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.

Providing scientific visualisation for spatial data analysis: criteria and an assessment of SAGE

A consistent theme in recent work on developing exploratory spatial data analysis (ESDA) has been the importance attached to visualization techniques, particularly following the pioneering development of packages such as REGARD by Haslett et al (1990). The focus on visual techniques is often justified in two ways: (a) the power of modern graphical interfaces means that graphics is no longer a way of simply presenting results in the form of maps or graphs, but a tool for the extraction of information from data; (b)graphical, exploratory methods are felt to be more intuitive for non-specialists to use than methods of numerical spatial statistics enabling wider participation in the process of getting data insights. Despite the importance attached to visualisation techniques, very little work has been done to assess the effectiveness of techniques, either in the wider scientific visualisation community, or among those working with spatial data. This paper will describe a theoretical framework for developing visualisation tools for ESDA that incorporates a data model of what the analyst is looking for based on the concepts of "rough" and "smooth" elements of a data set and a theoretical scheme for assessing visual tools. The paper will include examples of appropriate tools and a commentary on the effectiveness of some existing packages

SIG y análisis espacial de datos: perspectivas convergentes

En este artículo se identifican algunos de los desarrollos más importantes experimentados por los SIG y el análisis espacial de datos desde los inicios de los 50. Aunque tanto los SIG como el análisis espacial de datos comenzaron como dos áreas de investigación y aplicación más o menos separadas, han crecido unidos estrechamente a lo largo del tiempo. En el trabajo se mantiene que estas dos disciplinas se unen en el terreno de la Ciencia de la Información Geográfica, proporcionando cada una de ellas apoyo o añadiendo valor a la otra. El artículo comienza proporcionando una visión crítica retrospectiva de los desarrollos que han tenido lugar en los últimos cincuenta años. A continuación, se reflexiona acerca de los desafíos actuales y se especula sobre el futuro. Por último se comenta el potencial de convergencia del desarrollo de los SIG y del análisis espacial de datos bajo la rubrica de la Ciencia de la Información Geográfica (o SIGciencia)

Evaluating Neighbourhood Policing using Bayesian Hierarchical Models: No Cold Calling in Peterborough, England

As part of a wider Neighbourhood Policing strategy, Cambridgeshire Constabulary, in common with other Police Forces in the UK, instituted "No Cold Calling" (NCC) zones to reduce cold calling (unsolicited visits to sell products or services), which is often associated with rogue trading and distraction burglary. This paper evaluates the NCC targeted areas chosen in 2005-6 and reports whether they experienced a measurable impact on their burglary rates in the period up to 2008. Time series data for burglary at the Census Output Area level is analysed using a Bayesian hierarchical modelling approach, addressing issues often encountered in small area quantitative policy evaluation. Results reveal a positive NCC impact on stabilising burglary rates in the targeted areas

A protocol for investigation of the effects of outdoor air pollution on stroke incidence, phenotypes and survival using the South London Stroke Register.

Stroke is a major cause of death and disability. About 5.3 million people die every year from stroke worldwide with over 9 million people surviving at any one time after suffering a stroke. About 1 in 4 men and 1 in 5 women aged 45 years will suffer a stroke if they live to their 85th year. It is estimated that by 2023 there will be an absolute increase in the number of people experiencing a first ever stroke of about 30% compared with 1983. In the UK, stroke is the third commonest cause of death and the most common cause of adult physical disability and consumes 5% of the health and social services budget. Stroke is assuming strategic public health importance because of increased awareness in society, an ageing population and emerging new treatments. It is an NHS health service and research priority, being identified as a target in Our Healthier Nation and the NSF for Older People for prevention and risk factor control and in the NHS Plan as a disease requiring intermediate care planning and reduction in inequalities of care. Whilst a number of risk factors for stroke are well known (e.g. increasing age, ethnicity, socioeconomic deprivation, hypertension), the potential importance of outdoor air pollution as a modifiable risk factor is much less well recognised. This is because studies to date are inconclusive or have methodological limitations. In Sheffield, we estimated that 11% of stroke deaths may be linked to current levels of outdoor air pollution and this high figure is explained by the fact that so many people are exposed to air pollution.We plan to study the effects of outdoor air pollution on stroke using a series of epidemiological (i.e. population based) studies. The purpose of this project is: to examine if short term increases in pollution can trigger a stroke in susceptible individuals, to investigate if the occurrence of stroke is higher amongst people living in more polluted areas (which would be explained by a combination of exposure to short term increases and longer term exposure to higher pollution levels), and to see if people living in more polluted areas have reduced survival following their stroke. We will use geographical information systems, robust statistical methods and powerful grid computing facilities to link and analyse the data. The datasets we will use are the South London Stroke Register database, daily monitored pollution data from national monitoring networks and modelled pollution data for London from the Greater London Authority. The South London Stroke Register records information on all patients who suffer a stroke ("incident" cases) living within a defined area. This stroke incidence dataset offers major advantages over previous studies examining the effects of pollution on hospital admissions and mortality, as not all patients with stroke are admitted or die and there may be a delay between the onset of stroke and admission or death. In addition, it contains other useful information, particularly the type of stroke people have suffered. Air pollution is a potentially modifiable risk factor for stroke. This study will provide robust population level evidence regarding the effects of outdoor air pollution on stroke. If it confirms the link, it will suggest to policy-makers at national and international levels that targeting policy interventions at high pollution areas may be a feasible option for stroke prevention

