• Journal of the Korean Geographical Society
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• v.35 no.5
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• pp.665-680
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• 2000

본 연구의 목적은 미국의 산타아나 강 상류 유역분지 내 잠재적 퇴적물 생산량의 공간적 분포 패턴을 고찰하는데 있다. 이를 위해 산타아나 강 상류지역을 42개의 하부 유역분지로 나눈 후에 각 유역분지에 퇴적물 생산량에 영향을 주는 지형 기복 요소, 면적-형태 요소, 지질 요소, 기후 요소와 관련하여 20개의 변수를 GIS를 이용하여 추출하였다. 이러한 20개의 변수들을 기초로 군집분석하여 42개 하부 유역분지들의 잠재적 퇴적물 생산량을 평가한 결과 4개 지역으로 구분되었다. 평가 결과 <발톤> 평기자 포함된 제2지역이 산타아나 강 상류 유역분지에서 가장 퇴적작용이 왕성한 지역으로 나타났다. 이 지역은 낮은 기복 및 고도와 미고화된 물질로 피복된 지역이 97%를 차지하고 있다. 잠재적 퇴적물 생산량이 가장 높은 지역은 제 2지역의 상류부에 분포하는 유역분지들(제 4지역)로서 높은 기복과 고도뿐만 아니라 침식 면적이 넒으며, 과거의 빙하작용이 있었던 지역이다. 특히 단층선이 퇴적작용이 크게 이루어지고 있는 지역(제2지역)과 잠재적 퇴적물 생산량이 가장 높은 지역(제4지역) 사이에 분포하고 있어, 사면경사의 급변으로 제 2 지역의 퇴적작용은 더욱 가속화 될 것이다.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.170-180
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• 2010

With development of the earth's subsurface space, the need for a reliable subsurface spatial model such as a cross-section, boring log is increasing. However, the ground mass was essentially uncertain. To generate model was uncertain because of the shortage of data and the absence of geotechnical interpretation standard(non-statistical uncertainty) as well as field environment variables(statistical uncertainty). Therefore, the current interpretation of the data and the generation of the model were accomplished by a highly trained experts. In this study, a geotechnical ontology model was developed using the current expert experience and knowledge, and the information content was calculated in the ontology hierarchy. After the relative distance between the information contents in the ontology model was combined with the distance between cluster centers, a cluster analysis that considered the geotechnical semantics was performed. In a comparative test of the proposed method, k-means method, and expert's interpretation, the proposed method is most similar to expert's interpretation, and can be 3D-GIS visualization through easily handling massive data. We expect that the proposed method is able to generate the more reasonable subsurface spatial information model without geotechnical experts' help.

• Environmental and Resource Economics Review
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• v.33 no.1
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• pp.59-86
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• 2024

Recently, research on city gas demand is increasing by reflecting the characteristics of each region. The similarity of the social structure of the adjacent region and the density of the supply infrastructure induce spatial correlation with the clustering that has a microscopic relationship between regions. Accordingly, as a result of analyzing the spatial correlation after dividing the demand for city gas for civilian use into a total of 54 regions based on the jurisdiction of 34 city gas companies, it was confirmed that there was a positive spatial correlation from a global and local perspective. In this study, the demand for city gas for civilian use for 54 regions from January 2014 to December 2022 was composed of panel data, and the spatial panel regression analysis and the general panel regression analysis were compared, and it was found that the spatial error model (SEM) was the most suitable model. This presents policy and practical implications by confirming that the demand for city gas for civilian use in one region has a significant relationship with the adjacent region.

• Journal of the Korean Geographical Society
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• v.30 no.2
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• pp.120-131
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• 1995

