Spatial Distribution Of Crime Research Articles

Crime on the mass transit system in Hong Kong: a hotspots and harmspots trajectory approach

PurposeA growing body of literature focuses on crime hotspots; however, less is known about the spatial distribution of crime at mass transit systems, and even less is known about trajectory patterns of hotspots in non-English-speaking countries.Design/methodology/approachThe spatiotemporal behaviour of 1,494 crimes reported to the Hong Kong’s Railway Police District across a two-year period was examined in this study. Crime harm weights were then applied to offences to estimate the distribution of crime severity across the transit system. Descriptive statistics are used to understand the temporal and spatial trends, and k-means longitudinal clustering are used to examine the developmental trajectories of crime in train stations over time.FindingsAnalyses suggest that 15.2% and 8.8% of stations accounted for 50% of all counted crime and crime harm scores, respectively, indicating the predictability of crime and harm to occur at certain stations but not others. Offending persists consistently, with low, moderate and high counts and harm stations remaining the same over time.Research limitations/implicationsThese findings suggest that more localised crime control initiatives are required to target crime effectively.Originality/valueThis is one of the only studies focusing on hotspots and harmspots in the mass transit system.

Public transport stops and crime within the city space. The case of Stare Bałuty in Łódź

The goals of the study presented in the article draw attention to the role of public transport stops in the spatial distribution of crime in the Stare Bałuty estate in Łódź, Poland. Answers are provided to the questions of spatio-temporal structure of criminal acts committed within the estate, the influence zone of transport stops as well as the assessment and effects of environmental crime predictors in their vicinity. Crime location quotient (LQC) was used to assess the intensity of crime and identify the influence zone that attracts certain categories of crimes to the vicinity of stops. The influence of environmental predictors on the level of threat was identified and assessed on the basis of B. Czarnecki’s method. The variables used in the analysis initially spanned 739 crimes and 53 public transport stops evaluated with regard to 20 safety aspects and their impact on the pro-crime effects on the scale of location as well as various forms and functions of urban development. A strong negative influence of public transport stops ‒ attracting various categories of crime, mostly property theft ‒ was discovered. The negative influence of stops on the concentration of crime within 200 metres is reinforced by the existence of environmental crime predictors. The recommendations and discussions resulting from the findings should influence the policy of crime prevention on the level of object location, management and the maintenance of socio-spatial order in the vicinity.

Reinvestigating the relationship between cities and the spatial distribution of robbery: A tale of eight cities

PurposeThe law of crime concentration suggests cities have almost no impact on the spatial distribution of crime. This study reinvestigates the relationship between cities and the distribution of crime across the various micro-places and neighborhoods which compose these locations. MethodsWe observed robbery incidents reported to police departments across eight U.S. cities from 2015 to 2019. We calculated the spatial variability of the distribution of robberies attributed to census blocks (i.e., micro-places), census tracts (i.e., neighborhoods), and cities (i.e., macro-places) using variance partitioning techniques with multi-level negative binomial regression models. ResultsOur findings are mixed on the relationship between cities and the spatial distribution of robbery incidents. The descriptive analyses suggest a moderate influence of cities on measures of crime concentration. One of our modeling strategies estimates a larger impact while another strategy observes almost no contribution of cities to the total spatial variability. ConclusionsThis study supports previous research which demonstrates there are overwhelming similarities in the distribution of crime between cities and micro-places account for most of the spatial variability of patterns. While cities do not appear to have a major influence on distributions, future research should continue to clarify these mixed findings and provide a more compelling theoretical account of this relationship.

Recreating Human Mobility Patterns Through the Lens of Social Media: Using Twitter to Model the Social Ecology of Crime

Studies of neighborhood crime are often limited in their ability to account for the dynamic nature of human mobility, a central tenet of prominent theoretical perspectives on the spatial distribution of crime. Yet, recent work indicates the utility of social media data for estimating the size and composition of such ambient population. In the present study, we assess whether four Twitter-derived measures are associated with crime counts across 2,348 block groups. Specifically, we focus on the density of Twitter users (and tweets), as well as the proportion of Twitter users (and tweets) that are “insiders.” We inferred Twitter users’ “insider” location from the block group in which they tweeted most frequently.

