A new information theoretical measure of global and local spatial association

In this paper a new measure of spatial association, the S statistics, is developed. The proposed measure is based on information theory by defining a spatially weighted information measure (entropy measure) that takes the spatial configuration into account. The proposed S-statistics has an intuitive interpretation, and furthermore fulfills properties that are expected from an entropy measure. Moreover, the S statistics is a global measure of spatial association that can be decomposed into Local Indicators of Spatial Association (LISA). This new measure is tested using a dataset of employment in the culture sector that was attached to the wards over Stockholm County and later compared with the results from current global and local measures of spatial association. It is shown that the proposed S statistics share many properties with Moran's I and Getis-Ord Gi statistics. The local Si statistics showed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatial association. The statistics can also be extended to bivariate distributions. It is shown that the commonly used Bayesian empirical approach can be interpreted as a Kullback-Leibler divergence measure. An advantage of S-statistics is that this measure select only the most robust clusters, eliminating the contribution of smaller ones composed by few observations and that may inflate the global measure.Global and local measure of spatial association, LISA, S-statistics, Gi statistics, Moran's I, Kullback-Leibler divergence,

Exploring offence statistics in stockholm city using spatial analysis tools

ABSTRACT The objective of this paper is to investigate changes in offence patterns in Stockholm City using methods from spatial statistics. The paper has two parts. The first is a brief description of methodological procedures to obtain robust geographical units for spatial statistical analysis. The second part focuses on a discussion of the results of different types of spatial statistical analyses of offence patterns for Stockholm City. Standardised offence rates (SOR) are calculated and mapped using GIS for three offences: residential burglary, theft of and from cars and vandalism. The Getis-Ord statistic is used to identify crime clusters or hot spots and finally offence patterns are analysed as a function of socio-economic variables using the linear regression model. The findings of previous Swedish studies on crime patterns, mostly by Wikström (1991), and the insights provided by North American and British theories on crime patterns provide a background for this study. Results suggest that whilst there have been no dramatic changes in the geographies of these offences in Stockholm City during the last decade, there have been some shifts both in terms of geographical patterns and in their association with underlying socio-economic conditions.

Rural Crime and Community Safety

Crime is often perceived as an urban issue rather than a problem that occurs in rural areas, but how far is this view tenable? This book explores the relationship between crime and community in rural areas and addresses the notion of safety as part of the community dynamics in such areas. Rural Crime and Community Safety makes a significant contribution to crime science and integrates a range of theories to understand patterns of crime and perceived safety in rural contexts. Based on a wealth of original research, Ceccato combines spatial methods with qualitative analysis to examine, in detail, farm and wildlife crime, youth related crimes and gendered violence in rural settings. Making the most of the expanding field of Criminology and of the growing professional inquiry into crime and crime prevention in rural areas; rural development; and the social sustainability of rural areas, this book builds a bridge by connecting Criminology and Human Geography. This book will be suitable for academics, students and practitioners in the fields of criminology, community safety, rural studies, rural development and gender studies

Rural Crime and Community Safety

Crime is often perceived as an urban issue rather than a problem that occurs in rural areas, but how far is this view tenable? This book explores the relationship between crime and community in rural areas and addresses the notion of safety as part of the community dynamics in such areas. Rural Crime and Community Safety makes a significant contribution to crime science and integrates a range of theories to understand patterns of crime and perceived safety in rural contexts. Based on a wealth of original research, Ceccato combines spatial methods with qualitative analysis to examine, in detail, farm and wildlife crime, youth related crimes and gendered violence in rural settings. Making the most of the expanding field of Criminology and of the growing professional inquiry into crime and crime prevention in rural areas; rural development; and the social sustainability of rural areas, this book builds a bridge by connecting Criminology and Human Geography. This book will be suitable for academics, students and practitioners in the fields of criminology, community safety, rural studies, rural development and gender studies

Environmental and Wildlife Crime in Sweden

This article discusses the nature of environmental and wildlife crime (EWC) in Sweden. A review of the international literature helps to frame the Swedish case study. The novelty of this study lies in using 11 years of police records as well as newspaper articles (Media archives) as a basis for analysis. Geographical Information System (GIS) supports the spatial analysis of EWC at municipal and coordinate levels. Since most EWCs take place outside large urban areas, this study looks closely at the cases of EWC in the rural county of Västernorrland. Findings show an increase in both EWCs recorded by the police and covered by the media in the last decade. EWC-geography varies by crime type: rural areas are in general more prone to unlawful handling of chemicals and to nature and wildlife crimes than are urban areas, where dumping and other minor EWCs are more common. Detection of EWCs is highly dependent on people’s routine activities and accessibility. Drawing upon the Swedish evidence, the article closes with suggestions for improvements in research on environmental and wildlife crimes

