The concentration of urban crime in space by race: evidence from South Africa

Crime inequality in neighborhoods by race is blamed on social inequalities borne out of segregation and economic discrimination. South Africa is a country synonymous with racial-spatial segregation and discrimination as a result of legislatively enforced policies of the former apartheid government. This study examines whether urban crime inequalities by race exist in the city of Tshwane, South Africa and identifies the empirical causes of these crime inequalities. Violent and sexual crime was found to concentrate in Black African neighborhoods, while property crime was concentrated in neighborhoods classified as “Mixed”. The causes of crime in neighborhoods were found to vary across racial groups with results suggesting non-uniformity in the extent to which the various constructs impact crime based on race. The results challenge the notion that segregation and economic discrimination uniformly impacts affected communities. Explanations for the findings are provided in the context of an increasingly eclectic post-apartheid South African city.     

Hotspots vs. harmspots: Shifting the focus from counts to harm in the criminology of place

The prevailing pattern in much of the social sciences, including geography and criminology, relies on count data. “Hotspots” — geospatial areas with disproportionally more crime than the rest of the city — are usually identified by the number of events in these areas. Yet no attention is given to their severity, or any other weighting system of harm, despite the common-sense view that not all crimes are created equal. To illustrate the value of focusing on harm in addition to count data, we turn to a spatial analysis of crime by observing crime concentrations (hotspots) against harm concentrations (harmspots), across fifteen councils in the United Kingdom. The definition of “harm” is based on the Sentencing Guidelines for England and Wales, as each crime category (n = 415) attracts a different severity weight. Both “hotspots” and “harmspots” are defined as being at least 2 standard deviations from the mean distribution within each city: This procedure creates comparable datasets. The data suggest that half of all crime events are concentrated within 3% of all street segments in the selected councils, yet harm is even more heavily concentrated, with half of all harm located in just 1% of each council [OR = 3.49; 95% CI 3.268–3.728]. The intra-unit variance was also reduced by approximately half — from 0.75% to 0.45%. We discuss the implications of using harm, in addition to counts, for research and policy by arguing that a shift in focus is required both for the development of theories and for cost-effective prevention strategies.     

Spatial conjunctive analysis of (crime) case configurations: Using Monte Carlo methods for significance testing

While research has repeatedly demonstrated how spatial distributions of crime can be shaped by the presence of facilities such as bars and public transport hubs, the joint influence of different facility types has rarely been explored. Spatial conjunctive analysis of case configurations (also known as qualitative comparative analysis) offers a means to identify the combinations of facility types that are most commonly found around crime events, and has been used in a small number of studies focusing on street robbery. This study extends this limited evidence base by implementing a significance test based on the Monte Carlo method using street robbery data for Austin, Texas. The results show that some of the top-ranking facility type combinations had observed frequencies that were not significantly greater than chance expectations. The accurate identification of the highest-risk environments has important implications for crime prevention.     

A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery

ABSTRACT

Accurate crime prediction can help allocate police resources for crime reduction and prevention. There are two popular approaches to predict criminal activities: one is based on historical crime, and the other is based on environmental variables correlated with criminal patterns. Previous research on geo-statistical modeling mainly considered one type of data in space-time domain, and few sought to blend multi-source data. In this research, we proposed a spatio-temporal Cokriging algorithm to integrate historical crime data and urban transitional zones for more accurate crime prediction. Time-series historical crime data were used as the primary variable, while urban transitional zones identified from the VIIRS nightlight imagery were used as the secondary co-variable. The algorithm has been applied to predict weekly-based street crime and hotspots in Cincinnati, Ohio. Statistical tests and Predictive Accuracy Index (PAI) and Predictive Efficiency Index (PEI) tests were used to validate predictions in comparison with those of the control group without using the co-variable. The validation results demonstrate that the proposed algorithm with historical crime data and urban transitional zones increased the correlation coefficient by 5.4% for weekdays and by 12.3% for weekends in statistical tests, and gained higher hit rates measured by PAI/PEI in the hotspots test.     