To analyze mobility patterns, this study used three Constraint (Capability Constraint, Coupling Constraint, Authority Constraint) models which were proposed in Dr. Hagerstrand's Time-space theory. This paper shows that three constraint models have some effects upon mobility by age. In this study, Capability Constraint means a certain special constraint that is what we can't do during proceeding basic natural urges like sleep, fare, etc. Coupling constraint is a physical one. Each person limits the action range for staying on a special place in special time. For instance, students have to stay in school so that they have mobility constraints. Authority Constraint is a social one. When we use urban facilities or traffic, we may be controlled by mobility sphere by an agreement or a social position. It is social agreement that the opening hour of a store, the time table of mass-transportation and a social positional control that the personal income, the standard of education. In this study it has been in a process of determination of the cluster number that degree of influences a social constraint to mobility. Considering the mobility constraint of characteristics of space divides urban and rural, people in urban area have higher mobility rate than in rural area. Resuets of determination of the cluster, show similar mobility pattern. People in urban area are connected verity of mobility which related to urban space structures with determination of cluste-number. That is to say, mobility patterns can be changed by space charactcristics. Constraints by sex and age are also social constraints and they are influenced by mobility patterns. For instance, females at the age of twenties have similar mobility pattern to the same age male but they have sudden changes after thirty's age. Male entertains a similar pattern without restriction of age. That is to say, management by sex as a social constraint affects mobility. To establish more realistic traffie policy, mobility formation should be reflected to the space in a view of social-behavioral science. To embody this, some problems should be investigated as follows. 1. As a problem of methodology, if sufficient samples ensured, we could subdivide clusters and could open up a new method of analyzing the mobility clusters by using the neuro-network. 2. Extracting actions connected with mobility and finding life cycle which is classified by daily cluste-characteristics, suitable counterproposal could be presented to the traific policy.

• Journal of Korean Society of Forest Science
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• v.99 no.3
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• pp.259-266
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• 2010

Forest fire occurrence in Korea is highly related to human activities and its spatial distribution shows a strong spatial dependency with cluster pattern. In this study, we analyzed spatial distribution pattern of forest fire with point pattern analysis considering spatial dependency. Distributional pattern was derived from Ripley's K-function according to causes and distances. Spatially clustered intensity was found out using Kernel intensity estimation. As a result, forest fires in Korea show clustered pattern, although the degrees of clustering for each cause are different. Furthermore, spatial clustering pattern can be classified into two groups in terms of degrees of clustering and distance. The first group shows the national-wide cluster pattern related to the human activity near forests, such as human-induced accidental fire in mountain and field incineration. Another group shows localized cluster pattern which is clustered within a short distance. It is associated with the smoker fire, arson, accidental by children. The range of localized clustering was 30 km. Beyond of this range, the patterns of forest fire became random distribution gradually. Kernel intensity analysis showed that the latter group, which have localized cluster pattern, was occurred in near Seoul with high densed population.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.4
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• pp.175-181
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• 2014

Korean government proposed a new initiative 'government 3.0' with which the administration will open its dataset to the public before requests. City of Seoul is the front runner in disclosure of government data. If we know what kind of attributes are governing factors for any given segmentation, these outcomes can be applied to real world problems of marketing and business strategy, and administrative decision makings. However, with respect to city of Seoul, selection of optimal variables from the open dataset up to several thousands of attributes would require a humongous amount of computation time because it might require a combinatorial optimization while maximizing dissimilarity measures between clusters. In this study, we acquired 718 attribute dataset from Statistics Korea and conducted an analysis to select the most suitable variables, which differentiate Gangnam from other districts, using the Genetic algorithm and Dunn's index. Also, we utilized the Microsoft Azure cloud computing system to speed up the process time. As the result, the optimal 28 variables were finally selected, and the validation result showed that those 28 variables effectively group the Gangnam from other districts using the Ward's minimum variance and K-means algorithm.

• Korean Journal of Plant Resources
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• v.33 no.1
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• pp.1-14
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• 2020

This study was conducted to analyze community structure and species composition of Pinus densiflora for. erecta Stand in Mt. Cheonchuk (653 m). Field survey was carried out from June to September in 2013. 74 plots (20×20 m) were set up, 5 herb layer plots (3×3 m) were constructed for each plot, and there, Diameter at Breast Heigh t(DBH), height, environmental factor, annual growth were measured. Vascular plants were surveyed as following; 66 family, 165 genus, 211 species, 2 sub species, 29 variety, 6 form 248 taxa. Results of cluster analysis for P. densiflora for. erecta forest, 3 communities were divided into; Quercus mongolica (P-1), Quercus variabilis (P-2) and Quercus aliena-Stephanandra incisa (P-3). There were significant environmental factors that organic layer, annual growth, CEC, total total nitrogen, organic matter and pH for each community. As a result of DCA, P-1 and P-2 were distributed large range of environmental factors but relatively limited in P-3. Distributions of herb layer were affected by sand, cation exchange capacity, silt and total nitrogen. Results of MRPP test for herb layer communities, it was significantly analyzed (A=0.003, P<0.008). Species diversity index was highly recorded in P-3 and influenced by cation exchange capacity, total nitrogen, annual growth in consequence of NMS analysis.

