• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.124-137
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• 2018

The main purpose of this study is to find the hotspots of crimes that occur frequently in the space and to derive the appropriate CCTV installation location. One of the characteristics of crime is clustered around past occurrence area, and these crimes are strongly correlated. It is also possible to find the cause of the clusters and the variables that affect the crime through the history of the crime. In addition to the traditional OLS model, spatial differential model including spatial autocorrelation and spatial error model were used to select the variables influencing the five major crime rate, the theft rate and the foreign resident rate. The variables affecting the Five major crimes were positive (+) sign for the welfare and the rate of the bar cluster rate, and negative (-) for the street density. The CCTV area occupies 46% of the hotspots based on the overlapping of the areas where the elderly people are crowded, the bar cluster, many multicultural families, and the areas with low density of street lamps. It turned out. Taking into account the current CCTV operation, the total number of new cases to cover the risk point was 89.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2010.09a
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• pp.102-107
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• 2010

본 연구에서는 2009년 강원도 읍면동 주민등록 데이터와 탐구적 공간데이터 분석 방법의 하나인 Getis - Ord $Gi^*$를 이용하여 강원도 남녀 장수인구의 공간적 분포패턴을 분석하였다. 분석결과는 강원도의 남성인구와 여성인구의 지역적 장수도에 공간적 군집이 존재하며 장수도가 높은 지역의 군집의 경우 남성과 여성 사이에 커다란 차이가 존재함을 보이고 있다. 남성의 경우 장수도가 높은 지역이 영서지역의 접경지역을 중심으로 군집하는 반면 여성의 경우 장수도가 높은 지역이 영동 해안지역 중심으로 군집하여 분포하였다. 이 결과는 장수에 영향을 미치는 환경적(자연환경적, 사회적) 요인이 남녀에 선별적으로 작용하고 있음을 암시한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3D
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• pp.391-397
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• 2008

This paper analyzes the spatial patterns of population distribution in Seoul Metropolitan Area in terms of spatial association using spatial statistics and spatial exploratory technique. Our empirical analysis based on global index shows that, in Seoul Metropolitan Area, the population had been distributed with strong positive spatial association over the period of 1980-2005. It implies that the population of each region is affected by the population distribution of adjacent regions. In addition, the analysis using local index was conducted for detecting the local patterns of spatial association, and the result shows that the clusters of population had been moved in the direction of West(Incheon and Bucheon) and South(Anyang and Seongnam) of Seoul where a large scale of lands or towns were developed over the period. These results will be the preliminary data for establishing management and development plans of Seoul Metropolitan Area.

• Spatial Information Research
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• v.7 no.2
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• pp.159-173
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• 1999

GIS has been regarded as one of important tools or methodologies for various geoscience applications. Recently, spatial data integration schemes for site-specific or field-specific thematic mapping are newly developed and utilized. However, these kinds of approaches are somewhat insufficient quantitative assessment of integrated layers towards known targets in-detailed . Moreover, GIS analysis scheme is rarely extended to scientific approaches. In this study, simple approach of Multi-Buffer Zone Analysis , related to GIS analystical aspect, is addressed and an actual application for predicting or favorable mapping of mineral occurrences, one of GIS-based geoscientific approaches, is performed, As for geo-processing in GIS itself, this scheme can be regarded as extension or adaptiation of cell-based buffering or proximity analysis to geoscientific data interpretation. This study is based on rationale that surface geological pattern around primitives such as a point, a line, or a polygon in GIS, representing significant geological features, can be efficiently utilized to delineate complex geological behaviors or events, especially handling multiple dta sets originated from multiple sources such as airborne geophysical/radiometric exploration, field survey, and even a classified image of remote sensing. Conclusively, this methodology associated wit GIS is though to be helpful to analyze the spatial pattern of multiple data, pointing given sources, and is expected to effectively utilize for exploratory analysis of cell-based resultant layer integrated with complex or different data sources.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.1
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• pp.12-25
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• 2009

The aim of this study is to analyze the periodical and spatial characteristics of urban crime and to find out the factors that affect the crime occurrence. For these, crime data of Masan City was examined and crime occurrence pattern is ploted on a map using crime density and criminal hotspot analysis. The spatial relationship of crime occurrence and factors affecting crime were also investigated using ESDA (Exploratory Spatial Data Analysis) and SAR (Spatial Auto-Regression) model. As a result, it was found that crimes had strong tendency of happening during a certain period of time and with spatial contiguity. Spatial contiguity of crimes was made clear through the spatial autocorrelation analysis on 5 major crimes. Especially, robbery revealed the highest spatial autocorrelation. However as a autocorrelation model, Spatial Error Model(SEM) had statistically the highest goodness of fit. Moreover, the model proved that old age population ratio, property tax, wholesale-retail shop number, and retail & wholesale number were statistically significant that affect crime occurrence of 5 most major crimes and theft crime. However population density affected negatively on assault crime. Lastly, the findings of this study are expected to provide meaningful ideas to make our cities safer with U-City strategies and services.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.1
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• pp.1-18
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• 2019

