• Journal of Advanced Navigation Technology
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• 제27권4호
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• pp.488-494
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• 2023

In this paper, scenario-based urban flood prediction for the entire Jinju city was performed, and a simulation domain was constructed using G2D as a 2-dimensional urban flood analysis model. The domain configuration is DEM, and the land cover map is used to set the roughness coefficient for each grid. The input data of the model are water level, water depth and flow rate. In the simulation of the built G2D model, virtual rainfall (3 mm/10 min rainfall given to all grids for 5 hours) and virtual flow were applied. And, a GPU acceleration technique was applied to determine whether to run the flood analysis model in the target area. As a result of the simulation, it was confirmed that the high-resolution flood analysis time was significantly shortened and the flood depth for visual flood judgment could be created for each simulation time.

• Journal of the Korean Association of Geographic Information Studies
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• 제18권2호
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• pp.59-74
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• 2015

The purpose of this study is to analyze reasonable green area ratios for mitigating urban heat island considering various land use types. Land uses of 5 types such as single residential, multi residential, commercial area, public facility, and industrial area were considered. Green areas were extracted from the tree attribution of land cover. Effect of urban heat island was analysed by the surface temperature of ASTER thermal infrared radiance scanned daytime and nighttime. Mitigation effect of green area at daytime was higher than nighttime. Surface temperature of green area was low in single residential at daytime. But the difference of surface temperature by each land use type was small. The effect of surface temperature mitigation of green area was lower in industrial area. The results of reasonable green area ratios for mitigating urban heat island indicate that surface temperature was the lowest with green area ratio of 40~50% in single residential, multi residential, and commercial area at daytime. Surface temperature of nighttime was not changed much by green area ratios. Therefore, the results of this study will be suggested in urban development planning to construct effectively green area for mitigating urban heat island.

• Journal of the Korean Association of Geographic Information Studies
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• 제22권2호
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• pp.65-81
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• 2019

This study analyzed the relationship of land cover type, urban temperature in Gimhae city, Gyeongsangnam-do, South Korea. Date were used for land cover map, MODIS LST, and detailed temperature data on the Korean Peninsula based on RCP between 2000 and 2010. The correlation between urban area and surface temperature was 0.417, 0.512 for agricultural area and -0.607 for forest area. The correlation between surface temperature and air temperature was 0.301. The relationship with air temperature was analyzed as 0.275 for urban area, agriculture area 0.226, forest area 0.350. Urban and agricultural areas showed increased surface and air temperature as the area increased, while forest areas showed opposite improvements. In structural equation models, urban and agricultural areas had direct effects on the rise of surface temperature, whle forest areas had direct effects on the reduction of air temperature. In the future, it is necessary to use measured temperature data near the surface to understand the relationship between surface temperature and temperature according to the changes in spatial characteristics, which will prepare measures for urban heat island mitigation at the level of urban and environmental planning.

• The Journal of the Korea Contents Association
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• 제19권2호
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• pp.340-348
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• 2019

This study analyzes the factors that influence commercial gentrification in Seoul by using both logit model analysis and machine learning with data cumulated from 2015 to 2018 regarding 158 market areas. Logit analysis indicates that log(market area average monthly rent) and the ratio of the purchasing amount by customers aged 40 and younger to total sales in the restaurant and retail business category are statistically significant at 1%; the increase in sales per female customer aged between 30 and 39 in the restaurant and retail business category is statistically significant at 5%; and the increase in number of retailers with a business history of less than two years in the franchise business category is significant at 10%. Machine learning indicates that significant factors ordered by importance are the total retail area, the existence of an industrial complex within the market area, the existence of a traditional market within the market area, the location of subway stations within the market area, the increase of entertainment facilities such as movie theaters within the market area, average monthly rent, and the growth rate of average monthly rent. The contribution of this research is threefold. First, this study analyzes the entire commercial area of Seoul, Korea. Second, this study provides a foundation for future research on predictive indicators by empirically investigating the factors that influence commercial gentrification in Seoul. Lastly, this study introduces various methods of research by utilizing a machine learning approach.

• Proceedings of the KSRS Conference
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• 대한원격탐사학회 2006년도 춘계학술대회 논문집
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• pp.63-67
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• 2006

본 연구에서는 해안침식이 진행되고 있는 해운대 해수욕장의 장기 해안지형 변화 및 인근지역의 토지피복 변화에 대해 분석하였다. 지난 60여 년간의 항공사진을 이용하여 해안선을 추출하고 이를 수심측량 및 GPS측량 자료를 이용하여 조위보정한 후, 해빈면적을 추출하여 해안지형 변화를 분석하였다. 또한 환경부 토지피복 세분류를 기준으로 하여 육안판독을 통해 13개년도의 토지피복도를 제작하고 토양유실량을 산정하여 연도별 토지피복 변화를 분석하였다. 그 결과, 해운대 해수욕장의 해안선이 점진적으로 후퇴하고 있으며 해수욕장 면적이 전체적으로 감소하고 있는 것으로 나타났다. 춘천천 복개 및 도시개발에 의한 모래 공급원 차단이 이러한 해안침식에 영향을 주는 인위적 원인이라고 사료된다.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2015년도 학술발표회
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• pp.442-442
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• 2015

