Burglary Crime Research Articles

MULTI-SPATIOTEMPORAL PATTERNS OF RESIDENTIAL BURGLARY CRIMES IN CHICAGO: 2006-2016

Abstract. This research attempts to explore the patterns of burglary crimes at multi-spatiotemporal scales in Chicago between 2006 and 2016. Two spatial scales are investigated that are census block and police beat area. At each spatial scale, three temporal scales are integrated to make spatiotemporal slices: hourly scale with two-hour time step from 12:00am to the end of the day; daily scale with one-day step from Sunday to Saturday within a week; monthly scale with one-month step from January to December. A total of six types of spatiotemporal slices will be created as the base for the analysis. Burglary crimes are spatiotemporally aggregated to spatiotemporal slices based on where and when they occurred. For each type of spatiotemporal slices with burglary occurrences integrated, spatiotemporal neighborhood will be defined and managed in a spatiotemporal matrix. Hot-spot analysis will identify spatiotemporal clusters of each type of spatiotemporal slices. Spatiotemporal trend analysis is conducted to indicate how the clusters shift in space and time. The analysis results will provide helpful information for better target policing and crime prevention policy such as police patrol scheduling regarding times and places covered.

The Journey to Crime: A Test of the Effects of Demographics on Crime Mobility

범죄여행에 관한 문헌들은 범죄자들이 자신들의 거처와 가까운 곳에서 범행을 한다고 가리키고 있다. 나아가서 빈집털이의 이동성에 관한 문헌들 역시 이러한 경향을 다시 확인해 주고 있다. 종전의 문헌들은 범죄이동성에 반영되는 인구동태학적 특성의 차이를 규명하려 했지만, 근래의 문헌들은 그러한 특성의 차이 규명에 실질적 노력을 보이지 않는다. 본 연구는 범죄여행에 내재하는 인구동태학적 특성의 차이를 재조명함을 목적으로 하고 있다. 남부 미국의 대도시에서 체포되어 형을 선고받은 331명의 빈집털이범들을 대상으로 수집한 데이터를 분석함으로써, 그 범죄자들이 자신들의 거처와 가까운 곳에서 범행을 하는지 여부와 아울러, 나이, 성별, 그리고 인종과 빈집털이를 위한 이동거리와의 상관관계를 파악하고자 한다. 분석된 데이터는 범죄자들이 자신들의 거처와 가까운 곳에서 범행을 하고, 범죄를 위한 이동거리의 차이는 인종과 성별에서 가장 크게 나타남을 보여준다. 이와 관련된 범죄정책과 전략도 논의하였다.The ‘journey to crime’ literature indicates that offenders commit crimes close to their homes. It is further confirmed by the mobility literature on the crime of burglary. The literature in the past identified demographic characteristic differences among crime mobility, while the modern literature has not devoted a substantial effort towards it. This article aims to revisit the idea of crime mobility and any inherent demographic differences in the journey to crime. Employing a sample of 331 arrested and charged burglary offenders from a large city in the southern United States, this study tests whether burglaries are most often committed close to an offender’s place of residence, as well as if there are identifiable age, gender, or race patterns in crime mobility for burglary. Our findings suggest that offenders remain close to their homes. Most significant, there are racial and gender differences in the distance traveled, in which regard crime policies and strategies are also discussed.

Burglary Crime Scene Rationality of a Select Group of Non-Apprehend Burglars

Burglary continues to yield low detection rates, and although the characteristics of how burglaries are committed has been investigated in some detail, less is known about how burglars avoid detection generally and in particular the activities of non-apprehended burglars. To investigate this issue, one can at least in principle investigate the special case of burglars who claim to have avoided apprehension in spite of the fact that they have committed a large number of burglaries over time. The approach taken here was to thematically analyze the interview data from a previous study comparing the crime scene movements of a small group of non-apprehended burglars with experienced but apprehended burglars. The results here from a thematic analysis of that previous study revealed marked differences in the rationales between the experienced, apprehended burglars and the experienced non-apprehended burglars when implementing different crime scene behaviors. A series of techniques and strategies emerges, which appear to aid in avoiding detection around the burglary scene and are summarized with implications discussed.

Spatial Pattern of Burglary in South Yorkshire Using Geographic Information System (GIS)

Burglary is an offence committed against others’ property and it is considered a violent crime. Nowadays to monitor and detect burglary crime geographic information system (GIS) is used broadly. The aim of this study is to analyses spatial pattern and spatial dependency of burglary in the study area by applying GIS techniques. For understanding the crime pattern better and creating plans for preventing and reducing crime and using the resources and places, sometimes might make greatest differences; the identification of hotspots in time is very important. The data for this study obtained from the secondary data; boundary shape file of the study area, socioeconomic data and burglary data for November 2012 were gained. The outcome of the study shows that the distribution of burglary is clustered. It is clear from the results that the rate of burglary strongly affects the percentage of unemployed people; also the percentage of non-white and young people (aged 20-24) does not significantly correlate with burglary.