Fear,crime, and space: The case of Viçosa,Brazil

Crime is both a factual and perceptual component of the urban landscape, seemingly both a societal pathology and the consequence of economic disparity between social groups. Crime has a spatial structure that can be revealed by mapping. Urban crime has a spatial multiplier effect that changes the values and perceptions of how people see urban space, and which jeopardizes the quality of life of a city's inhabitants. In this research we examine the question of whether the geography of actual criminal acts is echoed by peoples' perceptions of crime, what might be termed their “spaces of fear”. We ask how the fear of crime is associated with reported urban crime. Urban crime incidents have been increasing in Viçosa, Minas Gerais, Brazil. We assembled crime information about Viçosa from two sources: first, crime as reported to the police and second, crime as perceived by city residents and measured by surveys and interviews. Reported criminal acts reveal a clustered geography, focusing particularly on the Downtown area, where there is a concentration of urban wealth and potential victims are more numerous. Offenses against property were focused on Downtown, while offenses against the person were located mostly in peripheral areas. The widespread feeling of insecurity in the city's neighborhoods, reflecting the fear of becoming a victim of violence and crime, was common throughout the city. Results confirmed the conclusion of past studies showing that the fear of violence and crime are not directly related to increasing numbers of criminal reports. Sites with higher incidence of crimes are not places with higher levels of fear. Rather than being geographically explainable “spaces of fear”, the spatial distribution of the fear of violence and crime appears to be unrelated in Viçosa, and neither is clustered or dispersed in any measurable way.     

A population cartogram of New Zealand

The authors use 1981 census data to create a cartogram showing the counties of New Zealand in proportion to their population.     

Integrating multi-source remotely sensed datasets to examine the impact of tree height and pattern information on crimes in Milwaukee,Wisconsin

There have been a great number of debates about the impacts of trees on crimes: some researchers believed that trees are a crime facilitator because of the concealment provision for potential criminals, while others argued that they are a crime deterrent because of the increased surveillance possibility and the therapeutic effect on psychological fatigue. To better answer this question, this study incorporated detailed tree features by using multi-source remotely sensed data at a very high resolution into environmental criminology analysis across the entire City of Milwaukee. Trees were extracted from aerial photographs, and broken down into two categories based on their heights to consider the effects of tree height on view obstruction. By controlling for confounding socioeconomic variables, the relationship between crimes and a series of composition and configuration indicators of trees with different height were investigated by using global and local spatial regressions. Results from classic and spatial statistical techniques finds complicated relationship between crimes and trees, which can be summarized in two aspects. First, the mixed effects of trees can be observed among different crime types. Second, the trends of spatial nonstationarity of the composition and configuration of trees with different heights were observed across the entire study area. The study outcomes could provide reasonable implications for making appropriate policies for crime prevention through environmental design to strengthen neighborhoods and communities in a city.     

Fear of crime, cultural threat and the countryside

Summary This paper argues that the study of crime and the fear of crime in rural areas reveals much about the geography of crime, policing and rural society. Drawing upon a crime and safety survey conducted with residents of a rural parish in Worcestershire it establishes a link between fear of crime and 'cultural threats' to residents' dominant constructions of rurality. It concludes by considering the 1998 Crime and Disorder Act and its implications for rural policing and society.     

