• 대한공간정보학회지
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• 제24권2호
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• pp.63-70
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• 2016

A housing market in an urban area is not just a single market but a combination of regionally different submarkets. This study begins with a critical mind that previous researches did not consider the spatial autocorrelation of each area where the housings are located. The clustering analysis of housing submarket which considers spatial autocorrelation is performed as it follows. First, 4 housing market attribute variables are reducted to 1 variable by principle component analysis. Then, after calculating $Gi^*max$ by AMOEBA, 7 housing submarkets which have similar characteristics based on $Gi^*max$ are classified. The characteristics of each submarket are investigated, then political implication is deduced as the following. Different level of housing policy should be made to each cluster because each cluster has different level of spatial autocorrelation.

• 대한교통학회지
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• 제7권1호
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• pp.57-70
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• 1989

The purpose of study is to analyze the spatial population distribution and accessibility of network in urban areas. This study examines the forty-six political subdivision cities in Korea at the end of 1983, except the four metrpolitans (Seoul, Pusan, Daeku and Incheon). Evaluation indexes are classified the spatial pupulation distribution and accessibility of network. To analyze the cities, 10 indexes and the statistical techniques such as descriptive analysis, correlation analysis, factor analysis and cluster analysis were used. According to the results of cluster analysis, 15 cities (Ulsasn, Suwon, Bucheon, Chungju and etc.) are classified dispersed cities and another 15 cities (Kwangju, Daejun, Sungnam, Mokpo and etc.) are classified concentrated cities.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1141-1150
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• 2006

In this study, we performed spatial cluster analysis which considered spatial information using earthquake data for Korean peninsula occurred on 1978 year to 2005 year. Also, we look into how to be clustered for regions using earthquake magnitude and frequency based on spatial scan statistic. And, on the basis of the results, we constructed earthquake map by earthquake outbreak risk and gave a possible explanation for the results of spatial cluster analysis.

• 한국수자원학회논문집
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• 제57권2호
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• pp.87-97
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• 2024

본 연구에서는 국가물관리기본계획의 2030년 물부족량 전망자료를 이용하여 공간군집특성을 고려한 우리나라 물부족 핫스팟 지역을 분석하였다. 물부족 최심 군집지역 도출을 위하여 표준유역 기준의 과거 최대 가뭄(약 50년 빈도)에 대한 물부족량 자료를 이용하여, Local Moran's I와 Getis-Ord Gi* 통계량으로 공간군집분석을 수행하였다. 클러스터맵(Cluster Map)을 통해 물부족 공간군집 대상지역을 선정하고, 공간적 군집 특성은 p-값 및 모란 산점도를 통해 적정성을 검증하였다. 분석 결과, 한강권역 내 1개 군집[임진강하류(#1023) 및 주변]과 낙동강권역 내 2개 군집 [대종천(#2403) 및 주변, 가화천(#2501) 및 주변] 지역이 물부족이 심각한 핫스팟 지역으로 나타났으며, 한강권역 내 1개 군집[남한강하류 (#1007) 및 주변]과 낙동강권역 내 1개 군집[병성천(#2006) 및 주변] 지역이 물부족 HL (해당지역은 물부족량이 많고 주변지역은 물부족량이 적은) 지역으로 나타났다. 표준유역단위 공간군집분석을 수행할 경우 물부족 공간군집지역 전체가 통계량 기준을 100% 만족하여 통계적으로 유의미한 결과가 도출되었다. 이는 표준유역 단위로 공간군집분석을 할 경우 가변적 공간단위 문제를 일정 부분 해결한 것으로 공간군집분석의 정확성이 상대적으로 높아졌다.

• 천문학회보
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• 제46권2호
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• pp.67.4-68
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• 2021

In studying the dynamical evolution of galaxy clusters, one intriguing approach is to compare the spatial distributions of various components, such as the dark matter, the member galaxies, the gas, and the intracluster light (ICL; the diffuse light from stars, which are not bound any individual cluster galaxy). If we find a visible component whose spatial distribution coincides with the dark matter distribution, then we could draw a dark matter map without requiring laborious weak lensing analysis. Furthermore, if the component traces the dark matter distribution better for more relaxed galaxy cluster, we could use the similarity as a dynamical stage estimator of the galaxy cluster. We present a novel new methodology to quantify the similarity of two or more 2-dimensional spatial distributions. We apply the method to a sample of galaxy clusters at different dynamical stages simulated within N-cluster Run, which is an N-body simulation using the galaxy replacement technique. Among the various components (stellar particles, galaxies, ICL), the velocity defined ICL+ brightest cluster galaxy (BCG) component traces the dark matter best. Between the sample galaxy clusters, the relaxed clusters show stronger similarity of the spatial distribution between the dark matter and ICL+BCG than the dynamically young clusters.