A Case Study into NYPD's Burglary Crime Prevention Checklists

A Case Study into NYPD's Burglary Crime Prevention Checklists

The feasibility of using crime scene behaviour to detect versatile serial offenders: An empirical test of behavioural consistency, distinctiveness, and discrimination accuracy

PurposeTo test whether geographical, temporal, and modus operandi (MO) crime scene behaviours can be used to support behavioural case linkage (BCL) with crime series that contain several different types of offence.MethodsCrime scene data relating to 749 solved commercial burglaries and robberies were extracted from the databases of the Metropolitan Police Service, London, England. From these data, 2,231 linked crime pairs (containing two crimes committed by the same offender) and 273,422 unlinked crime pairs were created (two crimes committed by different offenders). Three measures of similarity were calculated for each crime pair: (1) the kilometre distance between crimes (intercrime distance [ICD]); (2) the number of days between crimes (temporal proximity [TP]); and (3) a statistical measure of similarity in MO behaviour (Jaccard's coefficient). Statistical tests of difference, binary leave‐one‐out logistic regression, and receiver operating characteristic analysis were used to determine whether the three measures of similarity could be used to distinguish between linked and unlinked crime pairs, some containing only burglaries (burglary pairs), some containing only robberies (robbery pairs), and some containing both burglaries and robberies (cross‐crime pairs).ResultsLinked and unlinked crime pairs could be distinguished with a high level of accuracy (AUCs > .90), with the highest accuracy when combining ICD, TP, and Jaccard's coefficient. These findings were replicated with the burglary pairs, robbery pairs, and cross‐crime pairs.ConclusionsOffender behaviour is sufficiently consistent and distinctive to support the use of BCL with versatile crime series, as well as with burglary crime series and robbery crime series.

Partially Supervised Spatiotemporal Clustering for Burglary Crime Series Identification

SummaryStatistical clustering of criminal events can be used by crime analysts to create lists of potential suspects for an unsolved crime, to identify groups of crimes that may have been committed by the same individuals or group of individuals, for offender profiling and for predicting future events. We propose a Bayesian model-based clustering approach for criminal events. Our approach is semisupervised, because the offender is known for a subset of the events, and utilizes spatiotemporal crime locations as well as crime features describing the offender's modus operandi. The hierarchical model naturally handles complex features that are often seen in crime data, including missing data, interval-censored event times and a mix of discrete and continuous variables. In addition, our Bayesian model produces posterior clustering probabilities which allow analysts to act on model output only as warranted. We illustrate the approach by using a large data set of burglaries in 2009–2010 in Baltimore County, Maryland.

Addressing issues of spatial spillover effects and non-stationarity in analysis of residential burglary crime

The aim of this paper is to address two critical but largely neglected issues in the spatial analysis of urban crime which are spatial spillover effects of crime penetrating neighborhood boundaries and non-stationarity regarding the relationships between contextual factors and neighborhood crime. We use a GIS-based spatial approach to normalize the estimate of burglary crime at block group level and use the geographically weighted regression (GWR) to investigate the correlates of neighborhood crime. Results suggest that the use of normalized measure of neighborhood crime helps better reveal the spatial patterns of burglary crime and the use of GWR accounts for the spatial variations of relationships between contextual factors and crime. In particular, the normalized measure of crime has implications for improving the measurement accuracy of the risk of crime across urban neighborhoods and can be applied to the spatial analysis of other socioeconomic issues such as housing foreclosures and environmental hazards which are also plagued by the spatial spillover issue when geographically contiguous data are analyzed.

Intelligence-Led Policing: The Evaluation of the Denver Police Department's Policy

This study assesses the intelligence-led policing model implored by the Denver Police Department. This study focuses on the crimes of burglary, motor vehicle theft, and robbery to identify the impact an intelligence-led policing model implemented by the Denver Police Department has on the cited crimes.

Spatial Heterogeneity, Social Capital, and Rural Larceny and Burglary

AbstractWe explore the role of social capital in explaining patterns of rural larceny and burglary crime rates. We find consistent evidence that higher levels of social capital tend to be associated with lower levels of rural property crime rates. We also find that there is significant spatial heterogeneity in the underlying data‐generating process. This spatial heterogeneity suggests that relying on global estimates from classical statistical methods, such as least squares, may lead to erroneous policy recommendations at the local level. We suggest that some of the inconsistencies in the ecological empirical criminology literature might be explained by spatial heterogeneity.

