• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.5
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• pp.1791-1798
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• 2010

This research predicted the change and characteristics of space structure by new residential area development through objective and quantitative analysis of urban spatial configuration using space syntax and associated the prediction with the city status statistics data and quantitative analysis, and the results are summarized as follows: (1) If large scale new residential area of Dongnae township proceeds to be developed according to present plan, accessibility to the new residential area will drop, and also as the outside space ripple effects by new residential area development also are anticipated small, the new residential area apprehensibly will not succeed to play the role of integrating the entire city structurally, but will cause structural problem, severing the city structure. (2) If the city planned road between existing urban center planned based on 2004 Chuncheon city plan overall drawing and main road which is the entrance road of the planned new residential area is developed together, the accessibility to the entire space of Chuncheon city and the new residential area will be easy, allowing the new residential area properly integrated into the entire space of Chuncheon city, consequently giving a prediction that classification of land use between the central part of Chuncheon city and surrounding residential area would become conspicuous.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.445-450
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• 2008

Recently, environmental and ecological approaches is in progress in urban stream, especially the guarantee of instream flow becomes very important. In this paper, it is suggested that water volume estimation method utilizing the topographical shape data obtained by field investigation and satellite image to manage the urban stream efficiently. The data obtained at Gap River is the study area are analysed and those results are as belows. First, surveying to investigate topographic shape characteristics of urban stream is carried out. In details, the gradient characteristics from water surface to bottom in case of sand area and in case of grass area are 0.013 and 0.065 respectively. In conclusion, the gradient characteristic of grass area is five times bigger than that of sand area. Besides, IKONOS image is classified by spectrum analysis and Minimum Distance Method and the sand area extraction method by the generalization method as Median filter is suggested to calculate water volume. Finally, mapping process on the sand area extracted from the topographical shape field data in river and satellite images is carried out by the GIS spatial analysis. And on the assumption that the water level was 1m at that time when satellite image was taken, the water volume was $225,258m^3$. It is clarified that the effect of water volume improvement was about 10.5% in comparison with water volume that had no consideration on the gradient characteristics of sand-bar.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.3
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• pp.9-20
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• 2008

The government is planning to link a small park with the soon to be ready subway line 9 as a part of Seoul's policy, "The standard or plan for making a water-friendly space by water use" (2007). However, the specified concepts and instructions of the small parks need further work. Therefore, the policy is expected to expand to neighboring small parks near the subway station, but these are not supported by research or data which suggests the needs or actual user behavior and utilization of small parks. our country added the specified concept of small parks and theme parks to the classification of urban parks in the Urban Park Act Revision (2005.3.31), but the concept of small parks is not clearly settled in the law in the scopes of its function, scale, promotion nor particularly defined plans for small park projects. This study examines as small park near a subway station. The characteristics of there region and users vary from the characteristics of the station and region. In the "directions for concrete standards under the types of urban parks and green zones" (2007.2) the types of small parks are classified by "regional characteristics" and "user characteristics". Therefore, this study classifies the subject of neighboring small parks near subway stations as the neighborhood and small urban parks according to the Urban Park Act. The study was paralleled with observation and questionnaires on the analysis of the neighborhood and small urban parks. The actual conditions of park utilization and user behavioral characteristics were deducted by observation, while the questionnaire determined actual user utilization, importance and satisfaction level as well as the small park environment. This study largely focused on three aspects: park facility, design of this sentence isn't even complete. The second aspect isn't finished and the third isn't here.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.1-16
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• 2017

