• ETRI Journal
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• 제43권2호
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• pp.272-287
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• 2021

This article presents a multi-dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made, a binary classification-based model is framed, and when all categories are considered for analysis, a multiclass model is formulated. The proposed crime-prediction model (HotBlock) utilizes spatiotemporal analysis for predicting crime in a fixed spatial region over a period of time. It is robust under variation of model parameters. HotBlock's results are compared with baseline real-world crime datasets. It is found that the proposed model outperforms the standard DeepCrime model in most cases.

• 한국콘텐츠학회:학술대회논문집
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• 한국콘텐츠학회 2015년도 춘계 종합학술대회 논문집
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• pp.17-18
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• 2015

To improve urban safety there is an increasing social need for environmental design against crime, which is defined as the creation of inconvenient environments or situations for criminal offenders. By using a cluster analysis, we aimed to clarify crime occurrence patterns from the perspective of land-use. Osaka Prefecture was chosen as the study area because it has the highest crime rate in Japan. The results revealed that there are six patterns of crime occurrence, and that cities of medium-level of mixed land-use have the lowest crime rates.

• 대한건축학회논문집:계획계
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• 제36권5호
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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.

• 대한건축학회논문집:계획계
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• 제35권11호
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• pp.53-60
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• 2019

Multi-unit house, multi-household house, row house and apartments with less than 500 households were included in the list of anti-crime for buildings following the revision of the "notice of crime prevention building standards" on July 31, 2019. Strengthening the performance of crime prevention buildings is inevitable to increase the cost of building construction, including installation of preventive facilities and use of facilities that have secured performance. Thus an economic analysis on the costs and expected benefits of implementing the standards is required for social consensus. Economic analysis is divided into cost analysis and benefit analysis. This study aims to perform an economic analysis on the installation of crime prevention facilities in the buildings subject to expanded crime prevention obligations. Cost analysis is calculated as the sum of the cost of installation and the price of the crime prevention facilities installed for each target residential building. Benefit analysis is calculated as the social cost of targeted crimes that are expected to decrease due to the installation of crime prevention facilities. Economic analysis shows that the total cost of installing crime prevention facilities in residential buildings is estimated at 107.31 billion won per year, while the total benefit from enhanced crime prevention performance is estimated at 9.38 billion won per year. Considering inflation, benefits are expected to outpace costs in the 28th year since the system was implemented.

• Architectural research
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• 제14권2호
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• pp.45-56
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• 2012

The high rate of urban crime is a main issue that needs to be dealt with in this high-tech society. With the rapid increase of urban crime, research has mainly focused on topics either on a global or a local scale, such as cities or communities and houses or buildings, without reliable observational data. This study makes the best use of the nationwide surveys carried out by Korean government agencies for the analysis of urban crime patterns and factors in major Korean cities. The aims of this research are threefold: understanding the relationship between urban crime patterns and socio-economic differences in cities, determining the effect of residence types on the urban crime patterns; and uncovering potential influential factors of a crime victim's individual characteristics. The statistical methods used for the analysis of social statistical data are as follows: simple regression, logistic regression, one-way ANOVA and post-hoc test. This research found that the patterns of urban crime rate in cities have a certain tendency toward the cities' socio-economic and geographical differences. The residence type is an influential factor showing a close relation to the crime rate. Personal issues, such as the types of occupation, education, marriage, etc., are directly relevant to victims of crime.

• ETRI Journal
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• 제43권6호
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• pp.1058-1080
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• 2021

Crime is not a completely random event but rather shows a pattern in space and time. Capturing the dynamic nature of crime patterns is a challenging task. Crime prediction models that rely only on neighborhood influence and demographic features might not be able to capture the dynamics of crime patterns, as demographic data collection does not occur frequently and is static. This work proposes a novel approach for crime count and hotspot prediction to capture the dynamic nature of crime patterns using taxi data along with historical crime and demographic data. The proposed approach predicts crime events in spatial units and classifies each of them into a hotspot category based on the number of crime events. Four models are proposed, which consider different covariates to select a set of independent variables. The experimental results show that the proposed combined subset model (CSM), in which static and dynamic aspects of crime are combined by employing the taxi dataset, is more accurate than the other models presented in this study.

