• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.6
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• pp.53-66
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• 2019

The purpose of this study was to suggest indicator-based selection and improvement plans for evaluating urban regeneration projects. First, we selected the indicators by conducting expert surveys and analysis of the responses received. Additionally, using the selected indicators, we analyzed the residents' opinions in Wongogae Village, where urban regeneration projects were in progress. Based on these, we suggested a plan to improve Wongogae Village. According to the study, we classified the urban regeneration evaluation indicators into 'Physical environment', 'Social environment' and 'Economic environment' according to their characteristics. We selected urban regeneration evaluation factors through the first expert survey and MCB analysis. As a result, we selected six factors for the 'Physical environment' category: 'Traffic and pedestrian environment', 'Residential (housing) environment', 'Safety and security environment', 'Greenspace', 'Landscape improvement' and 'Public space', In the 'Social environment' category, four factors were chosen: 'Resident participation', 'Community activation', 'Role of the local government and support centers' and 'Resident education' while for the 'Economic environment' category three factors were selected: 'Local economic revitalization', 'Creating an economy-based environment', 'Job creation'. Next, we conducted a second expert survey and carried out an AHP analysis using the selected evaluation factors to derive the overall weight for each. Among the evaluation factors for urban regeneration, the 'Residential (housing) environment' has the highest weighted value of 0.108, followed by 'Local economic revitalization' and 'Resident participation'. Lastly, the analysis of the residents' opinions of Wongogae Village using the urban regeneration evaluation factors, Parking environment', 'Maintenance of old houses and living environment', 'Environment for founding town and social enterprises', 'Improve commercial and business environment', 'Maintain and activate existing business' and 'Vitalizing small regional economies such as domestic handicrafts and side-job' had high overall importance, but low satisfaction, which means that it is necessary to improve the focus. Therefore, in order to improve the urban regeneration project in villages, it is necessary to improve the parking environment by expanding public parking lots, eliminate close houses, and idle lands, or open a school playground in the village for the residents. In addition, it is essential to encourage economic activities, such as fostering village enterprises and social enterprises in connection with cooperatives and allow for the selling of the products through resident activities, such as neighboring markets.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.3
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• pp.65-84
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• 2023

In order to establish a balanced development plan at the local government level, it is necessary to understand the current urban spatial structure. In particular, since the central area is a key element of balanced development, it is necessary to accurately identify its location and size. Therefore, the purpose of this study was to identify the central area system for Busan and to derive underprivileged areas that were alienated from the service areas where the functions of the central area could be used. To identify the central area system, four indicators(De facto Population, Land Price, Commercial Buildings, Credit Card Consumption) were used to calculate the central area index, and Getis-Ord Gi* and DBSCAN analysis were performed. Next, the hierarchy of the central areas were classified and the service areas were derived through network analysis by using it. As a result of the analysis, a total of 12 central areas were found in Seomyeon, Jungang, Yeonsan, Jangsan, Haeundae, Deokcheon, Dongnae, Daeyeon, Sasang, Pusan National University, Busan Station, and Sajik. Most of the underprivileged areas affected by the central area appeared in the Eastern area of Busan and the Western area of Busan, and were derived from old industrial areas, residential areas, and some new cities. Based on the results of the study, we can find three meanings. First, we have made a new attempt to apply a machine learning methodology that has not been covered in previous studies. Second, our data show the difference between the actual data and the existing planned central areas. Third, we not only found the location of the central areas, but also identified the underprivileged areas.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• 한국노년학
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• v.29 no.1
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• pp.329-352
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• 2009

This study examined life in old age and images of the aged perceived by middle-aged and old-aged generations through indepth interviews with 30 persons aged 40s through 80s residing in three areas (city or county) in capital region in Korea to use it as basic information in planning social welfare policy and reorganizing social services in response to population aging in capital region in Korea. In terms of economic life of the middle-aged and olde-aged generations perceived older people's opportunities for work were rarely given to the aged due to ageism and negative stereotypes of aging and the aged, and the aged tended to regard themselves less able or unable to work. In terms of social life of the aged both middle-aged and old-aged generations perceived that the frequency of social participation was low, and the daily life of the aged was found mostly aimless, unorganized and unplanned. In terms of psycho-social life of the aged both generations still felt that they were not alienated from the family, neighbors, and the society. In terms of social welfare services both generations thought the aged needed basic services such as income maintenance, health care, housing services, and particularly they felt lack of social services. The old-aged generation was willing to travel to the distance taking more than one hour to receive social services that they would need. Both the middle-aged and the old-aged agreed upon the necessity of preparation for old age and the benefits of earlier preparation, however, they said that they could not prepare for their old age due to lack of social programs to help preparation for old age and due to spending for rearing and education of their children. In terms of perceived life in old age both middle-aged and old-aged generations tended to be slightly positive, but the degree of positiveness differed between respondents from urban area and those from rural area regardless of generations. Images of the aged were perceived to be overwhelmingly negative while positive images were very few in number regardless of generations. This finding may suggests that negative stereotypes on aging and the aged are also prevalent in Korean society like in Western societies. Based on findings of this study some implications for social policies in response to population aging in capital region were suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.10
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• pp.4543-4550
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• 2012

The purpose of this paper is to suggest the improvement method to achieve the interactive development effect between high-tech industrial complex and its surrounding areas. For this reason, this paper has conducted an empirical analysis to find out relevant comprehensive factors, affecting nearby housing prices from such plans, especially by reviewing 'Seoul Digital Industrial Complex.' This paper is truly differentiated from previous research by adding a new perspective 'diverse location characteristics', as it focuses not only on 'high-tech facility' characteristics, but also on 'urban function facilities', including 'transportation facilities', 'amenity facilities', 'security facilities', etc. Then, SPSS Version 18.0 was utilized to conduct the multiple regression analysis with the accumulated relevant data and several results were drawn out as following: Firstly, 'deterioration level', 'brand of apartment', etc. are found to be major influencing factors. Secondly, 'educational facilities', 'transportation facilities', 'Cultural & Sports facilities', 'Amenity facilities', etc. are found in the sector of 'location characteristic'. Lastly, 'leading companies within the industrial complex', were also found, affecting nearby housing prices. Therefore, when a housing development project is planned to grant the interactive development effect to high-tech industrial complex and its surrounding housing areas, it is necessary to consider variety factors, such as comprehensive location characteristics and housing complex characteristics, and also proper housing policy measures should be devised in accordance with the actual demand of employees and their dependant family members.