Jonathan Corcoran

Visualising space and time in crime patterns: A comparison of methods

Abstract Previous research exploring space–time patterns has focused on the relative merits and drawbacks of the effectiveness of static maps vis-a-vis interactive dynamic visualisation techniques. In particular, they have tended to concentrate on the role of animation in interpretation of patterns and the understanding of underlying factors influencing such patterns. The aim of this paper is to broaden this debate out to consider the effectiveness of a wider range of visualisation techniques in permitting an understanding of spatio-temporal trends. The merits of three visualisation techniques, (map animation, the comap and the isosurface) are evaluated on their ability to assist in the exploration of space–time patterns of crime disturbance data. We conclude that each technique has some merit for crime analysts charged with studying such trends but that further research is needed to apply the techniques to other sources of crime data (and to other sectors such as health) to permit a comprehensive evaluation of their respective strengths and limitations as exploratory visualisation tools.

Scale mismatches, conservation planning, and the value of social-network analyses

Many of the challenges conservation professionals face can be framed as scale mismatches. The problem of scale mismatch occurs when the planning for and implementation of conservation actions is at a scale that does not reflect the scale of the conservation problem. The challenges in conservation planning related to scale mismatch include ecosystem or ecological process transcendence of governance boundaries; limited availability of fine-resolution data; lack of operational capacity for implementation; lack of understanding of social-ecological system components; threats to ecological diversity that operate at diverse spatial and temporal scales; mismatch between funding and the long-term nature of ecological processes; rate of action implementation that does not reflect the rate of change of the ecological system; lack of appropriate indicators for monitoring activities; and occurrence of ecological change at scales smaller or larger than the scale of implementation or monitoring. Not recognizing and accounting for these challenges when planning for conservation can result in actions that do not address the multiscale nature of conservation problems and that do not achieve conservation objectives. Social networks link organizations and individuals across space and time and determine the scale of conservation actions; thus, an understanding of the social networks associated with conservation planning will help determine the potential for implementing conservation actions at the required scales. Social-network analyses can be used to explore whether these networks constrain or enable key social processes and how multiple scales of action are linked. Results of network analyses can be used to mitigate scale mismatches in assessing, planning, implementing, and monitoring conservation projects.

Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).

The use of spatial analytical techniques to explore patterns of fire incidence : A South Wales case study

The application of mapping and spatial analytical techniques to explore geographical patterns of crime incidence is well established. In contrast, the analysis of operational incident data routinely collected by fire brigades has received relatively less research attention, certainly in the UK academic literature. The aim of this paper is to redress this balance through the application of spatial analytical techniques that permit an exploration of the spatial dynamics of fire incidents and their relationships with socio-economic variables. By examining patterns for different fire incident types, including household fires, vehicle fires, secondary fires and malicious false alarms in relation to 2001 Census of Population data for an area of South Wales, we demonstrate the potential of such techniques to reveal spatial patterns that may be worthy of further contextual study. Further research is needed to establish how transferable these findings are to other geographical settings and how replicable the findings are at different geographical scales. The paper concludes by drawing attention to the current gaps in knowledge in analysing trends in fire incidence and proposes an agenda to advance such research using spatial analytical techniques.

The Use of Comaps to Explore the Spatial and Temporal Dynamics of Fire Incidents: A Case Study in South Wales, United Kingdom

Abstract This article reports on the results from a spatiotemporal analysis of disaggregate fire incident data. The innovative analysis presented here focuses on the exploration of spatial and temporal patterns for four principal fire incident categories: property, vehicle, secondary fires, and malicious false alarms. This research extends previous work on spatial exploration of spatiotemporal patterns by demonstrating the benefits of comaps and kernel density estimation in examining temporal and spatiotemporal dynamics in calls for services. Results indicate that fire incidents are not static in either time or space and that spatiotemporal variation is related to incident type. The application of these techniques has the potential to inform policy decisions both from a reactive, resource-allocation perspective and from a more proactive perspective, such as through spatial targeting of preventive measures. *We would like to thank the South Wales Fire and Rescue Service for access to the data on which the article is based. In particular, we thank Andy Marles and Dave Bennett of the South Wales Fire and Rescue Service for their help and advice on various aspects of the data sets. The interpretations of the analysis, however, are solely those of the authors and do not necessarily reflect the views and opinions of the Service or any of its employees. The work uses 2001 Census and GIS boundary data obtained via MIMAS CASWEB and EDINA UKBORDERS; academic services both supported by ESRC and JISC. These data are copyright of the Crown and are reproduced with permission of the Controller of HMSO.

