Network-based space-time scan statistics for detecting micro-scale hotspots

Events recorded in urban areas are often confined by the micro-scale geography of street networks, yet existing spatial–analytical methods do not usually account for the shortest-path distance of street networks. We propose space–time NetScan, a new spatial–temporal analytical method with improved accuracy for detecting patterns of concentrations across space and time. It extends the notion of a scan-statistic-type search window by measuring space-time patterns along street networks in order to detect micro-scale concentrations of events at the street-address level with high accuracy. Performance tests with synthetic data demonstrate that space-time NetScan outperforms existing methods in detecting the location, shape, size and duration of hotspots. An empirical study with drug-related incidents shows how space-time NetScan can improve our understanding of the micro-scale geography of crime. Aside from some abrupt one-off incidents, many hotspots form recurrent hotbeds, implying that drug-related crimes tend to persist in specific problem places

The when and where of an emerging crime type: the example of metal theft from the railway network of Great Britain

Metal theft has become an increasingly common crime in recent years, but lack of data has limited research into it. The present study used police-recorded crime data to study the spatial and temporal concentration of metal theft from the railway network of Great Britain. Metal theft was found to exhibit only weak seasonality, to be concentrated at night and to cluster in a few locations close to – but not in – major cities. Repeat-victimisation risk continued for longer than has been found for other crime types. These and other features appear to point to metal theft being a planned, rather than opportunistic, offence and to the role of scrap-metal dealers as facilitators

Mapping Crime Hotspots in Akure, Nigeria: A GIS Perspective

African countries in recent times have witnessed an unprecedented level of insecurity. This has made national security threat to be a major issue for the government and has prompted huge allocation of the national budget to security. The objective of this paper is to mark out crime hotspot areas in the central area of Akure metropolis; and examine the rate at which crimes are committed, the surveillance method used and its effectiveness. The research made use of Google Earth imagery and Geographical Information System (GIS) technology to delineate crime hotspots in Akure. A 100m buffer was created around the identified crime hotspots to select houses that are susceptible to the impacts of crime activities in the study area. A structured questionnaire was also used to elicit information on crime, surveillance method, and effect of crime on the people and level of occurrence in the city among others. Findings identified six major crimes in eight hotspot areas; noise, loss of property and threat to life were some of the effects of hotspots on residents. The paper recommends construction/repair of roads in the core residential areas for effective surveillance of hotspots. The use of satellite images to combat crime in the city is also canvassed

Health, wealth, and air pollution: advancing theory and methods.

The effects of both ambient air pollution and socioeconomic position (SEP) on health are well documented. A limited number of recent studies suggest that SEP may itself play a role in the epidemiology of disease and death associated with exposure to air pollution. Together with evidence that poor and working-class communities are often more exposed to air pollution, these studies have stimulated discussion among scientists, policy makers, and the public about the differential distribution of the health impacts from air pollution. Science and public policy would benefit from additional research that integrates the theory and practice from both air pollution and social epidemiologies to gain a better understanding of this issue. In this article we aim to promote such research by introducing readers to methodologic and conceptual approaches in the fields of air pollution and social epidemiology; by proposing theories and hypotheses about how air pollution and socioeconomic factors may interact to influence health, drawing on studies conducted worldwide; by discussing methodologic issues in the design and analysis of studies to determine whether health effects of exposure to ambient air pollution are modified by SEP; and by proposing specific steps that will advance knowledge in this field, fill information gaps, and apply research results to improve public health in collaboration with affected communities

Effects of different building blocks designs on the statistical characteristics of Automated Zone-design Tool output areas

Prior to any census, the country usually gets demarcated into small geographic units called census enumeration areas, districts or blocks. In most countries, these small geographic units are also used for census dissemination. In cases where they are not used for census release, they are normally used as building blocks for developing output areas or they are aggregated to higher spatial levels in an effort to preserve privacy or confidentiality. Buildings blocks are therefore, of significant importance towards results that could be drawn from either aggregated higher level or from output areas developed using these small geographic areas. This paper aimed at evaluating the effects of different building blocks on the statistical characteristics of output areas generated using the Automated Zone-design Tool (AZTool) computer program. Different spatial layers (such as Enumeration Areas (EAs), Small Area Layers (SALs) and SubPlaces) from the 2001 census data were used as building blocks for the generation of census output areas with AZTool program in both rural and urban areas of South Africa. One way-Analysis of Variance (ANOVA) was also performed to determine statistical significance of the AZTool results. Results showed that the AZTool output areas generated from smaller areas (EAs and SALs) tend to be more homogeneous than the ones generated from larger areas (SubPlaces) when using dwelling type and geotype as homogeneity variables. The output areas from smaller areas also had narrower population distribution and more compact shapes than their counter-parts. In addition, the AZTool optimised output areas from the smaller areas allowed a clear distinction of the scale effects than output areas from larger areas. It was concluded that indeed different building blocks did have an impact on the statistical qualities of the AZTool optimised output areas in both rural and urban settings in South Africa.Keywords: AZTool; Building blocks; Enumeration areas; Output areas; Scale effects; Small Area Layers; SubPlace

A Self-Adjusting Approach to Identify Hotspots

Hotspot identification or detection has been widely used in many fields; however the traditional grid-based approaches may incur some problems when dealing with point database. This article expands on three types of mismatch problems in grid-based approach and suggests a point-based approach may be more suitable. Inspired by the DBSCAN algorithm, a self-adjusting approach is then proposed for hotspot detection which overcomes the weakness of parameter sensitivity shared by most clustering approaches. Finally, the data of commercial points of interest of a city is used for demonstration