Crime and Safety in the Rural

Criminology has until recently neglected the nature and levels of crime outside the urban realm. This is not a surprise as crime tends to concentrate in urban areas and the police directs resources where the problems are. Yet, there are many reasons why scholars, decision-makers and society as a whole should care about crime and safety in rural areas. This book highlights 20 reasons why crime and safety in rural areas is a topic of relevance. We attempt to untangle currently simplistic views of the rural by discussing a number of facets of the countryside as both safe and criminogenic, and more importantly, a hybrid place worth to be examined in its own right. We adopt the notion of a rural-urban continuum that captures the nuances of places of varied nature, spanning from remote and desolate spaces to accessible and connected environments of the urban fringe. Areas on the rural-urban continuum may be in constant transformation given local and global influences, which imposes challenges for policing and long-term social sustainability. Then, the book critically reviews a rich body of English-language literature in rural criminology that extends over more than four decades—a scholarship that has engaged researchers and practitioners in all continents. The books finishes with a discussion of the emergent research questions of the field, and offers implications for practice and the 2030 Sustainable Development Goals

Crimes against animal production: Exploring the use of media archives

Swedish media have revealed an increase in crimes against animal production (CAAP) in the last decade. We investigate the nature of such crimes (especially against mink, pig, and rabbit farms), with a focus on those crimes whose suspects are animal rights groups by utilizing data from media archives from 2009 to 2019. Newspaper articles show that while vandalism and trespassing are often committed against mink farms, property crimes occur more often against pig and rabbit farms. Because there are indications that crime suspects are not a homogeneous group and express different motivations to commit CAAP, a multipronged approach is needed to prevent CAAP. The use of newspaper articles from media archives has proven to be successful for obtaining a general perspective of CAAP, but it is limited for capturing crime incidence or for investigating CAAP spatiotemporal nature when using geographical information systems. The automated usage of digital media archives should be further explored and critically assessed in future research in criminology

Defecation, littering and other acts of public disturbance in pandemic times – A study of a Scandinavian city

The spatiotemporal patterns of public disturbance acts are investigated in Stockholm, the capital of Sweden. Using crowdsourced data, the number of records is compared 15 months before and after the stay-at-home measures of the COVID-19 pandemic, controlling for seasonal trends. Poisson-Gamma-CAR regression models are implemented to assess the potential impact of land use on the spatial distribution of public disturbance acts, accounting for the effect of pandemic restrictions and differences in neighborhood context. Findings show that, with the exception of abandoned vehicles, there was a significant increase in records of public disturbance after the 2020 stay-at-home pandemic restrictions. Parks, transport hubs and less importantly, schools were significantly associated with public disturbances, controlling for neighborhood characteristics and reporting practices. Recommendations are made for research and practice

A new information theoretical measure of global and local spatial association

In this paper a new measure of spatial association, the S statistics, is developed. The proposed measure is based on information theory by defining a spatially weighted information measure (entropy measure) that takes the spatial configuration into account. The proposed S-statistics has an intuitive interpretation, and furthermore fulfills properties that are expected from an entropy measure. Moreover, the S statistics is a global measure of spatial association that can be decomposed into Local Indicators of Spatial Association (LISA). This new measure is tested using a dataset of employment in the culture sector that was attached to the wards over Stockholm County and later compared with the results from current global and local measures of spatial association. It is shown that the proposed S statistics share many properties with Moran's I and Getis-Ord Gi statistics. The local Si statistics showed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatial association. The statistics can also be extended to bivariate distributions. It is shown that the commonly used Bayesian empirical approach can be interpreted as a Kullback-Leibler divergence measure. An advantage of S-statistics is that this measure select only the most robust clusters, eliminating the contribution of smaller ones composed by few observations and that may inflate the global measure

A new information theoretical measure of global and local spatial association

In this paper a new measure of spatial association, the S statistics, is developed. The proposed measure is based on information theory by defining a spatially weighted information measure (entropy measure) that takes the spatial configuration into account. The proposed S-statistics has an intuitive interpretation, and furthermore fulfills properties that are expected from an entropy measure. Moreover, the S statistics is a global measure of spatial association that can be decomposed into Local Indicators of Spatial Association (LISA). This new measure is tested using a dataset of employment in the culture sector that was attached to the wards over Stockholm County and later compared with the results from current global and local measures of spatial association. It is shown that the proposed S statistics share many properties with Moran's I and Getis-Ord Gi statistics. The local Si statistics showed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatial association. The statistics can also be extended to bivariate distributions. It is shown that the commonly used Bayesian empirical approach can be interpreted as a Kullback-Leibler divergence measure. An advantage of S-statistics is that this measure select only the most robust clusters, eliminating the contribution of smaller ones composed by few observations and that may inflate the global measure