• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.252-252
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• 2020

대하천 주변 광역상수도 공급지역은 가뭄 발생시에도 안정적으로 물이용이 가능하나, 중소하천을 수원으로 하는 하천의 상류지역은 가뭄시 물공급 안정성이 취약하다. 따라서 중소하천을 대상으로 가뭄시 물 공급시설의 효율적 운영, 물부족 위험도 평가, 가용 수자원의 최적이용 등 종합적인 대책 마련을 위해서는 신뢰성 높은 수문량(하천유출량 및 수자원가용량) 예측이 필요하다. 기존의 가뭄시 하천유출량 예측정확도 평가는 통계적 회귀분석을 통한 가뭄지수 기반의 가뭄상황의 예측에 치중하여 불확실성이 크며 국내 유역의 복잡한 물이용체계를 고려하지 않아 시·공간적인 규모에 따라 상이한 결과를 나타내며 실측자료 기반의 하천유출량과 비교하면 정확도가 대부분 60% 이하로 나타난다(이상은 등, 2015). 본 연구에서는 상세 물이용체계를 고려한 정도높은 수자원가용량의 평가를 위하여 한강권역 내의 한탄강댐 상류 유역을 테스트베드로 선정하였다. 한탄강댐 상류유역은 다수의 복잡한 농업용 수리시설 운영에 따른 수자원가용량 예측정확도가 매우 낮은 지역으로 본 연구를 통해 정도 높은 수자원가용량 예측정확도를 확보하기에 적정한 유역이라 판단하였다. 수자원가용량을 평가하기 위한 모형은 한국건설기술연구원에서 개발된 CAT3.1(Catchment hydrologic cycle Assessment Tool 3.1)을 이용하였다. CAT 3.1은 중소하천 유역내의 인위적인 물이용체계(광역급수, 재이용, 지하수 취수, 하천수 취·배수 등)를 반영한 수문량(하천유출량 및 수자원가용량) 평가 및 예측이 가능한 모형으로 기존 개념적 매개변수 기반의 집중형 수문모형과 물리적 매개변수 기반의 분포형 수문모형의 장점을 최대한 집약하여 개발되었다. 한탄강댐 상류유역의 물리적 매개변수는 최대한 기 구축된 GIS 자료를 활용하여 추출하였다. 토지이용현황은 산림과 농업지역이 대부분을 차지하여 농업용수 공급이 대부분인 물이용체계를 가지고 있다. 따라서 한국농어촌공사에서 관리하는 11개 농업용 저수지에 대한 취수현황 및 제원, 국가지하수센터의 유역내 지하수사용량, 하폐수처리량을 기본 입력 자료로 사용하였다. 특히 농업용 저수지의 경우에는 저수지출구점을 기준으로 저수지 상류유역 및 한국농어촌공사에서 기 구축된 관개면적 공간자료를 기본으로 수혜구역을 세분화하여 모형을 적용하였다.

• Journal of Korean Society for Geospatial Information Science
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• v.6 no.1 s.11
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• pp.35-51
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• 1998

This article aims at presenting a new framework for traffic accident analysis by proposing a new methodology for the management of the accident data and by establishing the relationship between accidents and roadway characteristics within it For the first issue, authors introduced geographic information system (GIS) into the analysis framework of the accident data since it is believed that analysis based on GIS seems to provide more effective information in reducing accidents. Point-based, line-based, and polygon (grid)-based approaches were set of along with concrete examples. Especially, the location-based scores such as localization, specialization coefficients, and Tress score have been added to identify the intensity of certain accident types within study area or grids. The second issue addressed the equation formulation of accident and fatality numbers with roadway characteristics like number of intersections and road length in a grid with a sense that (1) accidents on roadways are the function of the roadway physical characteristics rather than the socio-economical secondary data (2) the equation can be applied to the any 'suggested' area, not just region or nation, and (3) the accident forecasting model should emphasize the accident location itself more than any other factors. Some equations based on those assumption have been derived along with some future research agenda.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.4
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• pp.153-170
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• 2013

This study was conducted to analyze the thermal comfort in the urban neighborhood park and to obtain a plan for improvement of the thermal environment. First, in the result of the analysis of the distribution characteristics of the park's main thermal environment factors and differences among types of space, temperature, relative humidity, and wind speed did not show a clear difference spatially. However, the median radiant temperature showed great differences according to the openness of the space and the covering material. According to the evaluation of thermal comfort by types of space based on derived thermal environmental factors, the PMV value of the square was the highest at 4.39, the paths showed 2.58, greenery 1.90, and resting spaces 0.42. In the result of the PMV regression model established for the evaluation of the significance of these thermal environment factors that decide thermal comfort, it showed that the relative significance to the PMV was as follows in decreasing order: median radiant temperature(1.084), wind speed(-0.280), temperature(0.013), and relative humidity(-0.009). When conducting a scenario analysis on the areas with need for improvement in thermal environment, it was found that through reflectivity, color and the change in the physical properties of packing materials the thermal comfort felt by the body could be improved, and it is believed that through this the improvement plan can be established.

