• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.63-79
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• 2008

With the recent development of advanced GIS and complex spatial analysis technologies, the more sophisticated technologies are being required to support the advanced knowledge for solving geographical or spatial problems in various decision support systems. In addition, necessity for research on scientific crime investigation and forensic science is increasing particularly at law enforcement agencies and investigation institutions for efficient investigation and the prevention of crimes. There are active researches on geographic profiling to predict the base location such as criminals' residence by analyzing the spatial patterns of serial crimes. However, as previous researches on geographic profiling use simply statistical methods for spatial pattern analysis and do not apply a variety of spatial and temporal analysis technologies on serial crimes, they have the low prediction accuracy. Therefore, this paper identifies the typology the spatio-temporal patterns of serial crimes according to spatial distribution of crime sites and temporal distribution on occurrence of crimes and proposes STA-BLP(Spatio-Temporal Analysis based Base Location Prediction) algorithm which predicts the base location of serial crimes more accurately based on the patterns. STA-BLP improves the prediction accuracy by considering of the anisotropic pattern of serial crimes committed by criminals who prefer specific directions on a crime trip and the learning effect of criminals through repeated movement along the same route. In addition, it can predict base location more accurately in the serial crimes from multiple bases with the local prediction for some crime sites included in a cluster and the global prediction for all crime sites. Through a variety of experiments, we proved the superiority of the STA-BLP by comparing it with previous algorithms in terms of prediction accuracy.

• Journal of the Economic Geographical Society of Korea
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• v.16 no.3
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• pp.512-527
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• 2013

This study examines the spatial distribution characteristics of financial industry which has been a necessary service for contemporary urban life. In particular, we analyze the spatial distribution patterns of money lending business which is considered with informal financial services as well as the spatial distribution patterns of banks which are representative of the institutional financial services. For the purpose, their density distribution patterns are explored by Kernel density analysis for both financial services in first. Moran's I coefficients are estimated for these two financial services to clarify the distintion in their geographical concentration patterns. The results of spatial autocorrelation analysis show stark differences between the center city and outskirts of the Seoul metropolitan area. Multivariate regression models are developed to explain the relationships between the spatial distributions of financial services and geographical variables. Finally, we discuss financial exclusion problem in the Metropolitan Seoul based on these spatial distribution characteristics.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.59-62
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• 2015

하천에서 유사이동 분석이 중요한 이유는, 지속가능한 하천관리의 관점에서 하도, 구조물, 생물 서식처와 수질에 이르기까지 하천 내 유사이동이 미치는 영향이 광범위하기 때문이다. 특히, 유사가 어느 지점에서 유실되며 어느 지점에 쌓이는지와 같은 이슈는 하천 지속가능한 관리를 위한 핵심이라 해도 과언이 아니다. 상대적으로 크기가 작은 부유사 입자의 이동은 일상적인 하천의 흐름에서도 대부분 관찰되기 때문에, 그 이동패턴을 파악하는 것이 하천의 효율적 관리에 밑바탕이 된다. 기존연구들에서 주로 연구되었던 부유사 농도 또는 플럭스 산정은 유사에 의한 영향을 파악하기 위한 좋은 지표임은 분명하지만, 유사 입자가 움직이기 시작하는 지점이나 침전하는 지점 등 공간적 분석을 위해서는 입자의 움직임에 초점을 맞춘 분석이 필요하다. 따라서 본 연구에서는 부유사 입자를 추적하는 모의 방법을 이용하여, 개수로에서 부유사 입자를 방류하는 형태가 바뀌었을 때, 입자의 공간적 분포가 어떤 식으로 영향을 받는지에 대하여 분석하였다. 모의결과와 실험결과를 비교하여 연구의 접근방법이 부유사 이동의 공간적 분석을 위한 타당한 방법을 검증하였으며, 나아가 실험으로 측정하기 어려운 부유사 이동 패턴을 제시하였다. 입자의 방류 위치나 방류 간격 등 부유사 입자의 분산에 영향을 미치는 요인들 또한 함께 분석하였다.

• Journal of the Economic Geographical Society of Korea
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• v.12 no.2
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• pp.179-194
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• 2009

The spatial distribution of crime incidences in urban neighborhoods is a reflection of their socio-economic environment and spatial inter-relations. Spatial interactions between offenders and victims lead to spatial autocorrelation of the crime incidences. The spatial autocorrelation among the incidences biases the interpretation of the ecological model in OLS framework. This research investigates residential crimes using residential burglaries and robberies occurred in the city of Columbus, Ohio, for 2000. In particular, the spatial distribution of incidence rates of residential crimes are accounted in OLS framework using eigenvectors, which reflect spatial dependence in crime patterns. Result presents that handling spatial autocorrelation enhanced model estimation, and both economic deprivation and crime opportunity are turned out significant in estimating residential crime rates.