This study was conducted to analyze the urban heat island(UHI) intensity of South Korea by using Moderate Resolution Imaging Spectroradiometer(MODIS) satellite imagery. For this purpose, the metropolitan area was spatially divided according to land cover classification into urban and non-urban land. From the analysis of land surface temperature(LST) in South Korea in the summer of 2009 which was calculated from MODIS satellite imagery it was determined that the highest temperature recorded nationwide was $36.0^{\circ}C$, lowest $16.2^{\circ}C$, and that the mean was $24.3^{\circ}C$, with a standard deviation of $2.4^{\circ}C$. In order to analyze UHI by cities and counties, UHI intensity was defined as the difference in average temperature between urban and non-urban land, and was calculated through RST1 and RST2. The RST1 calculation showed scattered distribution in areas of high UHI intensity, whereas the RST2 calculation showed that areas of high UHI intensity were concentrated around major cities. In order to find an effective method for analyzing UHI by cities and counties, analysis was conducted of the correlation between the urbanization ratio, number of tropical heat nights, and number of heat-wave days. Although UHI intensity derived through RST1 showed barely any correlation, that derived through RST2 showed significant correlation. The RST2 method is deemed as a more suitable analytical method for measuring the UHI of urban land in cities and counties across the country. In cities and counties with an urbanization ratio of < 20%, the rate of increase for UHI intensity in proportion to increases in urbanization ratio, was very high; whereas this rate gradually declined when the urbanization ratio was > 20%. With an increase of $1^{\circ}C$ in RST2 UHI intensity, the number of tropical heat nights and heat wave days was predicted to increase by approximately five and 0.5, respectively. These results can be used for reference when predicting the effects of increased urbanization on UHI intensity.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.43-50
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• 2016

Urbanization in Korea has increased significantly and subsequently, various facilities have been concentrated in urban areas at high speed in accordance with a growing urban population. Accordingly, damages have occurred due to a variety of disasters. In particular, fire damage among the social disasters caused the most severe damage in urban areas along with traffic accidents. 44,432 cases of fire occurred in 2015 in Korea. Due to these accidents, 253 were killed and property damage of 4,50 billion won was generated. However, despite the efforts to reduce a variety of damage, fire danger still remains high. In this regard, this study collected fire data, generated from 2007 to 2014 through the Jinju Fire Department and the National Fire Data System(NFDS) and calculated fire risk by analyzing the clustering of fire cases and facilities in Jinju-si based on the current DB of facilities, offered by the Ministry of Government Administration and Home Affairs. As a result, the risk ratings of fire occurrence were classified as four stages under the standards of the US Society of Fire Protection Engineers(SEPE). Business facilities, entertainment facilities, and automobile facilities were classified as the highest A grade, detached houses, Apartment houses, education facilities, sales facilities, accommodation, set of facilities, medical facilities, industrial facilities, and life service facilities were classified as U grade, and other facilities were classified as EU grade. Finally, hazardous production facilities were classified as BEU grade, the lowest grade. In addition, in the case of setting the standard with loss of life, the highest risk facility was the hazardous production facilities, while in the case of setting the standard with property damage, a set of facilities and industrial facilities showed the highest risk. In this regard, this study is expected to be effectively utilized to establish the fire reduction measures against facilities, distributed in urban space by calculating risk grades regarding the generation frequency, casualties, and property damage, through the classification of fire, occurred in the city, according to the facilities.

• Korean Journal of Remote Sensing
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• v.32 no.2
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• pp.119-131
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• 2016

Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.121-135
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• 2014

Object-based classification methods provide a valid alternative to traditional pixel-based methods. This study reports the results of an object-based classification to examine land cover in the demilitarized zones(DMZs) of Inje-gun. We used land cover classes(7 classes for main category and 13 classes for sub-category) selected from the criteria by Korea Ministry of Environment. The average and standard deviation of the spectrum values, and homogeneity of GLCM were chosen to map land cover types in an hierarchical approach using the nearest neighborhood method. We then identified the distributional characteristics of land cover by considering 3 topographic characteristics (altitude, slope gradient, distance from the Southern Limited Line(SLL)) within the DMZs. The results showed that scale 72, shape 0.2, color 0.8, compactness 0.5 and smoothness 0.5 were the optimum weight values while scale, shape and color were most influenced parameters in image segmentation. The forests (92%) were main land cover type in the DMZs; the grassland(5%), the urban area (2%) and the forests (broadleaf forest: 44%, mixed forest: 42%, coniferous forest: 6%) also occupied mostly in land cover classes for sub-category. The results also showed that facilities and roads had higher density within 2 km from the SLL, while paddy, field and bare land were distributed largely outside 6 km from the SLL. In addition, there was apparent distinction in land cover by topographic characteristics. The forest had higher density at above altitude 600m and above slope gradient $30^{\circ}$ while agriculture, bare land and grass land were distributed mainly at below altitude 600m and below slope gradient $30^{\circ}$.