Assessing the social context of wildfire-affected areas. The case of mainland Portugal

Wildfires cause different impacts, depending on the conditions and resilience level of the exposed communities. Wildfire occurrence in mainland Portugal was assessed with regard to socioeconomic and demographic parameters, to identify the most distinctive conditions of fire-affected areas, without implying the existence of causal relationships. The latest population and agriculture census data were used to retrieve conditions at the civil parish level, regarding demographic patterns, social and labor conditions, physical structures and agricultural activities. To identify differences between parishes, two groups were created with the communities that showed the highest and lowest 20% of wildfire incidence between 2007 and 2014, separately for density of fire events and for burned area. A stepwise approach based on classification trees and random Forest methods was applied to identify the best discriminant variables between the groups. First, irrelevant variables were removed by an interactive process based on misclassification rates. The second step used random Forest analysis to the remaining variables to evaluate their importance in distinguishing the groups. In the final step, cluster analysis was applied to test the correspondence between the clusters created with the selected variables and the initial groups. Results showed that parishes with higher fire density have higher population density, higher proportion of young and educated people, larger families and more overcrowded buildings. On the contrary, parishes with larger burned area are less populated, less attractive to foreigners, have a higher proportion of elderly people, more degraded housing conditions and agricultural activities, visible in the density of sheep and goat and pastures, are still relevant. The cluster analysis demonstrated a better performance of the model for wildfire density, revealing a strong association with socioeconomic dynamics with an agreement above 0.85, much higher than for burned areas which is 0.29. Overall, the spatial distribution of wildfire impacts is framed by societal settings and particular conditions must be further understood to improve the coping capacity of affected communities.     

The crime kaleidoscope: A cross-jurisdictional analysis of place features and crime in three urban environments

Research identifies various place features (e.g., bars, schools, public transportation stops) that generate or attract crime. What is less clear is how the spatial influence of these place features compares across relatively similar environments, even for the same crime. In this study, risk terrain modeling (RTM), a geospatial crime forecasting and diagnostic tool, is utilized to identify place features that increase the risk of robbery and their particular spatial influence in Chicago, Illinois; Newark, New Jersey; and Kansas City, Missouri. The results show that the risk factors for robbery are similar between environments, but not necessarily identical. Further, some factors were riskier for robbery and affected their surrounding landscape in different ways that others. Consistent with crime pattern theory, the results suggest that the broader organization of the environmental backcloth affects how constituent place features relate to and influence crime. Implications are discussed with regard to research and practice.     

The use of predictive analysis in spatiotemporal crime forecasting: Building and testing a model in an urban context

Police databases hold a large amount of crime data that could be used to inform us about current and future crime trends and patterns. Predictive analysis aims to optimize the use of these data to anticipate criminal events. It utilizes specific statistical methods to predict the likelihood of new crime events at small spatiotemporal units of analysis. The aim of this study is to investigate the potential of applying predictive analysis in an urban context. To this end, the available crime data for three types of crime (home burglary, street robbery, and battery) are spatially aggregated to grids of 200 by 200 m and retrospectively analyzed. An ensemble model is applied, synthesizing the results of a logistic regression and neural network model, resulting in bi-weekly predictions for 2014, based on crime data from the previous three years. Temporally disaggregated (day versus night predictions) monthly predictions are also made. The quality of the predictions is evaluated based on the following criteria: direct hit rate (proportion of incidents correctly predicted), precision (proportion of correct predictions versus the total number of predictions), and prediction index (ratio of direct hit rate versus proportion of total area predicted as high risk). Results indicate that it is possible to attain functional predictions by applying predictive analysis to grid-level crime data. The monthly predictions with a distinction between day and night produce better results overall than the bi-weekly predictions, indicating that the temporal resolution can have an important impact on the prediction performance.     

Street profile analysis: A new method for mapping crime on major roadways

Street profile analysis is a new method for analyzing temporal and spatial crime patterns along major roadways in metropolitan areas. This crime mapping technique allows for the identification of crime patterns along these street segments. These are linear spaces where aggregate crime patterns merge with crime attractors/generators and human movement to demonstrate how directionality is embedded in city infrastructures. Visually presenting the interplay between these criminological concepts and land use can improve police crime management strategies. This research presents how this crime mapping technique can be applied to a major roadway in Burnaby, Canada. This technique is contrasted with other crime mapping methods to demonstrate the utility of this approach when analyzing the rate and velocity of crime patterns overtime and in space.     