• Spatial Information Research
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• v.20 no.1
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• pp.81-90
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• 2012

When analyzing geographical phenomena, two properties need to be considered. One is the spatial dependence structure and the other is a variation or an uncertainty inhibited in a geographic space. Two problems are encountered due to the properties. Firstly, spatial dependence structure, which is conceptualized as spatial autocorrelation, generates heterogeneous geographic landscape in a spatial process. Secondly, generic statistics, although suitable for dealing with stochastic uncertainty, tacitly ignores location information im plicit in spatial data. GIS is a versatile tool for manipulating locational information, while spatial statistics are suitable for investigating spatial uncertainty. Therefore, integrating spatial statistics to GIS is considered as a plausible strategy for appropriately understanding geographic phenomena of interest. Geographic hot-spot analysis is a key tool for identifying abnormal locations in many domains (e.g., criminology, epidemiology, etc.) and is one of the most prominent applications by utilizing the integration strategy. The article aims at reviewing spatial statistical perspective for analyzing spatial processes in the framework of GIS by carrying out empirical analysis. Illustrated is the analysis procedure of using spatial scan statistic for detecting clusters in the framework of GIS. The empirical analysis targets for identifying spatial clusters of breast cancer incidents in Erie and Niagara counties, New York.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.2
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• pp.125-146
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• 2020

There is an increasing need to foster new industries at the local level. This study aims to analyze the spatial patterns of new industries in Korea from 2007-2017 and to figure out its determinants of agglomeration in 2017. Through this study, it is found that new industries are unevenly distributed around Seoul Metropolitan Area(SMA). The regional disparity between SMA and non-SMA is prominent. Furthermore, new industries represent a strong spatial positive autocorrelation, showing a strong concentration on a few regions in Korea. This study explores the determinants on agglomeration of new industries with spatial statistical model. From the results of spatial error model, it is indicated that the number of graduate students, the ratio of technology based start-ups, and the number of elementary, middle, and high schools have a significant effect on new industries. In addition, the specialization and the diversity of industrial structure on knowledge-based manufacturing industries and knowledge-based service industries have been statistically significant. This study provides implications that non-SMA needs policies with respect to attracting talented people, developing human resources, and improving regional environment in order to improve regional competitiveness in promoting new industries.

• Journal of the Economic Geographical Society of Korea
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• v.14 no.1
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• pp.33-51
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• 2011

This study investigates the spatial characteristics of the provision of and demand for the private tutoring service industries and the consumer groups. For the purpose, we analyze the spatial characteristics of various types of tutoring institutes in the Seoul Metropolitan area. In particular, we exam the spatial distribution patterns of attendants of tutoring institutes by institution type as well as the resident population by attendant age group. By applying spatial autocorrelation analysis, we examine the spatial clustering patterns of tutoring institutes and attendants by type. The results show distinct differences in the spatial distribution patterns by tutoring institute type as well as by attendant age group. We found significant socio-economic variables which influence on the spatial distribution of tutoring institutes. Finally, we propose private tutoring service provision models constructed with these variables through multiple regression analysis.

• Spatial Information Research
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• v.20 no.4
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• pp.69-82
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• 2012

The purpose of this study was to identify structural properties of C.B.D and to provide direction that required for the plan and its development by analyzing land use patterns and its characteristics in the center of the city. In this study, the future planning elements and detailed land use of Seoul was analyzed, in regard to the spatial structural hierarchy and the function of downtown, by investigation of its current urban spatial structure. First, the characteristic of the land-use for merchandising facilities is that it is developed from west to east along the Jong-ro, Myungdong and Namdaemun, it shows high rate of the facilities along the horizontal axis. The large market area on this district would be the reason to the high rate of mechandising facilities. Second, the characteristic of the land-use for business facilities is that it is highly rated on the area passing through the Sejong-ro and Seoul station. The analysis result of our investigation is that the projects executed by Seoul city such as 'downtown maintenance planning' and 'downtown recreation program' strengthened functions of business and merchandising and promoted downtown shopping, leisure, tourism functions resulting activation of nearby market place and evaluated as maintaing the centrality of downtown Seoul well.

• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.213-213
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• 2023

하천의 합류부는 두 하천이 만나 형성되는 지역으로 복잡한 혼합 거동을 보인다. 합류부에서는 실제로 수리 특성이 유황에 따라 다양하게 변화하고 수환경 특성도 함께 변화하며, 이로 인해 본류와 지류에 비해 다양한 생태학적인 종이 분포하는 등 환경적으로 중요구간 중 하나이다. 합류부의 혼합 거동을 이해하기 위해서는 다양한 유황에 따른 수체 혼합 거동을 2차류를 통해 분석하는 것이 중요하다. 해외의 경우 2차류의 패턴을 통해 합류부에서의 혼합 거동을 공간적으로 분석한바 있으나(Riley and Rhoads, 2012), 대부분의 연구들은 중·소규모의 하천을 대상으로 진행되어 대규모 하천에서의 확인은 미흡한 상태이다. 또한, 실제 현장에서 계측을 통한 데이터 획득과 후 처리의 어려움으로 인해 현재 국내에서는 2차류 패턴을 통해 대규모 하천 합류부의 혼합 거동을 확인한 사례는 전무한 실정이다. 따라서, 본 연구에서는 Sontek사의 ADCP를 통해 계측된 수리 데이터를 Rozovskii의 방법을 기반으로 한 2차류로 나타내 낙동강-금호강 합류부에서의 공간적인 수체 혼합을 확인하였다. 혼합거리를 판단하기 위해 합류 이후 혼합의 경계면(Shear Layer)에서 나타나는 2차류의 특이한 패턴(Helical motion)을 주요 지표(Index)로 사용하였다. 그리고, 수질 센서인 YSI EXO2의 수표면 전기전도도의 분포를 통해 합류부에서 본류와 지류의 혼합거리를 산정하였으며, 2차류의 패턴과 비교하였다. 분석 결과, 대규모 하천에서 2차류의 특이한 패턴이 존재함을 명확히 확인하였다. 본류와 지류의 모멘텀 비에 따라 서로 다른 패턴의 혼합양상을 2차류를 통해 확인할 수 있었으며, 2차류의 혼합 패턴과 전기전도도의 분포를 비교 분석하여 합류부에서의 혼합을 3차원적으로 해석하였다.