Crime Diffusion and Displacement: Measuring the Side Effects of Police Operations*

In 2005, the Camden, New Jersey, Police Department responded to concerns about crime with a series of high-visibility, directed, uniform patrol deployment initiatives. The department deployed extra resources on overlapping shifts into hotspot areas to counteract trends in burglary, violence, and drug crime. In situations such as this, where police employ directed and geographically targeted enforcement initiatives, both police and the public are often concerned about displacement; however, until recently no standard tool for measuring displacement was available. The weighted displacement quotient, despite some acknowledged methodological concerns, represents for the first time a systematic approach to the measurement of geographical displacement of crime. Using the weighted displacement quotient as part of the evaluation of the Camden initiative, researchers found a marked decrease in crime in the target area and evidence of a diffusion of benefits to the surrounding displacement buffer zone. This article examines the use of the weighted displacement quotient in the analysis of varying types of crime and seeks to address some of the methodological and statistical concerns highlighted by previous researchers. In particular, this article addresses issues of buffer area selection and evaluation. The Camden initiative serves as a case study to demonstrate the technique, as it is applied to drug, vehicle, gun, and violent crime, as well as overall crime in targeted areas of the city.

Retrospective analysis of violent crimes in Marmara, Turkey

PurposeThe purpose of this study is to determine the contribution of expert reports, which were prepared as a result of examining the evidence sent to Istanbul Criminal Laboratory, to the conclusion of judicial cases of burglary, homicide, and wounding in the provinces of Marmara Region between the years 2004‐2005.Design/methodology/approachIn this research, 6,249 judicial cases (murder, wounding, burglary) that occurred within the borders of Marmara Region during 2004‐2005 and were submitted to Istanbul Criminal Police Laboratory (KPL) have been subjected to evaluation according to the years (2004, 2005), the type of the case (murder, wounding, or burglary), whether any sexual assaults also occurred, the existence of the biological evidence (blood, saliva, skin residue, hair, tissue, semen, blood and similar biological material), and the conclusion of cases.FindingsWhen analyzing the crime types, it was seen that wounding and burglary were committed the most, respectively in 2004 and 2005. Out of total committed crimes in this period, homicide held the lowest percentage. The most evaluated biological evidence was blood. Sexual assaults realized together with violent crimes were on an average of 0.8 percent. By analyzing the biological evidence, the success in identifying the perpetrators of the cases was only 16 percent, which has to be evaluated carefully.Originality/valueFinding evidence at the crime scene and its proper investigation and submission to courts are extremely important. From this aspect, the expert reports of the Criminal Laboratories have an important level of impact on the conclusion of the cases. Commencing with the evidence collected from homicide, wounding and burglary crimes, which were committed in Marmara Region, it is necessary to evaluate the current situation and offer proposals for increasing its effectiveness.

The linking of burglary crimes using offender behaviour: Testing research cross‐nationally and exploring methodology

Purpose. The current study tests whether existing behavioural case linkage findings from the United Kingdom (UK) will replicate abroad with a sample of residential burglaries committed in Finland. In addition, a previously discussed methodological issue is empirically explored.Methods. Seven measures of behavioural similarity, geographical proximity, and temporal proximity are calculated for pairs of burglary crimes committed by 117 serial burglars in Finland. The ability of these seven measures to distinguish between pairs of crimes committed by the same offender (linked pairs) and different offenders (unlinked pairs) is tested using logistic regression and receiver operating characteristic (ROC) analysis. Two methodologies for forming the unlinked pairs are compared; one representing the ‘traditional’ approach used by research and, the other, a new approach that represents a potentially more realistic and statistically sound approach to testing case linkage.Results. A wider range of offender behaviours were able to distinguish between linked and unlinked crime pairs in the current Finnish sample than in previous UK‐based research. The most successful features were the kilometre‐distance between crimes (the intercrime distance), the number of days separating offences (temporal proximity), and a combination of target, entry, internal, and property behaviours (the combined domain). There were no statistically significant differences between the two methodological approaches.Conclusions. The current findings demonstrate that a wider range of offender behaviours can be used to discriminate between linked and unlinked residential burglary crimes committed in Finland than in the UK. The use of a more realistic and statistically sound methodology does not lead to substantial changes in case linkage findings.

From Beats to Tracts

In this article, the author addresses the spatial incompatibility between different types of data that is commonly faced in crime analysis research. Socioeconomic variables have been proved valuable in explaining crime behaviors and in predicting crime activities. However, socioeconomic data and crime statistics are usually collected and aggregated at different spatial zonations of geographical space, making the integration and analysis of these data difficult. Simple areal weighting interpolation technique, although frequently employed, often leads to unsatisfactory results due to the fact that most types of crime do not distributed evenly across space. Using 2007 burglary crime in Houston, Texas, as an example, the author illustrates a remote sensing approach to interpolating crime statistics from police beat enumeration district used by Houston Police Department to census tract defined by the U.S. Bureau of the Census.