This research measured and visualized the spatial dependency and the spatial heterogeneity of the small business in Cheonan-si, Asan-si with $100m{\times}100m$ grids based on global and local spatial autocorrelation. First, we confirmed positive spatial autocorrelation of small business in the research area using Moran's I Index, which is ESDA(Exploratory Spatial Data Analysis). And then, through Getis-Ord $GI{\ast}$, one kind of LISA(Local Indicators of Spatial Association), local patterns of spatial autocorrelation were visualized. These verified that Spatial Regression Model is valid for the location factor analysis on small business commercial buildings. Next, GWR(Geographically Weighted Regression) was used to analyze the spatial relations between the distribution of small business, hourly mobile traffic-based floating population, land use attributes index, residence, commercial building, road networks, and the node of traffic networks. Final six variables were applied and the accessibility to bus stops, afternoon time floating population, and evening time floating population were excluded due to multicollinearity. By this, we demonstrated that GWR is statistically improved compared to OLS. We visualized the spatial influence of the individual variables using the regression coefficients and local coefficients of determinant of the six variables. This research applied the measured population information in a practical way. Reflecting the dynamic information of the urban people using the commercial area. It is different from other studies that performed commercial analysis. Finally, this research has a differentiated advantage over the existing commercial area analysis in that it employed hourly changing commercial service population data and it applied spatial statistical models to micro spatial units. This research proposed new framework for the commercial analysis area analysis.

• Spatial Information Research
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• v.20 no.6
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• pp.23-32
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• 2012

This study applied an exploratory analysis based on Self Organizing Map and GIS to cause specific age-standardized regional death rates data related to ten types of male cancers to find meaning patterns in the data. Then the patterns revealed from the exploratory analysis was evaluated to investigate possible relationship between these patterns and regional socio-economic status represented by regional educational attainment levels of head of household. The results from this analysis show that SI-GUN-GUs in Korea can be clustered to eighteen unique clusters in the stand point of male cancer death rates and these clusters are also spatially clustered. Also, the results reveal that regions with higher socio-economic status show lower level of the death rates compared with the regions with lower socio-economic status. However, for some cancer types, the regions with higher socio-economic status show relatively higher death rates. These patterns imply that the prevention, detection, and treatment of male cancers might be strongly affected by regional factors such as socio-economic status, environmental factors, and cultures and norms in Korea. Especially, one of the eighteen clusters, which includes Gangnam-Gu and Seocho-Gu, shows lower death rates in many of male cancer types. This implies that socio-economic status may be one of the most influential factors for regional cancer control.

• Journal of Korean Academy of Nursing
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• v.36 no.6
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• pp.1042-1054
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• 2006

Purpose: Previous evaluation studies of the visiting nursing program explained an average change of the participants' health status, without considering socio-ecological characteristics and their impacts. However, these factors must affect individual health problems and lifestyles. For effective and appropriate community based programs, the Geographical Information System(GIS) can be utilized. GIS is a computer-based tool for mapping and analyzing things that happen on earth, and integrates statistical analysis with unique visualization. The purpose of this study was to evaluate visiting nursing care and to advocate the usefulness of planning and evaluating visiting nursing programs using Exploratory Spatial Data Analysis(ESDA) with GIS technology. Methods: One hundred eighty-four elderly participants with cerebrovascular risk factors who lived in 13 areas of one community received visiting nursing care. The data analyzed characteristics of pre-post change and autocorrelation by ESDA using GIS technology. Results: Visiting nursing care showed an improvement in the participants' lifestyle habits, and family management ability and stress level, while the improvements were different depending on the regions. The change of family management ability and stress level correlated with neighborhoods (Morgan's I=0.1841, 0.1675). Conclusions: Community health providers need to consider the individual participant's health status as well as socio-ecological factors. Analysis using GIS technology will contribute to the effective monitoring, evaluation and design of a visiting nursing program.

• Journal of the Korean association of regional geographers
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• v.12 no.4
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• pp.508-521
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• 2006

The results of environmental equity analysis vary dramatically depending on different methods used. The information and data available to the researcher are also often uncertain and imprecise in empirical studies. A sensitivity analysis approach was used too handle uncertainties and methodological inconsistencies in environmental equity analysis. This paper explores the sensitivity of environmental equity analysis to two spatial measures such as proximity and scale. Two experiments were implemented to evaluate the effects of two spatial measures on the environmental equity analysis using a combination of control and experimental factors. Fulton County, Georgia was selected as a case study area for these experiments. Two major data sets including demographic characteristics and toxic release inventory (TRI) database for the study area in 1990 were integrated into a GIS environment. Two statistical analyses such as independent samples t-test and coefficient of variation were performed to determine the environmental equity in the study area and to compare the relative variability in the socioeconomic characteristics of populations over different spatial measures. The findings from two experiments indicate that the outcomes of environmental equity analysis are slightly sensitive to the buffer distance used to determine the impact zones of TRI facilities, but not to the geographic scale used in the analysis. The findings also suggest that the consequences of these choices can alter spatially and statistically the results in environmental equity analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.1
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• pp.43-51
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• 2012

The OLS(ordinary least squares) method is widely used in hedonic housing models. One of the assumptions of the OLS is an independent and uniform distribution of the disturbance term. This assumption can be violated when the spatial autocorrelation exists, which in turn leads to undesirable estimate results. An alterative to this, spatial econometric models have been introduced in housing price studies. This paper describes the comparisons between OLS and spatial econometric models using housing transaction prices of Busan, Korea. Owing to the approaches reflecting spatial autocorrelation, the spatial econometric models showed some superiority to the traditional OLS in terms of log likelihood and sigma square(${\sigma}^2$). Among the spatial models, the SAR(Spatial Autoregressive Models) seemed more appropriate than the SAC(General Spatial Models) and the SEM(Spatial Errors Models) for Busan housing markets. We can make sure the spatial effects on housing prices, and the reconstruction plans have strong impacts on the transaction prices. Selecting a suitable spatial model will play an important role in the housing policy of the government.