최근 도시 집중화 개발사업의 증가로 인해 유역의 유출환경이 크게 변화하고 있다. 특히, 도시화에 따른 불투수층 토지가 크게 증가함에 따라 지표면의 이용과 형질이 변형됨으로써 지표수 흐름과 지하수 함양 및 오염 등의 문제가 심각하게 대두되고 있는 실정이다. 제주도는 관광객 증가로 인한 각종 개발사업이 지속적으로 추진되고 있으나, 사전재해 영향성검토에서는 개발사업 소유역을 중심으로만 평가하고 있어 하천유역의 도시화에따른 홍수재해 영향은 검토하지 못하고 있는 실정이다. 따라서 본 연구에서는 제주도 도심하천인 한천유역을 대상으로 국가 수자원관리 종합시스템과 환경부에서 제공하는 1980년부터 2005년까지 5년 주기의 토지피복도를 이용하여 유역 내 토지이용 변화를 분석하고 호우사상에 따른 홍수유출 변동을 분석하여 토지이용 변화가 홍수유출량 미치는 영향을 도출하고자 한다.

• Journal of Intelligence and Information Systems
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• 제26권3호
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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."

• Korean Journal of Remote Sensing
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• 제33권6_3호
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• pp.1223-1232
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• 2017

This paper presents an approach to detect changes caused by urban development over a large area using KOMPSAT optical images. In order to minimize the radiometric dissimilarities between the images acquired at different times, we apply the grid-based rough radiometric correction as a preprocessing to detect changes in a large area. To improve the accuracy of the change detection results for urban development, we mask-out non-interest areas such as water and forest regions by the use of land-cover map provided by the Ministry of Environment. The Change Vector Analysis(CVA) technique is applied to detect changes caused by urban development. To confirm the effectiveness of the proposed approach, a total of three study sites from Sejong City is constructed by combining KOMPSAT-2 images acquired on May 2007 and May 2016 and a KOMPSAT-3 image acquired on March 2014. As a result of the change detection accuracy evaluation for the study site generated from the KOMPSAT-2 image acquired on May 2007 and the KOMPSAT-3 image acquired on March 2014, the overall accuracy of change detection was about 91.00%. It is demonstrated that the proposed method is able to effectively detect urban development changes in a large area.

• Korean Journal of Remote Sensing
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• 제22권6호
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• pp.565-574
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• 2006

Satellite images have been used to obtain land cover information that is one of important factors for hydrological analysis over a large area. In urban area, more detailed land cover data are often required for hydrological analysis because of the relatively complex land cover types. The number of land cover classes that can be classified with traditional multispectral data is usually less than the ones required by most hydrological uses. In this study, we present the capabilities of hyperspectral data (Hyperion) for the classification of hydrological land cover types in urban area. To obtain 17 classes of urban land cover defined by the USDA SCS, spectral mixture analysis was applied using eight endmembers representing both impervious and pervious surfaces. Fractional values from the spectral mixture analysis were then reclassified into 17 cover types according to the ratio of impervious and pervious materials. The classification accuracy was then assessed by aerial photo interpretation over 10 sample plots.

• Journal of Korean Public Health Nursing
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• 제22권2호
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• pp.224-236
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• 2008

Purpose: The principal objective of this study was to assess the relationships of depression, fatigue, BMI, and health locus of control between urban and rural female middle school students. Methods: The study subjects included 377 girls in randomly-sampled middle schools in urban and rural provinces. The data were collected via self-recorded questionnaires from April 21.- to May 2. 2008, and analyzed using the SPSS Win 12.0 program. Results; 1) The mean score of depression was $10.22{\pm}5.72$ (urban), $10.81{\pm}4.92$ (rural). 2) The mean fatigue score was $50.43{\pm}1.57$ (urban), $51.90{\pm}9.70$ (rural). 3) BMI was classified into 3 groups: leptosomic, normal weight, and obesity groups. The mean BMI score was $18.73{\pm}2.05$ (Seoul), and $20.31{\pm}3.26$ (provincial). 4) The internal locus of control was higher than the external locus of control (urban). 5) Fatigue was correlated with depression (r=.512, p=.000) in both areas. The health locus of control was correlated with Fatigue (r=.153, p=.042) in province. Conclusion: An effective program to reduce the levels of fatigue and depression for middle school girls and to maintain normal weight is required. In particular, the high-risk depression group can be managed through community mental health care center deep interviews, and close observation.