• Journal of the Economic Geographical Society of Korea
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• v.15 no.2
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• pp.292-303
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• 2012

The main purpose of this study is to analyze R&D networks and spatial implications in Qingdao consumer electronics industry agglomeration in China. The characteristics of R&D networks in Qindao consumer electronic industry are as follows. There is a cluster central around large enterprises led by the government and their subcontracting enterprises. However, the degree of collaborative networks in intra-firm, inter-firm, firm-research institutes(including university lab.) is relatively low. Therefore, Large enterprises in Qingdao has stimulated research collaborations with firms and research institutes located in other regions rather than within region. It is likely to show that R&D networks of consumer electronics industry has not been stimulated in Qingdao. Therefore, collaborative R&D networks among firms, research institutes and governments should be stimulated to build regional innovation systems central around consumer electronics industry in Qingdao.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.32-32
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• 2020

하나의 수계 또는 용수구역 내에서 작물생육기간 동안 지하수자원 수요량의 집중적인 증가로 인해 지역적 지하수 고갈이 발생하여 농작물 피해가 발생하고 있으며 과잉양수로 인한 지하수위 하강으로 사용자간 갈등도 빈번하다. 또한, 기후변화로 인해 극한기후인 가뭄의 잦은 발생은 이러한 현상을 가속화 한다. 지하수 산출성이 좋은 대수층의 공간적 분포는 복잡한 지질구조로 인해 균일하지 않으며 같은 대수층 내에서도 양수 위치에 따라 산출성은 다르게 나타난다. 이러한 지하수 수요와 공급 및 대수층 분포로 인한 지하수자원 불균형의 해소를 위해 지하수가 풍부한 지역에서 부족한 지역으로 지하수를 공급하는 방법을 적용할 수 있다. 이때 기술적용 지역의 지하수 사용 상황 및 공급 가능량을 정량적으로 평가하고 이를 기반으로 지하수 공급을 제어하는 것이 매우 중요하다. 지하수자원의 수요-공급 불균형이 발생할 때 즉각적으로 대응하기 위해서는 실시간으로 지하수 현황을 감시하고 이를 기반으로 공급 가능량을 산정할 필요가 있으며 이는 정보통신기술(Information and Communication Technology, ICT)에 기반한 관정연계관리체계(Well Network System, WNS)를 구성하는 기술 중 하나인 관정군집제어 기술로 구현될 수 있다. 수계 내에 설치된 기존의 양수정과 새롭게 추가된 관측정들을 4G LTE 네트워크를 통해 하나의 관정군으로 묶고 중앙 서버를 통한 자료 분석 및 양수 펌프 제어를 통해 대수층의 공급 능력과 사용자의 수요 현황에 따른 지하수자원의 체계적 분배를 구현하고자 하였다. 관정군집제어는 관정별 지하수위 및 양수정 양수량을 실시간으로 관측하고 이를 분석서버에 전송하여 해당 지하수계의 공급 가능량 및 인접관정 간섭 등을 분석하여 양수정의 펌프를 실시간으로 제어하고 양수된 지하수를 수요 지역으로 이송한다. 본 연구를 통해 관정군집제어 기술의 구현에 필요한 구성요소를 정의하고 이에 대한 구현 방법을 기술하여 WNS를 구성하는 하나의 요소기술 모델로 제시하고자 하였다.

• Land and Housing Review
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• v.14 no.2
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• pp.35-50
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• 2023

The purpose of this study is to identify areas in need of urban renewal by utilizing spatial data and analyzing their types and characteristics. For this, this research employed a kernel density function and K-means cluster analysis with spatial data, through which it sought ways to identify high-demand areas for urban renewal projects. The key findings and implications of the research are summarized as follows. Firstly, this research classified 587 target sites in Seoul based on development density (ratios) and an indicator for aged buildings. Approximately half of these areas were consistent with leading pilot project sites and Accelerated Integration Sites. Secondly, it was observed that residential environments in the designated leading pilot project sites, as decided by public sectors, were relatively poor compared to other areas. Lastly, the target areas for urban renewal were not clearly categorized through statistical analysis. Instead, it was found that categorization should be made depending on the requirements of each project.