Citation

Yi MS, Yeo KH. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography 2021; 39(1): 29-40.

Copyright

(Copyright © 2021)

DOI

10.7848/ksgpc.2021.39.1.29

PMID

unavailable

Abstract

Risk factors that threaten public safety such as crime, fire, and traffic accidents have spatial characteristics. Since each region has different dangerous environments, it is necessary to analyze the spatial pattern of risk factors for each sector such as traffic accident, fire, crime, and living safety. The purpose of this study is to analyze the spatial distribution pattern of local safety level index, which act as an index that rates the safety level of each sector (traffic accident, fire, crime, living safety, suicide, and infectious disease) for basic local governments across the nation. The following analysis tools were used to analyze the spatial autocorrelation of local safety level index : Global Moran's I, Local Moran's I, and Getis-Ord's G*i. The result of the analysis shows that the distribution of safety level on traffic accidents, fire, and suicide tends to be more clustered spatially compared to the safety level on crime, living safety, and infectious disease. As a result of analyzing significant spatial correlations between different regions, it was found that the Seoul metropolitan areas are relatively safe compared to other cities based on the integrated index of local safety. In addition, hot spot analysis using statistical values from Getis-Ord's G*i derived three hot spots(Samchuck, Cheongsong-gun, and Gimje) in which safety-vulnerable areas are clustered and 15 cold spots which are clusters of areas with high safety levels. These research findings can be used as basic data when the government is making policies to improve the safety level by identifying the spatial distribution and the spatial pattern in areas with vulnerable safety levels. © 2021 Korean Society of Surveying. All rights reserved.

Language: ko

Keywords

crime; safety; South Korea; cluster analysis; spatial distribution; index method; spatial analysis; policy making; local government; metropolitan area; autocorrelation; Hot Spot; Local Safety Level Index; Seoul [South Korea]; Spatial Autocorrelation; Spatial Pattern