Statistical modeling of spatially stratified heterogeneous data

Spatial statistics is an important methodology for geospatial data analysis. It has evolved to handle spatially autocorrelated data and spatially (locally) heterogeneous data, which aim to capture the first and second laws of geography, respectively. Examples of spatially stratified heterogeneity (SSH) include climatic zones and land-use types. Methods for such data are relatively underdeveloped compared to the first two properties. The presence of SSH is evidence that nature is lawful and structured rather than purely random. This induces another “layer” of causality underlying variations observed in geographical data. In this article, we go beyond traditional cluster-based approaches and propose a unified approach for SSH in which we provide an equation for SSH, display how SSH is a source of bias in spatial sampling and confounding in spatial modeling, detect nonlinear stochastic causality inherited in SSH distribution, quantify general interaction identified by overlaying two SSH distributions, perform spatial prediction based on SSH, develop a new measure for spatial goodness of fit, and enhance global modeling by integrating them with an SSH q statistic. The research advances statistical theory and methods for dealing with SSH data, thereby offering a new toolbox for spatial data analysis

Ultrafast neuronal imaging of dopamine dynamics with designed genetically encoded sensors

Neuromodulatory systems exert profound influences on brain function. Understanding how these systems modify the operating mode of target circuits requires measuring spatiotemporally precise neuromodulator release. We developed dLight1, an intensity-based genetically encoded dopamine indicator, to enable optical recording of dopamine dynamics with high spatiotemporal resolution in behaving mice. We demonstrated the utility of dLight1 by imaging dopamine dynamics simultaneously with pharmacological manipulation, electrophysiological or optogenetic stimulation, and calcium imaging of local neuronal activity. dLight1 enabled chronic tracking of learning-induced changes in millisecond dopamine transients in striatum. Further, we used dLight1 to image spatially distinct, functionally heterogeneous dopamine transients relevant to learning and motor control in cortex. We also validated our sensor design platform for developing norepinephrine, serotonin, melatonin, and opioid neuropeptide indicators

The ecology of outdoor rape: The case of Stockholm, Sweden

The objective of this article is to report the results of an ecological study into the geography of rape in Stockholm, Sweden, using small area data. In order to test the importance of factors indicating opportunity, accessibility and anonymity to the understanding of the geography of rape, a two-stage modelling approach is implemented. First, the overall risk factors associated with the occurrence of rape are identified using a standard Poisson regression, then a local analysis using profile regression is performed. Findings from the whole-map analysis show that accessibility, opportunity and anonymity are all, to different degrees, important in explaining the overall geography of rape - examples of these risk factors are the presence of subway stations or whether a basområde is close to the city centre. The local analysis reveals two groupings of high risk of rape areas associated with a variety of risk factors: city centre areas with a concentration of alcohol outlets, high residential population turnover and high counts of robbery; and poor suburban areas with schools and large female residential populations where subway stations are located and where people express a high fear of crime. The article concludes by reflecting upon the importance of these results for future research as well as indicating the implications of these results for policy