• Title/Summary/Keyword: Value of Floor-Area-Ratio

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Deducing environmentally conscious factors for apartment complex planning and weight evaluation (환경요소를 고려한 공동주택 단지계획요소 도출 및 가중치 평가)

  • Jung, Suk-Jin;Seo, Jung-Bum;Yoon, Seong-Hwan
    • KIEAE Journal
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    • v.16 no.6
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    • pp.51-56
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    • 2016
  • Purpose: As declines in the quality of residential environments occur, such as urban heat island effect, tropical night phenomenon, and violations of right to light and privacy due to urban densification and high rise building, these problems are emerging as social issues. In order to improve these issues, design factors which consider environmental aspects must be selected when planning apartment complexes, and ways to reflect them in the planning phase must be explored. Method: In this study, the analytical hierarchy process(AHP) was used to deduce design factors that considered environmental elements during the planning of apartment complexes. Furthermore, the priority and weight for each evaluation index were assessed. The objective was to propose a guideline for planning apartment complexes by finding the best solution for each evaluation index using complex weight values. Result: Floor area ratio was selected as the most important evaluation criterion in the environmentally conscious evaluation index for apartment complex planning. The shape and placement of skylights were selected as the most important evaluation criteria in the sunshine environment for a pleasant residential environment. Ground surface cover design was selected as the most important criterion in the outdoor thermal environment index for improving the microclimate within cities and apartment complexes. Thus, the results of this study can serve as an investigation guideline that concerns policy and regulations, and as reference data that can be used in planning apartment complexes.

Estimation of the Value of Road Traffic Noise within Apartment Housing Prices (아파트가격에 내재된 도로교통소음가치 추정)

  • 임영태;손의영
    • Journal of Korean Society of Transportation
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    • v.19 no.4
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    • pp.19-33
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    • 2001
  • In the developed countries, traffic noise is one of most serious problems faced by people's lives. So the importance of the traffic noise is quite well recognized by the infrastructure planners as well as the people. The traffic noise is valued in monetary terms in some countries and it is reflected in estimating the net present value or benefit/cost ratio. On the contrary, the effects of traffic noise are not reflected in the assessment of infrastructure in most cases in Korea. However, as the income level has been increasing, more people have been becoming to put more importance on their living conditions. The purpose of this paper is to estimate the value of traffic noise in the Seoul metropolitan area. The housing price were surveyed to use the quasi-hedonic price technique. By this way, two housing prices at the same floor level in different 128 complexes in the Seoul metropolitan area were surveyed. the actual traffic noise level was also measured. The differences of housing prices and noise levels were analyzed using the various types of regression models. The value is quite different by size of house. The value of large house is higher than that of small house. Since the income level of people in large house is higher than that in small house. it might be said that value of traffic noise for high income people is higher than that for low income people. Moreover, the increase of 1dB(A) noise affects the house price by about 0.3% in Seoul metropolitan area.

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Predicting Crime Risky Area Using Machine Learning (머신러닝기반 범죄발생 위험지역 예측)

  • HEO, Sun-Young;KIM, Ju-Young;MOON, Tae-Heon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.4
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    • pp.64-80
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    • 2018
  • In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

Crime Incident Prediction Model based on Bayesian Probability (베이지안 확률 기반 범죄위험지역 예측 모델 개발)

  • HEO, Sun-Young;KIM, Ju-Young;MOON, Tae-Heon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.4
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    • pp.89-101
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    • 2017
  • Crime occurs differently based on not only place locations and building uses but also the characteristics of the people who use the place and the spatial structures of the buildings and locations. Therefore, if spatial big data, which contain spatial and regional properties, can be utilized, proper crime prevention measures can be enacted. Recently, with the advent of big data and the revolutionary intelligent information era, predictive policing has emerged as a new paradigm for police activities. Based on 7420 actual crime incidents occurring over three years in a typical provincial city, "J city," this study identified the areas in which crimes occurred and predicted risky areas. Spatial regression analysis was performed using spatial big data about only physical and environmental variables. Based on the results, using the street width, average number of building floors, building coverage ratio, the type of use of the first floor (Type II neighborhood living facility, commercial facility, pleasure use, or residential use), this study established a Crime Incident Prediction Model (CIPM) based on Bayesian probability theory. As a result, it was found that the model was suitable for crime prediction because the overlap analysis with the actual crime areas and the receiver operating characteristic curve (Roc curve), which evaluated the accuracy of the model, showed an area under the curve (AUC) value of 0.8. It was also found that a block where the commercial and entertainment facilities were concentrated, a block where the number of building floors is high, and a block where the commercial, entertainment, residential facilities are mixed are high-risk areas. This study provides a meaningful step forward to the development of a crime prediction model, unlike previous studies that explored the spatial distribution of crime and the factors influencing crime occurrence.