• Journal of the Korean Regional Science Association
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• v.36 no.4
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• pp.3-23
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• 2020

This study aims to conceptualize the settlement inclusivity for overcoming social exclusion and the decline in quality of life of older people and to examine its effects on their mental health. The concept of the settlement inclusivity for older people focuses on the immediate environment around the place where they live. We proposed two domains for the conceptual framework; social domain that provides opportunities for community cohesion; spatial domain that provides security of residential area and access to basic services within walking distance. The social domain was represented by participation and interdependence, while the spatial domain by security and accessibility in the settlement inclusivity. Zero-inflated negative binomial regression model was constructed with 2017 National Survey of Older Koreans data to analyze the factors influencing depressive symptoms of older adults. The empirical results demonstrate that increased level of neighborhood network and social participation is associated with a decrease in the number of depressive symptoms. In addition, higher satisfaction in neighborhood environment and good accessibility to public transport/stores are associated with fewer depressive symptoms. Finally, housing condition and home ownership have a moderating effect on the relationship between social network/participation and depressive symptoms level, whereas they have no direct effects on depressive symptoms. This study demonstrates multi-dimensionally and mutually significant associations between settlement inclusivity and depressive symptoms for older people providing implications for urban planning and policies to improve mental well-being of older population.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.1
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• pp.35-49
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• 2014

In order to understand the impacts of surface characteristics and the distance from the urban heat island center to suburban areas on the mean night time air temperature, we analyzed GIS and AWS observational data. Spatial distributions of mean night time air temperature during the summer and winter periods of 2004-2011(six years) were utilized. Results show that the temperature gradients were different by distance and direction. We found high correlation between mean night-time air temperature and artificial land cover area within 1km and 200m radii during both summer(R=0.84) and winter(R=0.78) seasons. Regression models either from 1km and 200m land surface data explained the distribution of night-time temperature equally well if the input data had sufficient resolution with detailed attribute including building area and height.

• Journal of the Korean earth science society
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• v.40 no.6
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• pp.599-605
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• 2019

Rice yield (kg 10a^-1) in South Korea was estimated by meteorological variables that are influential factors in crop growth. This study investigated the possibility of anticipating the rice yield variability using a simple but an efficient statistical method, a multiple linear regression analysis, on the basis of the annual variation of meteorological variables. Due to heterogeneous environmental conditions by region, the yearly rice yield was assessed and validated for each province in South Korea. The monthly mean meteorological data for the period 1986-2018 (33 years) from 61 weather stations provided by Korean Meteorological Administration was used as the independent variable in the regression analysis. An 11-fold (leave-three-out) cross-validation was performed to check the accuracy of this method estimating rice yield at each province. This result demonstrated that temporal variation of rice yield by province in South Korea can be properly estimated using such concise procedure in terms of correlation coefficient (0.7, not significant). Furthermore, the estimated rice yield well captured spatial features of observation with mean bias of 0.7 kg 10a^-1 (0.15%). This method may offer useful information on rice yield by province in advance as long as accurate agro-meteorological forecasts are timely obtained from climate models.

• Land and Housing Review
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• v.13 no.2
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• pp.65-79
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• 2022

To suggest implications of future housing problems, this study investigates which characteristics affect the housing satisfaction of young single households. Using the survey data, we perform the multiple regression and decision tree models based on the SPSS Statistics 25.0. Our empirical results show several key features. First, housing characteristics and intention to continue single households had a positive (+) effect on housing satisfaction, in the order of natural, housing, physical characteristics, and intention to continue single households. Second, housing characteristics and intention to marry in the future had a positive (+) effect on housing satisfaction in the order of natural, housing, and physical characteristics. Third, housing characteristics and intention to increase household members in the future had a positive (+) effect on housing satisfaction, in the order of natural, housing, and physical characteristics satisfaction. Finally, the results of the decision tree model show that the natural characteristics were over 3.4, and housing satisfaction was the highest in the case of Jeonse. The results of this study provide three implications for policymakers. First, improving the residential environment of young single households is important. Second, providing customized housing for young single households could enhance the housing satisfaction of young people. Finally, housing provision needs to be carried out with suitable space for the lifestyle of young single households.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2004.11a
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• pp.249-258
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• 2004