• 시큐리티연구
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• 제14호
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• pp.261-283
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• 2007

범죄두려움의 원인을 설명하기 위한 최근의 연구들에서는 성, 연령, 경제수준, 범죄 피해경험 등의 미시적인 개인수준과 거시적인 지역수준과의 연계를 시도하는 연구에 관심과 노력을 보이고 있다. 하지만 이 연구에서는 이러한 지역수준의 특성에 대한 개인의 관심과 해석은 개인의 특성으로서 과거의 범죄피해경험, 범죄피해의 취약성 정도, 범죄관련 정보에 대한 관심에 따라 다를 수 있다고 보며, 미시적인 수준과 거시적인 수준의 연계를 시도하기에 앞서 개인적인 수준에서 개인의 특성과 범죄두려움의 관계에 대해서 실증적인 분석을 실시하였다. 따라서 이 연구의 목적은 범죄두려움이 과연 개인의 특성에 따라서 어떻게 느끼게 되며 또한 얼마나 많은 영향을 받게 되는지를 실증적으로 검증하는 데에 그 목적이 있다. 이 연구의 조사결과 우선 범죄피해경험이 집단간의 차이가 통계적으로 유의미한 인구통계학적 특성은 연령, 결혼상태, 최종학력, 거주하는 장소였으며, 범죄피해의 취약성 정도는 성별과 결혼상태, 범죄관련 정보에 대한 관심은 성별, 연령, 최종학력, 가족 수입, 거주장소 위치에 따라서 집단 간의 통계적으로 유의미한 차이가 있는 것으로 나타났다. 둘째, 개인적 특성 요인과 범죄두려움의 상관관계 분석을 실시한 결과 독립변수 세요인 모두 범죄두려움과 통계적으로 유의미한 상관관계를 나타내고 있었으며, 특히 범죄피해에 대한 취약성 요인이 범죄두려움과 가장 상관관계가 높게 나타났다. 마지막으로 개인의 특성으로서 범죄피해의 취약성, 범죄정보에 대한 관심, 범죄피해경험은 범죄두려움에 영향을 미쳤으며, 특히 이러한 개인적 특성 요인 중 자신이 범죄피해에 대해 취약하다고 생각 하는 범죄피해의 취약성이 범죄두려움에 가장 많은 영향을 미치는 요인으로 나타났다.

• 한국주거학회논문집
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• 제25권3호
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• pp.85-92
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• 2014

The purpose of this study is to explore the relationship between housing types and crime and to suggest the appropriate strategies and interventions of housing policies for crime prevention. For spatial analysis of crime data, spatial autocorrelation is tested by Moran's I Test. A Ordinary Least Squares-based regression model is employed because crime data used in this study fails to show spatial autocorrelation. Results show that housing type variables except non-residential housing type are not associated with crime. Among land-use characteristics, the percentage of commercial areas is likely to better explain crime occurrence rather than housing types. It is surprising that residents' satisfaction to housing environment has a positive direction in its relationship with crime even though it cannot have a statistical significance. However, fear of crime shows a negative direction with crime although it fails to have a statistical significance. The findings of this study can contribute to understand the association between housing types and crime when setting housing policies for crime prevention.

• 유통과학연구
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• 제16권7호
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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.

• 한국위성정보통신학회논문지
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• 제9권4호
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• pp.57-62
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• 2014

본 논문에서는 빅 데이터를 이용하여 범죄 발생 패턴을 분석하는 알고리즘을 제안하고 구현했다. 제안된 알고리즘은 대검찰청에서 수집하여 공개한 범죄관련 빅 데이터를 사용하며, 표준편차 타원체 및 공간밀도 분석과 같은 공간통계분석을 통해 서울시의 2011-2013년 범죄발생 패턴을 분석했다. 범죄 발생 빈도수를 이용하여 범죄발생지역, 시간, 요일, 장소의 위험지수를 구했고, 범죄 패턴 분석 알고리즘을 통해 범죄 발생 확률을 구했다. 이를 통해 공간통계분석을 했다. 제안된 알고리즘의 구현 결과, 서울시의 각 구별로 범죄발생 패턴이 다르다는 것을 파악할 수 있었고, 다양한 범죄발생 패턴을 분석하고 범죄발생확률을 위험지수를 통해 수치화하여 위험도를 정량적으로 산출할 수 있었다.