• Proceedings of the KAIS Fall Conference
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• 2010.05b
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• pp.630-633
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• 2010

입지분석은 공간 및 비공간적 특성이 중요하게 다루어져야 함에도 불구하고 공간데이터 타입(spatial data type), 공간관계(spatial relationship), 그리고 공간 자기상관성(spatial autocorrelation)의 복잡성에 기인한 처리의 어려움으로 인해 기하학적거리나 공간적 위치와 같은 단순 공간적 특성만 이용되었다. 본 연구에서는 서울시 대형할인점을 사례로하여로 GIS에 의한 공간데이터와 비공간데이터(인구통계 등)를 통합 구축한 후, 공간데이터마이닝 기법을 이용하여 입지패턴(location pattern)을 분석 추출하여 보고자 한다.

• Journal of Environmental Science International
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• v.21 no.3
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• pp.297-303
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• 2012

Slope is the geographic factor reflecting the 3-dimensional features of basin and it can be considered as the important geomorphological factor which governs the morphology of basin and the dynamics of water movement. In this study the approach to the 3-dimensional structures of basin is attempted with statistical analysis of local slope which can be defined and measured in easy and objective manner by means of DEM. As a result local slope is confirmed to be a highly variable spatial factor in basin. And distribution map of local slope based on spatial autocorrelation length in this study would be a useful tool in the further research of hydrology and geomorphology.

• Journal of the Korean Geographical Society
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• v.49 no.5
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• pp.761-778
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• 2014

There has been relatively little study to model price for commercial property because of its low transaction volume in the market. Despite of this thin market character, this paper tried to estimate prices for commercial lots as accurate as possible. We constructed a model whose components consist of mean structure(global trend), exponential covariance function and a pure error term, and applied it to actual sales price data of Seoul. We explicitly took account of spatial autocorrelation of land price by utilizing a kriging technique, a representative method of spatial interpolation, because the land price of commercial lots has feature of differential price forming pattern depending on submarkets they belong to. In addition, we chose to apply a bayesian kriging to overcome data scarcity by incorporating experts' knowledge into prior probability distribution. The chosen model's excellent performance was verified by the result from validation data. We confirmed that the excellence of the model is attributed to incorporating both autocorexperts' knowledge and spatial autocorrelation in the model construction. This paper is differentiated from previous studies in the sense that it applied the bayesian kriging technique to estimate price for commercial lots and explicitly combined experts' knowledge with data. It is expected that the result of this paper would provide a useful guide for the circumstances under which property price has to be estimated reliably based on sparse transaction data.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.23-32
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• 2020

Recently, women's fear of crime continues to increase in space of everyday. By the way, the fear of crime has the spatial properties as crime. Therefore, The purpose of this study is to evaluate the spatial dependence of fear of crime and to suggest the physical environmental factors influencing fear of crime. For this, a spatial regression analysis using spatial weights was conducted based on the location data of the fear of crime measured through a survey. The results of this study are as follows; First, the fear of crime felt by women in their twenties who are vulnerable to crime has spatial dependence. Therefore, it is necessary to consider the spatial characteristics in analyzing the environmental factors affecting this. Second, in order to reduce the fear of crime, it is necessary to improve the environments of old housing and entertainment facilities. There is also a need for ongoing management. Third, careful consideration is needed in the installation of CCTV and street lights, which are factors influencing the fear of crime. It is necessary to establish a reasonable arrangement standard for CCTV and to analyze the street lighting in detail.

• Journal of Korea Planning Association
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• v.54 no.2
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• pp.76-83
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• 2019

This study aims to empirically identify the effect of spatial accessibility, based on travel, on housing prices in the Korean capital region. More specifically, it has two research purposes: First, investigating the effect of comprehensive spatial accessibility, based on road network and actual trips from origin to destination, on average apartment price (Korean Won per square meter) at the level of Eup, Myeon and Dong; Second, identifying better accessibility index between Hansen's and Kalogirou and Foley's ones. The former represents a road-based travel time decay function with destination trips, while the latter is a function with origin trips as well as destination ones. The study employs spatial economic models considering spatial auto-correlative relationship as an appropriate methodology with such control independent indicators as population density, road density, educational environment and distances from CBDs. Analysis results demonstrate that spatial accessibility, based on road network and actual trips from origin to destination, has a statistically significant impacts on housing price in the region. Our empirical evidence proves that the Hansen index is more appropriate than the other in estimating housing price impacts.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.162-174
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• 2012

To visualize the characteristics of vertical seawater temperature data, in the ocean having 3D spatial characteristics, 2D thematic maps like horizontal seawater temperature distribution map at each depth layer and 3D volume model using 3D spatial interpolation are used. Although these methods are useful to understand oceanographic phenomena visually, there is a limit to analyze the spatial pattern of vertical temperature distribution or the relationship between vertical temperature characteristics and other oceanic factors (seawater chemistry, marine organism, climate change, etc). Therefore, this study aims to determine the spatial distribution characteristics of vertical temperature profiles in the South Sea of Jeju by quantifying the characteristics of vertical temperature profiles by using an algorithm that can extract the thermocline parameters, such as mixed layer depth, maximum temperature gradient and thermocline thickness. For this purpose spatial autocorrelation index (Moran's I) was calculated including mapping of spatial distribution for three parameters representing the vertical temperature profiles. Also, after grouping study area as four regions by using cluster analysis with three parameters, the characteristics of vertical temperature profiles were defined for each region.