URBAN MORPHOLOGY AND CRIME PATTERNS IN URBAN AREAS: A REVIEW OF THE LITERATURE

The emerging research on urban morphology provide sufficient explorations that result in a better understanding of crime areas and fear of crime in cities. Despite the effort so far, the existing literature on morphology of crime areas and pattern of crime presents different perspectives to the study of crime and spaces, reflecting the varied field of urban morphological research. There is a need to understand these perspectives in view of their directions and inherent limitations for effective understanding of crime pattern and urban morphogenesis in cities. The focus of the paper is on the understanding of different perspectives in the study of crime pattern and urban morphology in setting up an effective mechanism for crime prevention and control. Twenty (20) paper articles and six (6) theses published between 2010 - 2021 were selected based on the Environmental criminological research perspectives from the field of Geography, Urban Planning, Urban Design, Landscape Architecture and Architecture; and systematically reviewed based on their characteristics and then classified according to their relevance to environmental criminology for analysis and drawing of inferences. The findings indicated that, there is inadequate empirical research on the influence of urban morphology on crime pattern in cities. Therefore, the paper recommends for further research to focus on exploring the various links between elements of urban morphology and spatial distribution of crime in areas, and the explanations that could provide for effective crime prevention and control in cities.

Variations in the spatial distribution of crime events in an urban environment during the COVID-19 lockdown

ABSTRACT The article presents the impact of the COVID-19 pandemic on selected types of crime in Krakow and their spatial distribution during the lockdown period during the spring of 2020. We compared crimes committed over a three-month period from March 15 up to 15 June 2020 with crimes committed during the corresponding periods of previous years, i.e. in 2015–2019. To characterize their spatial distribution, we used the Nearest Neighbor Analysis method (NNA). In the next stage of the study, an intensity distribution map was prepared for five different crime categories in 2015–2019 using the kernel function method. The point data layer from 2020 was then superimposed on the intensity layer thus formed. The final step was to examine how generators/attractors affect the spatial clustering of crime before and during the pandemic. These two analyses allowed us to identify variation in those areas with the highest concentration of crime events (“hotspots”) that occurred as well as the impact of generators/attractors on the spatial distribution of crimes. The changes in crime patterns as a result of the pandemic restrictions were compared with existing criminological theories.

Blowing in the wind? Testing the effect of weather on the spatial distribution of crime using Generalized Additive Models

Oslo, the capital of Norway, is situated in a North European cool climate zone. We investigate the effect of weather on the overall level of crime in the city, as well as the impact of different aspects of weather (temperature, wind speed, precipitation) on the spatial distribution of crime, net of both total level of crime, time of day and seasonality. Geocoded locations of criminal offences were combined with data on temperature, wind speed, and precipitation. Generalized Additive Models (GAMs) allowed us to map level of and the spatial distribution of crime, and how it was impacted by weather, in a more robust manner than in previous studies. There was slightly more crime in pleasurable weather (i.e. low precipitation and wind speed and high temperatures). However, neither temperature, precipitation nor wind speed impacted the spatial distribution of crime in the city.

Spatial distribution of crimes in urban areas: An insight from Sri Lanka

Similar to other Asian countries, it is forecasted that the urban population in Sri Lanka will continue to increase at an accelerating rate and the majority will be living in urban areas by 2022. Urban crime which is a major challenge that cities face is assumed to spread with the increasing population. They are clustered geographically generating a substantial economic struggle. The related theories argue that criminal opportunity is the root cause of crime and physical environmental design makes an influence on the criminal opportunity. Therefore, a need of identifying how the built environment and different land uses become an opportunity and make an impact on the spatial distribution of urban crimes is evident. This study aims to do a hotspot analysis within the Colombo Municipal Council Area, Sri Lanka to identify the spatial relationship of urban crimes with different land uses. The data on 627 crime incidents occurred in 2018 were obtained from crime records of police stations in Colombo North, South and Central police divisions and were analyzed using Kernel Density Estimation in Geographical Information Systems (GIS) software. As per study findings, seven wards were identified as crime hotspots. Further, findings reveal that robbery and drug arrest incidents are common around low-income residential housing areas while property theft records are common around hospitals, cinemas and concentrated commercial areas. Vehicle thefts are often recorded near lakes, offices and playgrounds whereas housebreakings are recorded near housing schemes. Finally, implications to mitigate these impacts were also presented. Keywords: crime types, GIS, land use, spatial distribution, Sri Lanka, urban crime

Examining Time-Variant Spatial Dependence of Urban Places and Shootings.