오늘날 활발하게 이루어지고 있는 유비쿼터스 컴퓨팅 관련 기술 연구는 사용자가 시간과 장소에 구애받지 않고 네트워크에 접근해 다양한 컴퓨터 관련 서비스를 제공 받을 수 있는 방법에 초점을 맞추고 있다. 이 처럼 시간과 공간의 한계를 뛰어 넘은 네트워크로의 자유로운 접근은 일상 생활의 패러다임을 바꾸어 놓게 될 것이다. 유비쿼터스 컴퓨팅 기술을 통해 가장 큰 변화가 일어나는 분야는 일반 가정환경에서 일어나는 인텔리전트 홈 네트워크 (Intelligent Home Network) 라고 할 수 있다. 집에 들어오면, 자동으로 문을 열어주고, 불을 켜주며, 놓쳤던 TV 프로그램을 자동으로 녹화해 놓았다가 원하는 시간에 보여주고, 적당한 시간에 목욕물을 미리 받아준다. 또한 집밖으로 나가기 전, 일기예보에 따라 우산을 챙겨주고, 일정을 확인시켜주며 입고 나갈 옷을 골라줄 수도 있다. 이 모든 일들이 유비쿼터스 컴퓨팅 기술이 가져올 인텔리전트 홈 네트워크의 모습이다. 그러나, 모든 사용자에게 효과적인 서비스를 제공하기 위해서는 홈 네트워크 상의 자원 관리에서 일어날 수 있는 에이전트들간의 자원 접근 권한 충돌을 효율적으로 방지할 수 있는 기술이 필요하다. 유비쿼터스 컴퓨팅 환경에서 자원관리 특성은 점유의 연속성, 자원 사이의 연관성, 그리고 자원과 사용자 사 사이의 연계성의 3 가지 특성을 지니고 있다. 본 논문에서는 유비쿼터스 컴퓨팅 환경에서 일어날 수 있는 자원 충돌 상황을 효율적으로 처리하기 위한 자원 협상 방법을 제안한다. 본 방법은 자원 관리 특성을 바탕으로 시간논리에 기반을 둔 자원 선점과 분배 규칙으로 구성된다.트 시스템은 b-Cart를 기반으로 할 것으로 예측할 수 있다.타났다. 또한, 스네이크의 초기 제어점을 얼굴은 44개, 눈은 16개, 입은 24개로 지정하여 MER추출에 성공한 영상에 대해 스네이크 알고리즘을 수행한 결과, 추출된 영역의 오차율은 각각 2.2%, 2.6%, 2.5%로 나타났다.해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data b

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.237-254
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• 2020

Housing vacancies have become a major issue in urban areas, there have been many efforts to address this issue at the national and local levels. The purpose of this paper is to investigate the factors contributing to housing vacancies in old town Incheon in South Korea. In particular, the research focuses on examining the effects of multiple levels of factors on housing vacancies in a comprehensive way; the three levels of factors were identified with a literature review including housing (Level 1), Neighborhood (Level 2), and Region (Level 3). A multi-level logistic regression model was used to examine the relationship between 13 factors in three spatial levels and housing vacancies. As a result, the factors in all three levels were able to explain housing vacancies including site area and shape, proximity to major roads (Level 1), ratio of houses in designated urban renewal area and slope (Level 2), and ratio of the elderly living alone, land price, changes in land price and ratio of new houses (Level 3). These results show that the combination of the physical inferiority of the housing site and the neighborhood environment and the economic and social vulnerability of the region is likely to increases the number of vacant houses. This study also suggested that a multi-dimensional policy strategy is needed to solve the problem of housing vacancies, and urban policies, such as supplying new housing or urban renewal area designation, should be carefully implemented in a way not to create housing vacancies.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.211-231
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• 2022

This study attempted to identify the effects of macroeconomic variables such as the All Industry Production Index, Consumer Price Index, CD Interest Rate, and KOSPI on apartment lease prices divided into nationwide, Seoul, metropolitan, and region, and to present a methodological prediction model of apartment lease prices by region using Long Short Term Memory (LSTM). According to VAR analysis results, the nationwide apartment lease price index and consumer price index in Lag1 and 2 had a significant effect on the nationwide apartment lease price, and likewise, the Seoul apartment lease price index, the consumer price index, and the CD interest rate in Lag1 and 2 affect the apartment lease price in Seoul. In addition, it was confirmed that the wide-area apartment jeonse price index and the consumer price index had a significant effect on Lag1, and the local apartment jeonse price index and the consumer price index had a significant effect on Lag1. As a result of the establishment of the LSTM prediction model, the predictive power was the highest with RMSE 0.008, MAE 0.006, and R-Suared values of 0.999 for the local apartment lease price prediction model. In the future, it is expected that more meaningful results can be obtained by applying an advanced model based on deep learning, including major policy variables