GIS와 공간통계기법을 이용한 시,공간적 도시범죄 패턴 및 범죄발생 영향요인 분석 = Analysis of Spatio-temporal Pattern of Urban Crime and Its Influencing Factors

다국어 초록 (Multilingual Abstract)

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.

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