Characteristic on the Layout and Semantic Interpretation of Chungryu-Gugok, Dongaksan Mountain, Gokseong (곡성 동악산 청류구곡(淸流九曲)의 형태 및 의미론적 특성)

  • Rho, Jae-Hyun;Shin, Sang-Sup;Huh, Joon;Lee, Jung-Han;Han, Sang-Yub
    • Journal of the Korean Institute of Traditional Landscape Architecture
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    • v.32 no.4
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    • pp.24-36
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    • 2014
  • The result of the research conducted for the purpose of investigating the semantic value and the layout of the Cheongryu Gugok of Dorimsa Valley, which exhibits a high level of completeness and scenic preservation value among the three gugoks distributed in the area around Mt. Dongak of Gogseong is as follows.4) The area around Cheongryu Gugok shows a case where the gugok culture, which has been enjoyed as a model of the Neo-Confucianism culture and bedrock scenery, such as waterfall, riverside, pond, and flatland, following the beautiful valley, has been actually substituted, and is an outstanding scenery site as stated in a local map of Gokseong-hyeon in 1872 as "Samnam Jeil Amban Gyeryu Cheongryu-dong(三南第一巖盤溪流 淸流洞: Cheongryu-dong, the best rock mooring in the Samnam area)." Cheongryu Gugok, which is differentiated through the seasonal scenery and epigrams established on both land route and waterway, was probably established by the lead of Sun-tae Jeong(丁舜泰, ?~1916) and Byeong-sun Cho(曺秉順, 1876~1921) before 1916 during the Japanese colonization period. However, based on the fact that a number of Janggugiso of ancient sages, such as political activists, Buddhist leaders, and Neo-Confucian scholars, have been established, it is presumed to have been utilized as a hermit site and scenery site visited by masters from long ago. Cheongryu Gugok, which is formed on the rock floor of the bed rock of Dorimsa Valley, is formed in a total length of 1.2km and average gok(曲) length of 149m on a mountain type stream, which appears to be shorter compared to other gugoks in Korea. The rock writings of the three gugoks in Mt. Dongak, such as Cheongryu Gugok, which was the only one verified in the Jeonnam area, total 165 in number, which is determined to be the assembly place for the highest number of rock writings in the nation. In particular, a result of analyzing the rock writings in Cheongryu Gugok totaling 112 places showed 49pieces(43.8%) with the meaning of 'moral training' in epigram, 21pieces (18.8%) of human life, 16pieces(14.2%) of seasonal scenery, and 12pieces(10.6%) of Janggugiso such as Jangguchur, and the ratio occupied by poem verses appeared to be six cases(3.6%). Sweyeonmun(鎖烟門), which was the first gok of land route, and Jesiinganbyeolyucheon(除是人間別有天) which was the ninth gok of the waterway, corresponds to the Hongdanyeonse(虹斷烟鎖) of the first gok and Jesiinganbyeolyucheon of the ninth gok established in Jaecheon, Chungbuk by Se-hwa Park(朴世和, 1834~1910), which is inferred to be the name of Gugok having the same origin. In addition, the Daeeunbyeong(大隱屛) of the sixth gok. of land route corresponds to the Chu Hsi's Wuyi-Gugok of the seventh gok, which is acknowledged as the basis for Gugok Wollim, and the rock writings and stonework of 'Amseojae(巖棲齋)' and 'Pogyeongjae(抱經齋)' between the seventh gok and eighth gok is a trace comparable with Wuyi Jeongsa(武夷精舍) placed below Wuyi Gugok Eunbyeon-bong, which is understood to be the activity base of Cheongryu-dong of the Giho Sarim(畿湖士林). The rock writings in the Mt. Dongak area, including famous sayings by masters such as Sunsaeuhje(鮮史御帝, Emperor Gojong), Bogahyowoo(保家孝友, Emperor Gojong), Manchunmungywol(萬川明月, King Joengjo), Biryeobudong(非禮不動, Chongzhen Emperor of the Ming Dynasty)', Samusa(思無邪, Euijong of the Ming Dynasty), Baksechungpwoong(百世淸風, Chu Hsi), and Chungryususuk-Dongakpungkyung(淸流水石 動樂風景, Heungseon Daewongun) can be said to be a repository of semantic symbolic cultural scenery, instead of only expressing Confucian aesthetics. In addition, Cheongryu Gugok is noticeable with its feature as a cluster of cultural scenery of the three religions of Confucian-Buddhism-Taoism, where the Confucianism value system, Buddhist concept, and Taoist concept co-exists for mind training and cultivation. Cheongryu Gugok has a semantic feature and spatial character as a basis for history and cultural struggle for the Anti-Japan spirit that has been conceived during the process of establishing and utilizing the spirit of the learning, loyalty for the Emperor and expulsion of barbarians, and inspiration of Anti-Japan force, by inheriting the sense of Dotong(道統) of Neo-Confucianism by the Confucian scholar class at the end of the Joseon era that is represented by Ik-hyun Choi(崔益鉉, 1833~1906), Woo Jeon(田愚, 1841~1922), Woo-man Gi(奇宇萬, 1846~1916), Byung-sun Song(宋秉璿, 1836~1905), and Hyeon Hwang(黃玹, 1855~1910).