Using circular statistics to analyse time patterns in crime incidence

A set of techniques referred to as circular statistics has been developed for the analysis of directional and orientational data. The unit of measure for such data is angular (usually in either degrees or radians), and the statistical distributions underlying the techniques are characterised by their cyclic nature-for example, angles of 359.9 degrees are considered close to angles of 0 degrees. In this paper, we assert that such approaches can be easily adapted to analyse time-of-day and time-of-week data, and in particular daily cycles in the numbers of incidents reported to the police. We begin the paper by describing circular statistics. We then discuss how these may be modified, and demonstrate the approach with some examples for reported incidents in the Cardiff area of Wales. (c) 2005 Elsevier Ltd. All rights reserved.

Dynamics of bike sharing in Washington, DC and Brisbane, Australia: Implications for policy and planning

ABSTRACT The rapid growth in public bike-sharing programs (PBSPs) worldwide has left numerous research gaps, particularly related to environmental benefits, social benefits, and data from systems in cities with historically low bicycle ridership. We offer a battery of metrics and present results on their application to Washington, DC’s Capital Bikeshare and Brisbanes CityCycle. These metrics, which examine neighborhood performance and temporal and spatial ridership trends, initiate discussions on the policies and planning that make for a successful PBSP. We found that providing helmets, expanding hours of operation, and adding stations in suburbs with few or no stations leads to higher ridership.

Investigating the association between weather conditions, calendar events and socio-economic patterns with trends in fire incidence: an Australian case study

Fires in urban areas can cause significant economic, physical and psychological damage. Despite this, there has been a comparative lack of research into the spatial and temporal analysis of fire incidence in urban contexts. In this paper, we redress this gap through an exploration of the association of fire incidence to weather, calendar events and socio-economic characteristics in South-East Queensland, Australia using innovative technique termed the quad plot. Analysing trends in five fire incident types, including malicious false alarms (hoax calls), residential buildings, secondary (outdoor), vehicle and suspicious fires, results suggest that risk associated with all is greatly increased during school holidays and during long weekends. For all fire types the lowest risk of incidence was found to occur between one and six a.m. It was also found that there was a higher fire incidence in socially disadvantaged neighbourhoods and there was some evidence to suggest that there may be a compounding impact of high temperatures in such areas. We suggest that these findings may be used to guide the operations of fire services through spatial and temporal targeting to better utilise finite resources, help mitigate risk and reduce casualties.

A comparison of spatial disaggregation techniques as applied to population estimation for south east Queensland (SEQ), Australia

The accuracy of spatial disaggregation techniques largely depends on their underlying density assumptions and the quality of the data applied. This paper presents the results of a comparative investigation of four spatial disaggregation methodologies to determine their relative accuracies. These methodologies include binary dasymetric, a regression model, a locally fitted regression model and three-class dasymetric, each of which provides different solutions for explaining spatially heterogeneous density when population data is spatially disaggregated. In contrast to previous studies, we apply the spatial disaggregation techniques to a comparably larger and more varied geographical area which allows the spatial disaggregation techniques to be more rigorously tested. Results indicate that the three-class dasymetric technique generates higher levels of accuracy compared to the other spatial disaggregation techniques and this result is more conclusive than previous findings.

Relations between violence, calendar events and ambient conditions

National assault injury surveillance has identified major seasonal variation, but it is not clear whether assault injury is a seasonal problem in large cities. Relationships between community violence, calendar events and ambient conditions were investigated with reference to prospective, Accident and Emergency (A&E) derived information obtained from people injured in assaults in Cardiff between 1 May 1995 and 30 April 2000. Records of daily local ambient conditions included data relating to temperature, rainfall and sunshine hours and data of major local sporting events and annual holidays were studied. Pearson correlation coefficients were used to evaluate associations between variables. Overall, 19,264 assault-related A&E attendances were identified over the 5-year period. Almost three-quarters were males. Violence was clustered predominantly on Saturdays and Sundays, New Year and rugby international days. Temperature, rainfall and sunlight hours did not correlate significantly with violence (P > 0.05). The findings indicate that injury reduction effort should be intensified at the known risk times for violence and that in a capital city/regional centre violence cannot be predicted on the basis of ambient conditions.