ZG市街头抢劫者作案地选择及其影响因素研究

以往关于作案地选择的研究,缺乏考虑不同属性群体间的空间差异。以中国ZG市为例,利用离散空间选择模型,基于不同年龄属性的视角,进行街头抢劫者作案地选择及影响因素的对比分析,并据此提出犯罪防控建议。研究发现：① 不同年龄的街头抢劫者作案地选择存在显著的空间差异。即少年抢劫者趋向在劳动密集型产业集聚区和中小学密集区作案,而年轻的成年抢劫者仅趋向于劳动密集型产业集聚区,但成年抢劫者的作案地却偏向于客运站所在社区及其周边地区。② 年龄相关的活动节点、周围人口的监护作用和青少年人口比例是形成这种空间差异的主要因素。研究结果对犯罪防控与社会治理具有重要的参考意义,如：① 在青少年抢劫者频繁作案的劳动密集型产业集聚区,调控网吧、酒吧等年龄相关活动节点的数量。② 在成年抢劫者作案密集的客运站及其周边社区,规划一定数量周围人口的持续存在,以发挥出更好的监护作用。③ 在青少年人口比例较高的社区,通过问题青少年的摸底调查,加强精准引导与帮扶。论文首次验证了不同年龄的街头抢劫者作案地选择差异及成因,并在理论上弥补了犯罪者作案地选择缺乏细分人群的不足。     

2000年以来中外犯罪地理研究进展回顾与展望

以“Web of Science^TM核心合集”和CNKI核心文献库为数据源,运用CiteSpace软件进行文献计量分析,从发文时间、地区分布、学科分布、研究机构、关键词共现与高被引文献等方面,总结比较了2000年以来中外犯罪地理研究进展,并展望了未来的研究趋势。结果发现：1）国内外犯罪地理发文量整体呈现持续增长态势,美国发文量首位度明显。学科分布国外较为广泛,国内相对集中,且存在较大发展空间。研究机构之间的合作网络国外较强,国内机构联系较弱,后续研究力量正处于培育发展阶段。2）不同时期国内外研究关注的热点不同：国外侧重于暴力犯罪、恐怖主义犯罪、因种族歧视和性别歧视等引发的多类型犯罪研究,从微观到宏观,涉及地区、国家甚至全球层面;国内聚焦于城市社区“两抢一盗”犯罪、省域拐卖儿童犯罪和毒品犯罪等类型,微观和宏观并举,实证案例研究逐渐增多。3）随着多学科的交叉融合发展,国内外犯罪地理发展势头良好。犯罪分布模式、空间防控对策与犯罪风险模拟仍是当下较为活跃的研究议题,“3S”技术开发和大数据应用将成为犯罪地理研究的两条并行趋势线。未来需要以综合性思维审视犯罪地理环境,持续关注犯罪地理研究的潜在领域。同时,信息技术发展与计量模型应用为犯罪地理带来新契机,必须立足于当下国际社会环境,加强个人、组织和团体机构之间的研究合作,交流和分享经验成果,探索多样化的犯罪防控模式,并采取全球合作的方式应对区域所面临的犯罪挑战。     

Crime risk in urban neighbourhoods: the use of insurance data to analyse changing spatial forms

Summary The recent British Crime Surveys have confirmed that there are significant spatial variations in the distribution of crime risk. However, it is notoriously difficult to represent the spatial patterns in Britain convincingly, owing to the statistical inadequacy of the official crime data. This paper discusses the use of home contents insurance data as a proxy measure of crime risk, and examines the changing spatial distribution of crime risk in the two Northern conurbations of Merseyside and Greater Manchester. The analysis provides an explicit urban focus in order to establish links between the spatial distribution of crime risk and other patterns of deprivation or inequality in the urban environment. Since insurance data is used as a proxy measure of crime risk in the Department of the Environment's Index of Local Conditions, this analysis serves as an interesting basis for both academic and policy discussion.     

