• Journal of the Society of Disaster Information
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• v.14 no.2
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• pp.182-193
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• 2018

Purpose: The purpose of the study is to analyze the relationship between travel behavior and urban spatial characteristics in a hierarchical manner. Method: This study analyzed the relationship between traffic patterns and urban spatial characteristics for 83 cities in Korea by using a hierarchical linear model. Results: It was found that the urban spatial characteristics influenced the choice of transportation mode and travel time with personal attributes. However, the degree of influence on the choice of the means and the time required is relatively low through the policy of changing the city attribute, so the policy effect of mobilizing the land use policy for the traffic is theoretically, but the scale is not bigger than expected. Conclusion: In high density or the bigger scale of the city, the mass transportation system is widely supplied and used, but it does not overcome the drawback that it takes more time than the autos.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.28-38
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• 2019

The smart card data stores the transit usage records of individual passengers. By using this, it is possible to analyze the traffic demand by station and time. However, since the purpose of the trip is not recorded in the smart card data, the demand for each purpose such as commuting, school, and leisure is estimated based on the survey data. Since survey data includes only some samples, it is difficult to predict public transport demand for each purpose close to the complete enumeration survey. In this study, we estimates the purposes of trip for individual passengers using the smart card data corresponding to the complete enumeration survey of public transportation. We estimated trip purposes such as commute, school(university) considering frequency of O-D, duration, and departure time of a passenger. Based on this, the passengers are classified as workers and university students. In order to verify our methodology, we compared the estimation results of our study with the patterns of the survey data.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.1
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• pp.1-14
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• 2020

Various policies and studies regarding use of PBSS (Public Bike Sharing System) and Programs (PBSP) have been conducted worldwide as the number systems or programs has increased. Although various phenomena and demands have been generated by the use of PBSS in everyday life, the majority of research and the policies in South Korea have been implemented focused on commuting life. The purpose of this study aimed to understand various PBSS demands using PBSS usage data in 2018 in the Yeouido districts through classifying usage patterns and analyzing features. The rental stations were classified into three types based on weekday/weekend usage rates. The usage of Yeouido's PBSS accounted for 4.3% of the total usage in Seoul Metropolitan City, while the number of PBSS rental stations accounted for 2% of all rental stations in the Seoul urban areas. Rental stations with a higher weekday utilization rates showed high utilization rates in all four seasons and were mainly distributed in work and residential areas. Other stations showed a concentrated usage pattern in spring (April-May) and autumn (September-October) seasons, and their locations were close to the entrance of nearby parks. Besides, renting and returning were often concentrated at certain rental stations for high weekend utilization as compared to the pattern of high weekday usage. Therefore, PBSS management and programs should be operated to reflect various usage demands rather than uniform PBSS operations. The result of this study is meaningful to provide basic data for effective PBSS operation by monitoring the demand for PBSS usage in spatio-temporal terms.

• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.1-21
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• 2023

This study analyzed workers' residence and home-based work(HBW) trip by utilizing data from mobile carrier base stations of Gwangyang Port and terminal workers. In the past, research on port-related traffic or trip patterns mainly focused on cargo-based movement patterns for estimating cargo volume and port facilities, but this study analyzed trip patterns for workers in Gwangyang Port ports and related industries. As a result of the analysis, the average number of regular workers in the port hinterland Gwangyang Port was 1,295 per month, and the residence of workers was analyzed in Gwangyang City (66.1%)>Suncheon City (26.6%)>Yeosu City (3.1%). The average number of temporary workers in the hinterland was 2,645 per month, and Gwangyang City (45.8%)>Suncheon City (20.1%)>Yeosu City (5.7%). Next, the average number of regular workers at Gwangyang Port terminals was 753 per month, and Gwangyang City (66.1%)>Suncheon City (28.9%)>Yeosu City (3.3%) was analyzed. The average number of temporary workers at Gwangyang Port terminals was 1,893 per month, and Gwangyang City (50.8%)>Suncheon City (19.7%)>Yeosu City (9.8%). This study is expected to calculate the number of workers based on individual traffic using actual mobile carrier data to estimate the actual number of workers if the workplace address and actual work place are different, such as in port-related industries. This study is the first to be conducted on workers at Gwangyang Port. It is expected to be used as basic data for settlement conditions and urban planning, as well as transportation policies for port workers, by identifying the population coming from areas other than Gwangyang, where Gwangyang Port is located.

• 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.

• The Journal of Bigdata
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• v.7 no.2
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• pp.235-244
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• 2022

The rental history data of public bicycles in Seoul were analyzed to examine how pandemic phenomena such as COVID-19 caused changes in people's micro mobility. Data for 2019 and 2021 were compared and analyzed by dividing them before and after COVID-19. Data were collected from public data portal sites, and data marts were created for in-depth analysis. In order to compare the changes in the two periods, the riding direction type dimension and the rental station type dimension were added, and the derived variables (rotation rate per unit, riding speed) were newly created. There is no significant difference in the average rental time before and after COVID-19, but the average rental distance and average usage speed decreased. Even in the mobility of Ttareungi, you can see the slow rhythm of daily life. On weekdays, the usage rate was the highest during commuting hours even before COVID-19, but it increased rapidly after COVID-19. It can be interpreted that people who are concerned about infection prefer Ttareungi to village buses as a means of micro-mobility. The results of data mart-based visualization and analysis proposed in this study will be able to provide insight into public bicycle operation and policy development. In future studies, it is necessary to combine SNS data such as Twitter and Instagram with public bicycle rental history data. It is expected that the value of related research can be improved by examining the behavior of bike users in various places.