Visualizing the spatial movement patterns of offenders (original) (raw)

Visualization Techniques for Journey to Crime Flow Data

2013

Research applications using journey to crime (JTC) data are popular and becoming more prevalent in criminology and crime mapping analysis. JTC data present unique challenges for modeling and visualization not encountered with typical data that is only georeferenced at one point in space. This article reviews useful cartographic and data visualization techniques to explore JTC flow data. The article also provides supplementary material demonstrating and implementing several of the techniques discussed in the article. Pre-print at SSRN: http://papers.ssrn.com/sol3/papers.cfm?abstract\_id=2275379 Published at CaGIS: http://dx.doi.org/10.1080/15230406.2014.890545

Visualization of Criminal Activity in an Urban Population

Using Computer Simulations and Geographic Information Systems, 2008

Crime is a multi-dimensional and complex activity. In order to understand its nature one has to comprehend not only its spatio-temporal dimensions but also the nature of crime, the victimoffender relationship, the role of guardians and history of similar previous incidents. Visualization of all the dimensions is a formidable task due to the limitations of the present methods. Both for the police department and criminal justice researcher the need to deal with a vast amount of data is a prerequisite to the task of controlling the crime. This paper presents an interactive visualization technique intended to present the viewer with an accurate and intuitive view of the criminal activity in a cityscape. The technique employs many different visualization elements, which taken together presents a useful methodology to handle the important the associated factors of crime. The paper also describes the software technique and discusses avenues for future investigation.

Visualising space time patterns in crime: the hotspot plot

Part of the interest in crime mapping may be due to the relevance of geography in explaining patterns of crime. There is, however, a danger in missing other patterns (temporal patterns most notably) if the spatial domain is given disproportionate focus. A number of recent academic studies have shown reliable and meaningful spatio-temporal patterns of crime; yet their representation remains rather abstract. This article proposes a systematic method of displaying crime hot spots. It combines temporal and spatial information in an effective manner that allows the viewer to intuitively: assess temporal profiles of individual hot spots at the micro and macro levels (i.e. day and year); compare the importance and temporal signature of different hot spots; and relate the results of the first two to baseline measures.

Mirante: A visualization tool for analyzing urban crimes

2020

Visualization assisted crime analysis tools used by public security agencies are usually designed to explore large urban areas, relying on grid-based heatmaps to reveal spatial crime distribution in whole districts, regions, and neighborhoods. Therefore, those tools can hardly identify micro-scale patterns closely related to crime opportunity, whose understanding is fundamental to the planning of preventive actions. Enabling a combined analysis of spatial patterns and their evolution over time is another challenge faced by most crime analysis tools. In this paper, we present Mirante, a crime mapping visualization system that allows spatiotemporal analysis of crime patterns in a street-level scale. In contrast to conventional tools, Mirante builds upon street-level heatmaps and other visualization resources that enable spatial and temporal pattern analysis, uncovering fine-scale crime hotspots, seasonality, and dynamics over time. Mirante has been developed in close collaboration wit...

Hot Routes: Developing a New Technique for the Spatial Analysis of Crime.

The use of hotspot mapping techniques such as KDE to represent the geographical spread of linear events can be problematic. Network-constrained data (for example transport-related crime) require a different approach to visualize concentration. We propose a methodology called Hot Routes, which measures the risk distribution of crime along a linear network by calculating the rate of crimes per section of road. This method has been designed for everyday crime analysts, and requires only a Geographical Information System (GIS), and suitable data to calculate. A demonstration is provided using crime data collected from London bus routes.

Finding Criminal Attractors Based on Offenders' Directionality of Crimes

2011 European Intelligence and Security Informatics Conference, 2011

According to Crime Pattern Theory, individuals all have routine daily activities which require frequent travel between several nodes, with each being used for a different purpose, such as home, work or shopping. As people move between these nodes, their familiarity with the spatial area around the nodes, as well as between nodes, increases. Offenders have the same spatial movement patterns and Awareness Spaces as regular people, hence according to theory an offender will commit the crimes in their own Awareness Space. This idea is used to predict the location of the nodes within the Awareness Space of offenders. The activities of 57,962 offenders who were charged or charges were recommended against them were used to test this idea by mapping their offense locations with respect to their home locations to determine the directions they move. Once directionality to crime was established for each offender, a unique clustering technique, based on K-Means, was used to calculate their Cardinal Directions through which the awareness nodes for all offenders were calculated. It was found that, by looking at the results of various clustering parameters, offenders tend to move towards central shopping areas in a city, and commit crimes along the way. Almost all cluster centers were within one kilometer of a shopping center. This technique of finding Criminal Attractors allows for the reconstruction of the spatial profile of offenders, which allows for narrowing the possible suspects for new crimes.

Spatial cognition and crime: the study of mental models of spatial relations in crime analysis

Cognitive Processing, 2012

Several studies employed different algorithms in order to investigate criminal's spatial behaviour and to identify mental models and cognitive strategies related to it. So far, a number of geographic profiling (GP) software have been implemented to analyse mobility and its relation to the way criminals are using spatial environment when committing a crime. Since crimes are usually perpetrated in the offender's high-awareness areas, those cognitive maps can be employed to create a map of the criminal's operating area to help investigators to circumscribe search areas. The aim of the present study was to verify accuracy of simple statistical analysis in predicting spatial mobility of a group of 30 non-criminal subjects. Results showed that statistics such as Mean Centre and Standard Distance were accurate in elaborating a GP for each subject according to the mobility area provided. Future analysis will be implemented using mobility information of criminal subjects and location-based software to verify whether there is a cognitive spatial strategy employed by them when planning and committing a crime.

The Mapping and Spatial Analysis of Crime - Criminology - Oxford Bibliographies

Oxford Bibliographies Online: Criminology, 2019

The mapping and spatial analysis of crime covers a broad range of techniques and has been used to explore a variety of topics. In its most basic form, crime mapping is the use of Geographic Information System (GIS) to visualize and organize spatial data for more formal statistical analysis. Spatial analysis can be employed in both an exploratory and well as a more confirmatory manner with the primary purpose of identifying how certain community or ecological factors (such as population characteristics or the built environment) influence the spatial patterns of crime. Two topics of particular interest include examining for evidence of the diffusion of crime and in evaluating the effectiveness of geographically targeted crime reduction strategies. Crime mapping can also be used to visualize and analyze the movement or target selection patterns of criminals. Mapping software allows for the creation of electronic pin-maps and by spatially organizing the data, GIS increases the analytical value of these maps. Crime mapping allows researchers and practitioners to explore crime patterns, offender mobility, and serial offenses over time and space. Within the context of local policing, crime mapping provides the visualization of crime clusters by types of crimes, thereby validating the street knowledge of patrol officers. Crime mapping can be used for allocating resources (patrol, specialized enforcement) and also to inform how the concerns of local citizens are being addressed. The citations listed below highlight the interdisciplinary nature of both the study of crime and the development of the methods used in spatial analysis. They exemplify the growing prominence that spatial analysis has in understanding where crime occurs.