• Korean Journal of Remote Sensing
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• v.33 no.6_2
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• pp.1089-1100
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• 2017

This paper presented a method using past land cover maps in image segmentation and training set collection for updating land cover maps. In this method, the object boundaries in past land cover maps were used for segmenting image clearly. Also, the classes of past land cover maps were used to extract additional informative training set from the initial classification result using a small number of initial training set. To evaluate the applicability of proposed method, a case study for updating land cover maps was carried out using middle-level land cover maps and WorldView-2 image in the Taean-gun, South Korea. As a result of the case study, the confusions between urban and barren, paddy/dry field and grassland in the initial classification result were reduced by adding training set. In addition, the object segmentation using boundaries of past land cover map cleared land cover boundaries and improved classification accuracy. Based on the result of case study, the proposed method using past land cover maps is expected to be useful for updating land cover maps.

• Journal of Korean Society of Rural Planning
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• v.18 no.4
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• pp.13-26
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• 2012

The purpose of this study is to select the study area, which will be formed into Daegu Science Park as an national industrial complex, and to assess the landscape value based on biotop classification with different polygon forms, and to develop and computerize Biotop Value Assessment Tool (B-VAT) based on GIS. The result is as follows. First, according to the result of biotop classification based on an advanced analysis on preliminary data, a field study, and a literature review, total 13 biotop groups such as forrest biotop groups and total 63 biotop types were classified. Second, based on the advanced research on landscape value assessment model of biotop, we development biotop value assessment tool by using visual basic programming language on the ArcGIS. The first application result with B-VAT showed that the first grade was classified into 19 types including riverside forest(BE), the second grade 12 types including artificial plantation(ED), and the third class, the fourth grade, and the fifth grade 12 types, 2 types, and 18 types respectively. Also, according to the second evaluation result with above results, we divided a total number of 31 areas and 34 areas, which had special meaning for landscape conservation(1a, 1b) and which had meaning for landscape conservation(2a, 2b, 2c). As such, biotop type classification and an landscape value evaluation, both of which were suggested from the result of the study, will help to scientifically understand a landscape value for a target land before undertaking reckless development. And it will serve to provide important preliminary data aimed to overcome damaged landscape due to developed and to manage a landscape planning in the future. In particular, we expect that B-VAT based on GIS will help overcome the limitations of applicability for of current value evaluation models, which are based on complicated algorithms, and will be a great contribution to an increase in convenience and popularity. In addition, this will save time and improve the accuracy for hand-counting. However, this study limited to aesthetic-visual part in biotop assessment. Therefore, it is certain that in the future research comprehensive assessment should be conducted with conservation and recreation view.

• The Journal of Industrial Distribution & Business
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• v.11 no.7
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• pp.29-40
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• 2020

Purpose: In modern society, many urban problems are occurring, such as aging, hollowing out old city centers and polarization within cities. In this study, we intend to apply big data and machine learning methodologies to predict depression symptoms in the elderly population early on, thus contributing to solving the problem of elderly depression. Research design, data and methodology: Machine learning techniques used random forest and analyzed the correlation between CES-D10 and other variables, which are widely used worldwide, to estimate important variables. Dependent variables were set up as two variables that distinguish normal/depression from moderate/severe depression, and a total of 106 independent variables were included, including subjective health conditions, cognitive abilities, and daily life quality surveys, as well as the objective characteristics of the elderly as well as the subjective health, health, employment, household background, income, consumption, assets, subjective expectations, and quality of life surveys. Results: Studies have shown that satisfaction with residential areas and quality of life and cognitive ability scores have important effects in classifying elderly depression, satisfaction with living quality and economic conditions, and number of outpatient care in living areas and clinics have been important variables. In addition, the results of a random forest performance evaluation, the accuracy of classification model that classify whether elderly depression or not was 86.3%, the sensitivity 79.5%, and the specificity 93.3%. And the accuracy of classification model the degree of elderly depression was 86.1%, sensitivity 93.9% and specificity 74.7%. Conclusions: In this study, the important variables of the estimated predictive model were identified using the random forest technique and the study was conducted with a focus on the predictive performance itself. Although there are limitations in research, such as the lack of clear criteria for the classification of depression levels and the failure to reflect variables other than KLoSA data, it is expected that if additional variables are secured in the future and high-performance predictive models are estimated and utilized through various machine learning techniques, it will be able to consider ways to improve the quality of life of senior citizens through early detection of depression and thus help them make public policy decisions.