• Journal of the Economic Geographical Society of Korea
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• v.9 no.3
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• pp.318-340
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• 2006

In the last decade, there has been a widespread interest in knowledge production activities as a new engine of endogeneous growth. In the knowledge-based economy, there has been a growing importance of the patent as the index of knowledge production. Much literature suggests that knowledge production activities tend to be spatially concentrated and formed the clusters in the advanced economies. The purpose of this paper is to analyze spatial-temporal patterns of knowledge production activities in Korea based on a data set of patents from 1981-2000. This paper uses spatial statistical methods and GIS to explore the spatial dimensions of knowledge production activities in Korea. Through this research, it was found that knowledge production activities were unevenly distributed. The knowledge production activity measured by patent counts is highly concentrated in a limited number of cities. The top 10 cities accounted for 68.5% of the total number of patents in the period of 1981-2000, suggesting the existence of a strong concentration of knowledge production activities in Korea. The locations of knowledge production activities by themselves represented a strong spatial autocorrelation. The concentration of knowledge production activities in Korea is spatially correlated to the concentration of adjacent neighboring cities. The location of knowledge production activities is not free from a spatial context and spillover of knowledge production activities are heavily bounded within geographic limits, forming a spatial cluster. There appear some quite a large spatial cluster around the seoul metropolitan area.

• Journal of Distribution Science
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• v.16 no.7
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• pp.47-56
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• 2018

Purpose - This study aims to not only investigate spatial pattern of immigrants' residence and crime occurrences in South Korea, but shed light on how geographic distribution of immigrants and immigrant segregation affect crime rates. Research design, data, and methodology - Th unit of analysis is Si-Gun-Gu municipal level entities of South Korea. The crime data was obtained by Korea National Police Agency and two major types(violence and property) of crime were measured. Most demographic, social, and economic variables were derived from Korean Census Data in 2015. In order to examine spatial patterns of immigrants' distribution and crime rates in South Korea, the present study utilized GIS mapping technique and Exploratory Spatial Data Analysis(ESDA) tools. The causal linkage was investigated by a series of regression models using STATA. Results - Spatial inequality between urban metropolitan vs rural areas was visualized by mapping. Assuming large Moran's I value, spatial autocorrelation appeared to be quite strong. Several neighborhood characteristics such as residential stability and economic prosperity were found to be important factors leading to crime rate change. Residential distribution and segregation for immigrants were negatively significant in the regression models. Conclusions - Unlike the traditional arguments of social disorganization theory, immigrant segregation appeared to reduce violent crime rate and the high proportion of immigrants also turned out to be a crime prevention factor.

• Journal of Korean Society for Quality Management
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• v.44 no.3
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• pp.677-688
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• 2016

Purpose: In this study, we examine the effects of circulatory diseases mortality in South Korea 2005-2013 using the air pollution index, Methods: We cluster the region of high risk mortality by SaTScan$^{TM}$9.3.1 and compare this result with the regional distribution of air pollution. We use the Geographically Weighted Regression (GWR) to consider the spatial heterogeneity of data collected by administrative district in order to estimate the model. As GWR is spatial analysis techniques utilizing the spatial information, regression model estimated for each region on the assumption that regression coefficients are different by region. Results: As a result of estimating model of the collected air pollution index, circulatory diseases mortality data combined with the spatial information, GWR was found to solve the problem of spatial autocorrelation and increase the fit of the model than OLS regression model. Conclusion: GWR is used to select the air pollution affecting the disease each year, the K-means cluster analysis discover the characteristics of the distribution of air pollution by region.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.3
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• pp.248-259
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• 2009

This paper analyzes the interactions among regional labor markets in Korea. Specifically, we focus on the job market externality between neighboring regions. To estimate the job matching functions, we construct panel data on unemployment, vacancies and hires for the period of January 2004 through December 2007 for 15 cities and provinces in Korea. We employ various spatial econometric techniques to avoid the problem of spatial autocorrelation which frequently arises when dealing with regional data. Main findings are as follows. First, estimation results are consistent with conventional job matching theory. That is, as the number of job searchers and vacancies increase, the number of hires also rises. And it is relatively easier for firms to hire workers than for job seekers to find jobs. Second, it is found that, other things equal, the possibility of job matching is higher in large metropolitan areas than rural areas. Finally, the findings show that the number of job searchers in neighboring areas is negatively correlated with the number of hires in the area. Likewise, the number of vacancies in neighboring areas is positively correlated with number of hires in the area. These provide clear evidence on the existence of regional spillover effects.