• 농촌계획
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• 제13권3호
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• pp.103-110
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• 2007

Land development policy in Korea, characterized by its supply-oriented policy, has driven rapid economic development. However, it has a negative impact on the natural environment across the country. Especially, as the introduction of quashi-farmland system with the deregulation of agricultural land development in the late 1990s, numerous unfavorable landscape features such as road, motels and apartment have emerged in the rural area. As those interfered irreversible rural landscapes have been expanded, the demand for well preserved rural landscapes have been increased. The objectives of this study, thus, is to suggest the mitigations between the land development and conservation of natural landscape. As such, this study examines the recognition of current rural landscape management status through 118 students with two groups of landscape architecture majored (50 people) and non-landscape majored (68). Both group express the negative impression of current rural landscape management system in general and they pointed out the major landscape problems are caused from inappropriate land use. However, in detail those two groups respond differently, for example, the first group selected the damaged landscape is the second cause of the landscape problem, while the other group selected the poorly maintained settlements. Based on the analysis of the survey, this study suggests 3 recommendations in order to improve the sustainable rural landscape as establishing the proper rural land use planning system, building local governments' capacity to actively participate in the rural landscape management, and preparing the landscape management plans considering area distinctive characteristics.

• 한국인공지능학회지
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• 제10권1호
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• pp.27-32
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• 2022

As the need for eco-friendly transportation increases due to the deepening climate crisis, many local governments in Korea are introducing shared bicycles. Due to anxiety about public transportation after COVID-19, bicycles have firmly established themselves as the axis of daily transportation. The use of shared bicycles is spread, and the demand for bicycles is increasing by rental offices, but there are operational and management difficulties because the demand is managed under a limited budget. And unfortunately, user behavior results in a spatial imbalance of the bike inventory over time. So, in order to easily operate the maintenance of shared bicycles in Seoul, bicycles should be prepared in large quantities at a time of high demand and withdrawn at a low time. Therefore, in this study, by using machine learning, the linear regression algorithm and MS Azure ML are used to predict and analyze when demand is high. As a result of the analysis, the demand for bicycles in 2018 is on the rise compared to 2017, and the demand is lower in winter than in spring, summer, and fall. It can be judged that this linear regression-based prediction can reduce maintenance and management costs in a shared society and increase user convenience. In a further study, we will focus on shared bike routes by using GPS tracking systems. Through the data found, the route used by most people will be analyzed to derive the optimal route when installing a bicycle-only road.

• 환경위생공학
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• 제18권3호통권49호
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• pp.11-20
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• 2003

There are two ways of reducing air pollution. One is the approach of the pollutant source control and the other one is the traffic demand decreasing approach. This study is focusing on the approach of land use planning and optimal location of urban facilities because those are the basic cause to generate transportation demands. So, the purpose of this study would be to analyze the changes of NOx and CO distribution on environmental air by functional hierarchy of urban roads and to make evaluation model of 'Transportation-Land Use -Air Pollution'. It will contribute to improve the air pollution level at same actual traffic generation according to different location.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2004년도 추계학술발표회 논문집
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• pp.343-347
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• 2004

Landuse information is used to plan land use, urban and environmental management as base data. And, demand for landuse information is rising due to ecological consideration in urban area. But existing method to extract landuse information from aerial photographs or satellite images is difficulte to describe sufficient urban landuses. Also landuse information need to be linked with statistical data because statistical data is used to make decision for urban planning and management with landuse. Therefore this study aims to examine the landuse classification method using statistical unit data and 1:1,000 digital topographic data. for the purpose, the method was applied to a part of metropolitan Seoul. The results of study shows that total accuracy is 95%. For the future, the method will be effectively applicable for the city maintenance.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.266-268
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• 2003

This is based on the AGENT-LUC model framework. Luangprabang Province has the largest percentage of shifting cultivation area in Laos PDR. The model simulates the spatial and temporal patterns of the shifting cultivation in the study area, using a GIS database while the total area of shifting cultivation is controlled by supply and demand balance of food. The model simulation period is from 1990 to 1999, at a spatial resolution of 500m. The results are evaluated using statistical data and remote sensing images. Through the validation, it is concluded that the trends simulated agrees to that of statistical data and the spatial and temporal patterns are also replicated satisfactorily.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 A
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• pp.77-79
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• 2003

New cities and industrial complexes are being developed actively because of the government policies aiming population distribution and vitalization of construction industry. To determine the investment amount, number of power lines and substations for stable power supply to newly developed residential and industrial complexes, accurate estimation of power demand is necessary. This paper propose standards for the estimation of power demands for power company and construction company to settle the debates surrounding this issue. Through a survey and analysis of existing areas, new standards that will enable more accurate estimation of power demands in new cities complexes to be developed in the future are established by calculating the average load density, load factor, utilization factor by area, use and building size after dividing the facilities into building type and the areas into the areas planned to be developed and the areas not yet planned to be developed.

