{2.5}$ concentration was affected by ambient $PM_{2.5}$ concentration. Therefore, management of in-cabin $PM_{2.5}$ concentrations should be based on outdoor air quality.

• Journal of Information Technology Services
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• v.17 no.4
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• pp.139-150
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• 2018

This paper investigated the human distribution in subway station areas in Seoul, using geotweets and subway ridership data. Eight stations were selected from the districts of Gangnam and Gangbuk. Geotweets located within a 600-meter radius of the central coordinates of each station were extracted, and distances between the center of station and each tweet location were calculated. Donut-shaped dimension and pie-shaped dimension were generated, using the Haversine distance formula and the Azimuth angle formula respectively. By combining the two dimensions, Dartboard-shaped space division is created. Popular places within the subway station areas identified from this research are almost the same as the current well-known popular places, and this is an important case showing that people send tweets from various places where they engage in daily activities. We expect this study can be a methodological guideline for social scientists who use spatio-temporal or GPS data for their research.