Place-based interventions are increasingly implemented to address firearm violence. While research on the social determinants of health and criminological theories suggest that the built environment significantly influences health outcomes and the spatial distribution of crime, little is known about the attraction between urban places and shootings. The present study adds to the literature on firearm violence and micro-place research by exploring the spatial dependence in a Midwest metropolitan area between shootings and bus stops, vacant properties, alcohol outlets, and other locations that have been theoretically or empirically linked to firearm violence. The G-function and Cross-K function are used to characterize the univariate clustering of shootings and bivariate attraction with other locations, respectively. Bus stops, blighted vacant properties, alcohol outlets, and businesses/residential locations participating in a public-private-community initiative to reduce crime exhibited significant locational dependence with shootings at short distances. Attraction between on-premises alcohol outlets and shootings was observed only during the night. No attraction was found between schools and shootings. The findings reaffirm the importance of place-based research-especially at the micro-place level-and suggest that certain urban places may be appropriate targets for interventions that modify existing physical and/or social structures.

Uneven spatial distribution of crime and annual changes in major Japanese cities

Uneven spatial distribution of crime and annual changes in major Japanese cities

Examining the Spatial Distribution of Crime by Victim Characteristics

ABSTRACT It is well known that victims do not consistently report crimes. More problematically, victims in disadvantaged neighborhoods with high percentages of minority residents are not likely to report at high rates. Crime mapping is often considered at an aggregate level; however, the present study examines crime from a victim-perspective to better understand how crime is distributed by victim characteristics. Results reveal interesting similarities and differences in the geographical distribution of crime when disaggregated by victim race. Implications and directions for future research are also discussed.

Spatio-temporal analysis of urban crime leveraging multisource crowdsensed data

Crime analysis is important for social security management. With the advance of crowd sensing techniques, abundant multisource crowd sensed data could be used for crime analysis. The occurrence of crimes usually has some patterns in terms of temporal and spatial aspects. Investigating the spatio-temporal correlation of crimes could provide more useful cues for crime analysis and help discover underlying crime patterns. In this paper, we conduct a spatio-temporal study to understand urban crimes leveraging multisource crowd sensed data, including crime data, meteorological data, POI distribution, and taxi trips. Specifically, we first present monthly temporal trends and spatial distribution of crimes. We then investigate the spatio-temporal correlation using meteorological data (e.g., weather conditions and air temperature) and POI distribution and taxi trips. It is found that taxi trips and air temperature have a strong correlation with the crime, and some POI categories have a valuable correlation with the crime, e.g., College & University. We also find that Overcast days would witness more crime than other weather conditions.

Environmental crime predictors and the spatial distribution of crime. The case of stare Baluty in Lodz, Poland

The article refers to various studies on the creation of safe spaces as well as works on the influence of land-use on the distribution of crime in urban space. The goal of the study is to identify places and facilities which constitute a potential threat to safety and impact the spatial distribution of crime. An analysis of relationships between various types of crime predictors and the spatial distribution of crimes at the address-level has also been made. The most important conclusion drawn from the study is that the distribution of crime predictors strongly impacts the presence of crime in their direct vicinity and this influence on crime gradually lessens as the distance increases. The influence of such crime predictors as honeypots and public facilities on attracting crime as well as movement predictors and conflicts of land use on repelling crime was determined.

The Relationship between Crime Prevention Through Environmental Design (CPTED) and Criminal Geography (CG)

Knowledge of crime trends and permanent monitoring of criminal acts are the fundamentum of successful crime prevention. The need of searching of structure, dynamic and volume of crime is not new-fangled, as the examination of relationship between spatial distribution of crime and crime prevention through environmental design (CPTED). However, the philosophy of CPTED has changed significantly over the last two decades, with focus on the role of individuals and the communities, their involvement and the need to encourage them to act. How has this paradigm shift changed the relationship between these two areas? How trivial will be in the future to use CPTED tools in those areas, where we detect greater criminal infection?