• 대한교통학회지
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• 제32권2호
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• pp.130-138
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• 2014

이 연구는 대중교통전용지구의 조성목적에 따른 계획요소별 중요도 평가에 관한 것이다. 대중교통전용지구의 조성목적은 교통수요관리형과 지역활성화추진형으로 구분하였다. 이를 바탕으로 계획요소를 토지이용, 도시설계, 교통, 사회문화 특성으로 분류하고 이를 4As(Attraction, Amenity, Accessibility, Activity)라 명명하였다. AHP(Analytical Hierarchy Process) 기법을 통해 각 조성목적별로 계획요소의 중요도를 평가한 결과, 교통수요관리형은 교통(52.7%), 토지이용(25.6%), 도시설계(13.7%), 사회문화(8.0%) 순으로, 지역활성화추진형은 토지이용(36.1%), 교통(30.6%), 도시 설계(17.7%), 사회문화(15.6%) 순으로 도출되었다. 또한, 조성목적별로 세부계획요소의 중요도에서도 차이가 나타났다. 이러한 결과는 대중교통전용지구의 조성목적을 구분할 필요가 있음을 뒷받침하며, 다양한 계획요소의 반영을 위해서는 교통부문 단독계획이 아닌 타 계획과의 연계가 필수적임을 시사한다. 또한 승용차 접근성이 배제요인이 아닌 선택요인이라는 것과 사회문화적 특성에 대한 고려도 필요함을 확인하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.156-156
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• 2022

Explicitly spatially distributed and reliable data on industrial water demand is very much important for both policy makers and researchers in order to carry a region-specific analysis of water resources management. However, such type of data remains scarce particularly in underdeveloped and developing countries. Current research is limited in using different spatially available socio-economic, climate data and geographical data from different sources in accordance to predict industrial water demand at finer resolution. This study proposes a random forest regression (RFR) model to predict the industrial water demand at 0.50× 0.50 spatial resolution by combining various features extracted from multiple data sources. The dataset used here include National Polar-orbiting Partnership (NPP)/Visible Infrared Imaging Radiometer Suite (VIIRS) night-time light (NTL), Global Power Plant database, AQUASTAT country-wise industrial water use data, Elevation data, Gross Domestic Product (GDP), Road density, Crop land, Population, Precipitation, Temperature, and Aridity. Compared with traditional regression algorithms, RF shows the advantages of high prediction accuracy, not requiring assumptions of a prior probability distribution, and the capacity to analyses variable importance. The final RF model was fitted using the parameter settings of ntree = 300 and mtry = 2. As a result, determinate coefficients value of 0.547 is achieved. The variable importance of the independent variables e.g. night light data, elevation data, GDP and population data used in the training purpose of RF model plays the major role in predicting the industrial water demand.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.1890-1901
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• 2007

This paper explored train frequency of intercity rail station. Main factors to decide train frequency are location of station, social-economic index and land use of station area and travel demand. In this paper, we focused on travel demand which is critical factor to decide train frequency. Tests on a KTX case show that train frequency can be efficiently decreased in weekday to transport same demand. The work has shown many subjects that need further research. It is important to include various factors influencing on train frequency decision.

• 한국물환경학회지
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• 제39권2호
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• pp.162-174
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• 2023

In order to prevent water pollution caused by organic matter, Total Organic Carbon(TOC) has been adopted indicator and monitored. TOC can be divided into Dissolved Organic Carbon(DOC) and Particulate Organic Carbon(POC). POC is largely precipitated and removed during stream flow, which making DOC environmentally significant. However, there are lack of studies to define spatio-temporal distributions of DOC in stream affected by various land use. Therefore, it is necessary to estimate the past DOC concentration using other water quality indicators to evaluate status of watershed management. In this study, DOC was estimated by correlation and regression analysis using three different organic matter indicators monitored in mixed land-use watersheds. The results of correlation analysis showed that DOC has the highest correlation with TOC. Based on the results of the correlation analysis, the single- and multiple-regression models were developed using Biochemical Oxygen Demand(BOD), Chemical Oxygen Demand(COD), and TOC. The results of the prediction accuracy for three different regression models showed that the single-regression model with TOC was better than those of the other multiple-regression models. The trend analysis using extended average concentration DOC data shows that DOC tends to decrease reflecting watershed management. This study could contribute to assessment and management of organic water pollution in mixed land-use watershed by suggesting methods for assessment of unmeasured DOC concentration.