• Journal of Environmental Impact Assessment
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• v.18 no.1
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• pp.1-9
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• 2009

Even though the center of Cheongju city needs redevelopment because of a doughnut phenomenon, it has to be permitted within the environmental carrying capacity like a target water quality proposed on the Total maximum daily loads(TMDL) of Musim and Miho river watersheds. The aim of in this study is to identify the limit of redeveloping Cheongju downtown after analyzing its environmental carrying capacity using QUAL2E model. As a result of modeling various scenarios, the water quality of Musin river was shown that $BOD_5$ is 2.3mg/L which is the target water quality in the double of existing development plan of the Cheongju downtown. The water quality of Miho river was $BOD_5$ 3.97mg/L which is less than the target water quality of Miho B watershed in the same condition. Therefore, this means that the limit of redevelopment within the environmental carrying capacity of cheongju downtown was estimated to be the double of existing development plan.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.4
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• pp.92-101
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• 2011

This study analyzed the urban structure of Jinju city where urban doughnut phenomena, development of new town at suburban zone and establishment of innovation city appear. The sphere of this study was set limit to Jinju's dong area due to taking the limitation of data. Multivariate analysis was done by using 24 variables to classify into seven clusters(CBD, Industrial Area, Residential Area etc). We studied regional condition and problems at the relation between analyzed regional features of this study and development principles at the upper planning. Jinju city needs urban redevelopment, reconstruction works and redevelopment promotion project for urban outworn zone in view of the regional conditions to innovate outdated city image and restore western Gyeongnam as a central city and also they should promote innovative city that is progressing now and construction of new town that is linked with Sangpyeong industrial complex removal as well as the whole Chojang-dong zone. In conclusion, this study will help to understand regional phenomenon like regional development project and urban management.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.63-72
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• 2022

The extinction crisis of local cities, caused by a population density increase phenomenon in capital regions, directly causes the increase of vacant houses in local cities. According to population and housing census, Gunsan-si has continuously shown increasing trend of vacant houses during 2015 to 2019. In particular, since Gunsan-si is the city which suffers from doughnut effect and industrial decline, problems regrading to vacant house seems to exacerbate. This study aims to provide a foundation of a system which can predict and deal with the building that has high risk of becoming vacant house through implementing a data driven vacant house prediction machine learning model. Methodologically, this study analyzes three types of machine learning model by differing the data components. First model is trained based on building register, individual declared land value, house price and socioeconomic data and second model is trained with the same data as first model but with additional POI(Point of Interest) data. Finally, third model is trained with same data as the second model but with excluding water usage and electricity usage data. As a result, second model shows the best performance based on F1-score. Random Forest, Gradient Boosting Machine, XGBoost and LightGBM which are tree ensemble series, show the best performance as a whole. Additionally, the complexity of the model can be reduced through eliminating independent variables that have correlation coefficient between the variables and vacant house status lower than the 0.1 based on absolute value. Finally, this study suggests XGBoost and LightGBM based machine learning model, which can handle missing values, as final vacant house prediction model.