Developing a fractal model for spatial mapping of crime hotspots

Determining the precise area of urban crime hotspots, where the crime rate is significantly different from the surrounding area, is one of the essential applications of crime analysis. Besides, the classification of the spatial distribution of crimes can make spatial analysis more applicable to the police. In this regard, the present study examined the spatial distribution of five types of burglary in Zanjan city, NW Iran. Kernel density estimation (KDE) was initially applied to identify the crime distribution in the raster format. Because of producing a continuous-value surficial signature, the KDE model is not able to determine the exact borders of different crime density. To address this issue, the concentration-area (C-A) fractal model is proposed in this study as a frequency–spatial method for class designation of crime density. Thus, based on the interpolated maps derived from KDE, the C-A log–log plots consisting of the values of the gridded density maps of burglary crimes versus their occupied area were generated. Then, different threshold values and their corresponding criminal classes were delineated and mapped according to the drawn log–log plots. To evaluate the performance of the proposed fractal model, two GIS-based models, namely natural breaks classification (NBC) and equal interval classification (EIC), were generated over the KDE values. Then, a success rate curve was plotted as a validation method for quantitative evaluation of generated models based on the crime events. The obtained results revealed the benefit of the C-A fractal model in distinguishing different discretized classes of crime density over two other models. This can help to select the appropriate strategy to control and prevent crime occurrences in every crime density class.

The influence of extreme weather conditions on the magnitude and spatial distribution of crime in Tshwane (2001–2006)

ABSTRACTThis article examines the influence of extreme weather conditions on the magnitude and spatial distribution of violent, sexual and property crime in Tshwane, South Africa from 2001 to 2006. Analysis of variance (ANOVA) is initially used to identify whether there are significant differences in the mean amount of crimes (violent, sexual and property) committed on days stratified by temperature and rainfall extremes. Next, a spatial point pattern test is used to determine the spatial similarity of violent, sexual and property crime on temperature and rainfall days classified as low, random, and high. Results indicate a strong association between temperature and criminal activity, and a less significant association between rainfall and crime. The spatial distributions of all types of crime are found to differ significantly depending on the type of weather extreme observed. The results of this study has the potential to assist law enforcement agencies to better understand how weather affects crime patterns in urban areas in South Africa and develop and implement appropriate crime prevention measures.

Analyzing Space-Time Dynamics of Theft Rates Using Exchange Mobility

A critical issue in the geography of crime is the quantitative analysis of the spatial distribution of crimes which usually changes over time. In this paper, we use the concept of exchange mobility across different time periods to determine the spatial distribution of the theft rate in the city of Wuhan, China, in 2016. To this end, we use a newly-developed spatial dynamic indicator, the Local Indicator of Mobility Association (LIMA), which can detect differences in the spatial distribution of theft rate rankings over time from a distributional dynamics perspective. Our results provide a scientific reference for the evaluation of the effects of crime prevention efforts and offer a decision-making tool to enhance the application of temporal and spatial analytical methods.

Land use impact on spatial distribution of crime

Land use impact on spatial distribution of crime

Analyzing and Predicting Spatial Crime Distribution Using Crowdsourced and Open Data

Data analytics has an ever increasing impact on tackling various societal challenges. In this article, we investigate how data from several heterogeneous online sources can be used to discover insights and make predictions about the spatial distribution of crime in large urban environments. A series of important research questions is addressed, following a purely data-driven approach and methodology. First, we examine how useful different types of data are for the task of crime levels prediction, focusing especially on how prediction accuracy can be improved by combining data from multiple information sources. To that end, we not only investigate prediction accuracy across all individual areas studied, but also examine how these predictions affect the accuracy of identified crime hotspots. Then, we look into individual features, aiming to identify and quantify the most important factors. Finally, we drill down to different crime types, elaborating on how the prediction accuracy and the importance of individual features vary across them. Our analysis involves six different datasets, from which more than 3,000 features are extracted, filtered, and used to learn models for predicting crime rates across 14 different crime categories. Our results indicate that combining data from multiple information sources can significantly improve prediction accuracy. They also highlight which features affect prediction accuracy the most, as well as for which particular crime categories the predictions are more accurate.

Football pollution: an investigation of spatial and temporal patterns of crime in and around stadia in England

Inspired by theories of environmental criminology, this paper is concerned with the criminogenic potential of football matches. Do matches generate patterns of crime within grounds and beyond them? If so, over what period and over what distance are these effects produced? Police-recorded data for five football stadia for a 6-year timeframe (2005–2010) are examined using non-parametric permutation tests. The spatial extent of any patterns are quantified and used to further examine differences in the temporal distribution of crime and incidents. Change in the spatial distribution of crime and incidents occurred around all five stadia and did so during those periods when the ambient population was elevated on match days. The results provide further support for theories of environmental criminology, suggesting that there is a higher risk of crime and incidents in the areas immediately around stadia during the hours when matches take place.