Correlations between estimates of state IQ and FBI crime statistics

Previous research suggests that crime is negatively associated with IQ at the individual level and the aggregate state level. The purpose of the present study was to further explore the relationship between state IQ estimates and various categories of violent and property crimes. State demographic information including the gross state product, pupil/teacher ratio, and percent Black, Asian, and Hispanic were included in the correlational analyses. State IQ was significantly and negatively correlated with the violent crimes of murder, aggravated assault and robbery as well as the property crimes of motor vehicle theft, theft and burglary. Additionally, regression analyses were conducted for each crime significantly related to state IQ, controlling for significant state demographic variables. In general, results suggest that the prevalence of both violent and property crimes is associated with lower state IQs.

The Relationship Between Deprivation and Forensic Opportunities with Stolen Vehicles

Collection and interpretation of forensic intelligence (primarily through DNA and fingerprint identifications) is an integral part of the investigation of criminal offenses ranging from burglary and vehicle crime to major crime. The forensic contribution depends not only on the successful recovery of material, but also the ability to identify potential offenders and apply this intelligence to solve the crime. This study examines burglary and vehicle crimes investigated by Northamptonshire Police (U.K.) by analyzing relationships between deprivation of a crime location and the recovery and identification of DNA and fingerprint material. The results show that, for stolen vehicles, although significantly more forensic material (both DNA and fingerprints) is recovered and identified in more deprived neighborhoods, this does not lead to a corresponding increase in solved cases. These findings are considered in relation to previous studies, which have advocated the prioritization of resources at crime scenes most likely to yield forensic material.

The Effects of Deprivation on the Time Spent Examining Crime Scenes and the Recovery of DNA and Fingerprints

DNA and fingerprint identifications are now accepted as an integral part of the investigation of a wide range of criminal offences from burglary and auto crime to serious and major crime. Despite this, there is still much variation between U.K. police forces in the recovery of fingerprint and DNA material from crime scenes. Analysis of burglary and auto crime data for Northamptonshire, U.K., during a 3-year period has enabled an examination of the relationship between the deprivation of the neighborhood in which the crime was committed and the level of service provided by Crime Scene Examiners. The results indicate that the time spent examining a crime scene for forensic evidence is not affected by the deprivation of the neighborhood. Further, there is no statistical significance between deprivation and the recovery of fingerprints from the crime scene. The relationship between deprivation and DNA recovery is, however, statistically significant with DNA being recovered more frequently from less deprived neighborhoods.

Maximising the Opportunities to Detect Domestic Burglary with DNA and Fingerprints

The impact on the detection and reduction of domestic burglary by a prioritisation of forensic resources and processing over a six-month study period is examined. Targets were set and monitored for the twin factors of increased attendance at crime scenes and increased timeliness of processing both DNA and fingerprint samples. The results showed that it is possible to increase the number of primary detections derived from DNA and fingerprints with the DNA increase being statistically significant. This increase was accompanied by a decrease in reported domestic burglaries. After its completion, the longer term effect of the study on domestic burglary revealed a return to pre-study levels for both DNA and fingerprint detections although continuing reductions in DNA process times enable an increasing number of crimes to be detected with DNA. The results illustrate how a police force may run a focused forensic initiative to provide a short-term prioritisation on a ‘problem’ crime type such as burglary or auto crime where DNA and fingerprints can make a significant contribution to crime detection.

When Does Repeat Burglary Victimisation Occur?

Research consistently demonstrates that past victimisation is among the best predictors of future risk. Using recorded domestic burglary crime data from Victoria, Australia, analyses were conducted to examine temporal patterns of repeat burglary victimisation. The analyses focus on both time elapsed between incidents at the same location and the time of day that events occur, the latter previously unexamined in the literature. The time-course of revictimisation is as found hitherto: revictimisation occurs swiftly and the risk of repetition decays over time. Considering the time of day, in line with routine activities theory, the majority of incidents (first or follow-up events) occurred during the day. More interestingly, the results suggest that, relative to repeat burglaries that occur months after the first offence, those that occur within 7 days are more likely to occur at the same time of the day as the antecedent event. Moreover, the time course of revictimisation appears to vary for burglaries that occur at different times of the day. The results are discussed in relation to routine activities theory and with respect to their implications for crime reduction.

A Structured Portfolio Analysing the Crime of Burglary

Burglary is a high-volume crime, affecting around one in twenty-five households annually. In 1998 the Home Office launched a major crime reduction programme in England and Wales with a key element focussing on the reduction of burglary. It was hoped that this would discover the key element in reducing domestic burglary. So far, however, research has failed to determine the reasons for beginning and pursuing a career in burglary. This article attempt to provide a portfolio of the potential factors that could cause an individual to turn to property crime. It is important to look at these factors not as individual elements but as a framework of potential risk. A framework designed by Clarke (1977) is used to do this.