• 한국지리정보학회지
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• 제23권3호
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• pp.68-84
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• 2020

본 연구에서는 경상남도 창원시를 대상으로 노인인구 분포지역의 공간적 특성과 폭염과의 관계를 분석하였다. 이를 위해 통계청의 인구센서스 자료와 환경부 토지피복도, Landsat 8 지표면온도, 기상청의 폭염일수 자료를 활용하였다. 노인인구 분포의 공간적 특성은 토지이용특성을 고려하여 K-mean 군집화 분석을 통해 총 5개 유형으로 분류하였다. 공간유형별 노인인구 특성은 도시화된 유형(cluster-3)에서 노인인구의 수가 많았으나, 농촌지역과 산림지역에 분포하는 유형(cluster-1, cluster-2)에서는 노인인구의 구성 비율이 높은 것으로 나타났다. 지표면온도와 폭염일수 특성에서는 도시지역에서 지표면온도가 가장 높았으나 폭염일수는 농촌지역이 가장 많았다. 노인인구 분포지역의 공간유형에 따른 폭염 특성을 분석한 결과, 농촌지역 면적이 많은 cluster-2가 15.95일로 가장 높았고, 도시화된 유형인 cluster-3은 9.41일로 가장 낮았다. 즉, 도시지역에 거주하는 노인인구보다 농촌지역에 거주하는 노인인구가 폭염에 더욱 노출되어 있으며, 피해가 가중될 것으로 예상된다. 본 연구의 결과는 여름철 폭염 취약지역의 효과적인 관리와 사전 예방을 위한 다양한 정책방안을 마련하는데 기초적인 자료로 활용될 수 있을 것이다.

• International Journal of Costume and Fashion
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• 제12권1호
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• pp.29-48
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• 2012

The purpose of this study was to examine the relationship between consumer spatial behavior and consumer characteristics based on trade area selection criteria 469 female consumers who lived in the two new towns near Seoul, Bundang and Ilsan, participated in the study by completing questionnaires. Data were analyzed by using cluster analysis, ANOVA, Duncan's multiple range test, chi-square analysis, etc. The findings of the empirical research were as follows: 1. Five groups were identified by cluster analysis based on trade area selection criteria of clothing price-oriented group, time convenience-oriented group, shopping convenience-oriented group, variety/entertainment-oriented group, and passive shopping group. 2. Each group differed in spatial behavior such as clothing shopping area, the visiting frequency, and spatial movement type. 3. Each group showed differences in fashion involvement and demographic characteristics(age, marital status, education, occupation and social status).

• 환경영향평가
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• 제20권3호
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• pp.299-311
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• 2011

The objective of this paper is to present a methodology for the classification of spatial patterns considering the parameters of urban form which play a significant role in the formation of the urban climate. The urban morphological parameters, i.e. building coverage, impervious pavement, vegetation, water, farmland and landuse types were used to classify the spatial patterns by a K-means cluster analysis. And the presented methodology was applied on Changwon city, South Korea. According to the results of cluster analysis, the total spatial patterns were classified as 24 patterns. First of all, The spatial patterns(A-1, A-2, A-3, B-1, B-2, B-3, C-1, C-2, C-3, D-1, D-2, D-3, E-1, E-2, E-3, F-1, F-2, F-3, G-1, G-2, G-3), which distributed in the rural area and the suburban area, can have the positive impacts of cold air generation and wind corridor on an urban climate environment, were distributed in the rural area. On the other hand, the spatial patterns of the downtown area including A-4, B-4, C-4 and D-4 are expected to have the negative impacts on urban climate owing to the of artificial heat emission or the wind flow obstruction. Finally, it will require the future research to analysis the climatic properties according to the same spatial patterns by the field survey.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

• 농촌계획
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• 제29권3호
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• pp.79-89
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• 2023

As the demand for environmental-friendly agricultural products continues to rise due to increased concerns regarding food safety and ecosystem conservation, it is becoming important to identify regions and spatial locations where environmental-friendly should be intensively established for production integration. This study aims to analyze the spatial distribution of environmental-friendly certified farms in Jeollanam-do, South Korea. Spatial statistical analysis based on Local Moran's I and Getis-Ord Gi^* were used to identify spatial cluster characteristics and landscape indices were utilized to analyze spatial patterns of environmental-friendly certified farms. The results indicated that Haenam-gun, Gangjin-gun, Muan-gun, and Jindo-gun were identified as hotspots, while Muan-gun, Goheung-gun, and Jindo-gun exhibited high connectivity. This suggests that environmental-friendly certified farms in Muan-gun and Jindo-gun were clustered and closely connected to one another. Based on the results of the spatial distribution of environmental-friendly certified farms, areas belonging to the hotspot and with high connectivity should be managed as clustered districts to secure the foundation and system of environmental-friendly certified farms. Areas that belong to cold spots and have low connectivity should be preceded by measures to promote conversion to environmental-friendly agriculture. In addition, it is necessary to make it possible to create a large-scale cluster district through a long-term spatial planning strategy to expand the environmental-friendly certified farms. The findings of this study can provide quantitative data on policies and discussions for developing a model for rural spatial planning.