• Journal of the Korean Institute of Landscape Architecture
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• v.16 no.3
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• pp.21-37
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• 1989

Environmental design pattern of the nine Small Urban Spaces at C.B.D. in City of Seoul are surveyed and analyzed for user's satisfaction and behavior under the environmental design evaluation by using Christopher Alexander's Pattern Language. Small Urban Spaces as a part of streetscape are formed by physical factors as well as visual environment and interacting user's behavior. Therefore, user's satisfaction and behavior at the nine Urban Small Spaces were investigated under the further search for some possibilities of application of those Pattern Languages. A pattern language has a structure of a network. It is used in sequence, going through the patterns, moving always from large patterns to smaller, always from the ones which create comes simply from the observation that most of the wonderful places of the city were not blade by architects but by the people. It defines the limited number of arrangements of spaces that make sense in any given culture. And it actually gives us the power to generate these coherent arrangement of space. As a results, 'Plaza', 'Seats'and 'Aecessibility' related design Patterns are highly evaluated by Pattern Frequency, Pattern Interaction and their Composition ranks, thus reconfirm Whyte's Praise of urban Small Spaces in our inner city design environments. According to the multiple regression analysis of user's evaluation, the environmental functions related to the satisfaction were 'Plaza', 'Accessibility' and 'Paving'. According to the free response, user's prefer such visually pleasing environmental design object as 'Waterscape' and 'Setting'. In addition to, the basic needs in Urban Small Spaces are amenity facilities as bench, drinking water and shade for rest.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.6
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• pp.603-611
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• 2020

This study collected and analyzed transportation card data in order to better understand the operation and usage of city buses in Ulsan Metropolitan City in Korea. The analysis used quantitative and qualitative indicators according to the characteristics of the data, and also the categories were classified as general status, operational status, and satisfaction. The existing city bus survey method has limitations in terms of survey scale and in the survey process itself, which incurs various types of errors as well as requiring a lot of time and money to conduct. In particular, the bus means indicators calculated using transportation card data were analyzed to compensate for the shortcomings of the existing operational status survey methods that rely entirely on site surveys. The city bus index calculated by using the transportation card data involves quantitative operation status data related to the user, and this results in the advantage of being able to conduct a complete survey without any data loss in the data collection process. We took the transportation card data from the entire city bus network of Ulsan Metropolitan City on Wednesday April 3, 2019. The data included information about passenger numbers/types, bus types, bus stops, branches, bus operators, transfer information, and so on. From the data analysis, it was found that a total of 234,477 people used the city bus on the one day, of whom 88.6% were adults and 11.4% were students. In addition, the stop with the most passengers boarding and alighting was Industrial Tower (10,861 people), A total of 20,909 passengers got on and off during the peak evening period of 5 PM to 7 PM, and 13,903 passengers got on and off the No. 401 bus route. In addition, the top 26 routes in terms of the highest number of passengers occupied 50% of the total passengers, and the top five bus companies carried more than 70% of passengers, while 62.46% of the total routes carried less than 500 passengers per day. Overall, it can be said that this study has great significance in that it confirmed the possibility of replacing the existing survey method by analyzing city bus use by using transportation card data for Ulsan Metropolitan City. However, due to limitations in the collection of available data, analysis was performed only on one matched data, attempts to analyze time series data were not made, and the scope of analysis was limited because of not considering a methodology for efficiently analyzing large amounts of real-time data.