• Journal of the Korean Regional Science Association
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• v.33 no.1
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• pp.29-41
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• 2017

This study proposes an integrated accessibility measurement algorithm, which is applied to the Seoul Metropolitan public transportation system consisting of bus and subway networks, and analyzes the result. We construct a public transportation network graph linking bus-subway networks and take the time distance as the link weight in the graph. We develop a time-distance algorithm to measure the time distance between each pair of transit stations based on the T-card transaction database. The average travel time between nodes has been computed via the shortest-path algorithm applied to the time-distance matrix, which is obtained from the average speed of each transit route in the T-card transaction database. Here the walking time between nodes is also taken into account if walking is involved. The integrated time-distance accessibility of each node in the Seoul Metropolitan public transportation system has been computed from the T-card data of 2013. We make a comparison between the results and those of the bus system and of the subway system, and analyze the spatial patterns. This study is the first attempt to measure the integrated time-distance accessibility for the Seoul Metropolitan public transportation system consisting of 16,277 nodes with 600 bus routes and 16 subway lines.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.379-395
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• 2006

The purpose of this study is to analyze the spatial characteristics of travel patterns and travel behaviors of transit users in the Metropolitan Seoul area. We apply the data mining techniques to explore the travel patterns of transit users from the T-money card database which has been produced over 10,000,000 transaction records per day. The database contains the information of locations and times of origin, transfer, and destination points for each transaction as well as the informations of transit modes taken via the transaction. We develop an data mining algorithm to explore traversal patterns from the enormous information. The algorithm determines the travel sequences of each passenger, and produce the volumes of support on each points (stops) of transportation networks in the Metropolitan Seoul area. In order to visualize the spatial patterns of travel demands for transit systems we apply GIS techniques, and attempt to investigate the spatial characteristics of travel patterns and travel demand. Subway stops located in the Gangnam area appear the highest peak for the travel origin and destination, while the CBD in the Gangbuk stands at the second position. Two or three sub-peaks appear at the densely populated residential areas developed as the high-rise apartment complex. Subway stations located along the Subway Line 2, especially from Guro to Samsung receive heavy travel demand (total support), while bus stops located at the CBD in the Gangbuk stands the highest travel demand by bus.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.335-349
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• 2018

This study analyzes the effect of the changes in traffic environments such as transportation speeds on the time-distance accessibility for the public transportation passengers. To do this, we use passenger transaction databases of the Seoul metropolitan public transportation system: one week for each of the three years (2011, 2013, and 2015). These big data contain the information about time and space on the traffic trajectories of every passenger. In this study, the time-distances of links between subway stations and bus stops of the public transportation system at each time are calculated based on the actual travel time extracted from the traffic-card transaction database. The changes in the time-distance accessibility of the integrated transportation network from the experimental results can be summarized in two aspects. First, the accessibility tends to decline as the year goes by. This is because the transportation network becomes more complicated and then the average moving speed of the vehicles is lowered. Second, the accessibility tends to increase on the weekend in the analysis of accessibility changes by day. This tendency is because the bus speeds on bus routes on the weekend are faster than other days. In order to analyze the accessibility changes, we illustrate graphs of the vehicle speeds and the numbers of passengers by year and day.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.397-405
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• 2010

This study proposes visualization methods of the diurnal passenger flows on the Metropolitan Seoul Subway system (MSSs) and examines the passenger trip behaviors of major central business districts (CBDs). We mine the MSS passenger flow information from a single day T-card passenger trip transaction database. It is practically intractable to analyze such flows, involving huge, complex space-time data, by means of general statistical analysis. On the other hand, dynamic visualizations of the passenger flows make it possible to analyze intuitively and to grasp effectively characteristics of the passenger flows. We thus propose several methods to visualize the passenger flow information. In particular, we visualize dynamic passenger flows of each link on the subway network and analyze the time-space characteristics of passenger ridership for the three major CBDs. As the result, we can ascertain the strong association between CBD and subway line and clarify the distinction among three major CBDs in the diurnal patterns of subway passenger flow.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.1
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• pp.59-77
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• 2008

The purpose of this study is to investigate the impact of traffic-related air pollution on the urban population in the Metropolitan Seoul area. In particular, this study analyzes urban population exposure to traffic-related particulate materials(PM). For the purpose, this study examines the relationships between traffic flows and PM concentration levels during the last fifteen years. Traffic volumes have been decreased significantly in recent year in Seoul, however, PM levels have been declined less compare to traffic volumes. It may be related with the rapid growth in the population and vehicle numbers in Gyenggi, the outskirt of Seoul, where several New Towns have been developed in the middle of 1990's. The spatial pattern of commuting has changed, and thus and travel distances and traffic volumes have increased along the main roads connecting CBDs in Seoul and New Towns consisting of large residential apartment complexes. These changes in traffic flows and travel behaviors cause increasing exposure to traffic-related air pollution for urban population over the Metropolitan Seoul area. GIS techniques are applied to analyze the spatial patterns of traffic flows, population distributions, PM distributions, and passenger flows comprehensively. This study also analyzes real time base traffic flow data and passenger flow data obtained from T-card transaction database applying data mining techniques. This study also attempts to develop a space-time model for assessing journey-time exposure to traffic related air pollutants based on travel passenger frequency distribution function. The results of this study can be used for the implications for sustainable transport systems, public health and transportation policy by reducing urban air pollution and road traffics in the Metropolitan Seoul area.