The domestic divide: Access to the Internet in New Zealand

We use unit records of the 2006 census to show that access to the Internet in the home varies geographically in New Zealand primarily as a result of demographic and socio‐economic differences among individuals. Of particular significance is the much lower rates of domestic access experienced by Māori and Pacific Island individuals even after controlling for differences in their age, gender, education, income, occupation and settlement type. While differences in Internet access by ethnicity has been noted before, it is the magnitude and persistence of this difference in New Zealand after controlling for correlated factors that renders this study unique. Our results have important implications in an education environment increasingly reliant on Web access, but they also raise questions about the extent of access to the Internet outside the home.     

Social Democracy and Contextual Unemployment: New Zealand Labour in 1990

This paper examines the spatial implications of social-democratic policy transformation. It does so by exploring the political consequences of residential contextual unemployment engendered by a Labour government which had once been dedicated to maintaining full employment. Faced with economic crisis, as Przeworski's model predicts [Capitalism and social democracy, Cambridge University Press, Cambridge (1985)], New Zealand Labour, beginning in 1984, abandoned its traditional social-democratic statist policies, including the maintenance of full employment, and allowed unemployment to skyrocket under its stewardship. This meant subjecting its supporters to significant contextual cross-pressures, since many residential neighbourhoods became characterised by both high concentrations of Labour partisans, and by those recently unemployed by Labour's new market-liberal policies. Using original survey data merged with New Zealand census data, empirical findings show that residual partisan loyalties and a lack of a major party alternative constrained respondents' partisan disaffection, while channelling their disillusionment into both minor party voting and systemic, governmental criticisms - likely fuelling New Zealand's drive for electoral reform and a new system of proportional representation.     

Leveraging parallel spatio-temporal computing for crime analysis in large datasets: analyzing trends in near-repeat phenomenon of crime in cities

ABSTRACT

Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis.     

Spatial Scale and the Geography of Tobacco Smoking in New Zealand: A Multilevel Perspective

Smoking in New Zealand is more common in deprived areas and in areas with a significant Maori population. Despite its status as a major health problem there has been little work investigating this apparent geography of smoking Data from the 1996 Census is used to construct a multilevel ‘proportions‐as‐responses’ model of smoking prevalence. This enables an exploration of the geography of smoking at different spatial scales. Levels within the model distinguish contextual variation between local authorities, census area units and meshblocks. Particular account is taken of the influence of deprivation and ethnicity on smoking. Results confirm the importance of ethnicity and deprivation and indicate that cross‐level interaction between meshblock and census area unit measures is significant. They also challenge crude stereotypes about the apparent geography of smoking and suggest that, while levels of smoking may be high in parts of North Island, they are less high than might be expected given the socio‐demographic composition of the areas concerned. Conversely, smoking is more prevalent than expected in parts of South Island. The paper notes the health policy implications of these emergent geographies.     

Fortress Australia? (In)security and private governance in a gated residential estate

Part of a broader trend towards all-inclusive master planned developments, gated residential estates are an intensely private form of residential development with a degree of securitisation. Gated residential estates have been the topic of intense debate in urban planning and policy circles and the target of fierce criticism for potential exclusionary outcomes as fearful residents lock themselves away from the ills of wider urban society. Crime, a fear of crime and the need for security dominate discussions and understandings of gated residential developments in Australia without much empirical validation. This paper poses two key research questions: does fear of crime and need for increased security drive residents towards gated estates; and what are the lived experiences of security, gates and crime once residing within a gated estate? Based on in-depth research in Macquarie Links (one of Sydney's largest gated estates) this paper offers insights into the lived dimensions of gated estates. The paper explores the attractions and realities of security services and infrastructure, private control over the residential environment and the importance placed by the residents on the ability to protect the nature of their neighbourhood and to protect themselves from any ‘unwanted’ activities or groups. The discussion in this paper demonstrates that for the residents in the study, residing in a secure residential neighbourhood is less about the role and place of physical security and security services, and more to do with protection afforded by the private governance structure of the neighbourhood.