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Department of Geography


The Geography of Crime and Disorder: offences, offenders and victimization

A number of projects fall under this broad heading. The methodological orientation of all this work is quantitative (spatial analysis, spatial modelling and using GIS for data management and display) because research typically uses large police recorded offence and offender datasets.

In collaboration with Jane Law (now University of Waterloo, Canada), and building on earlier work with Max Craglia (ISPRA) and Paola Signoretta (Sheffield), we analysed the distribution of high intensity (violent) crime areas in English cities. Earlier work reported on findings that identified the socio-economic factors that helped explain the location of these areas. In addition this earlier work compared police perceptions of high intensity crime areas with recorded offence and offender data for Sheffield. In the concluding phase of this work we adopted a Bayesian approach in WinBUGS in order to combine (update) police perceptions of high crime areas with recorded offence and offender data. The reason for this work has been to explore ways in which expert knowledge can be integrated with current data to develop a more informed view of where these areas are located. The results of this work were published in 2007 (see publications list).

Dr Vania Ceccato and Professor Haining have been collaborating over several years analysing large geo-referenced crime data sets from different countries. Most of this work has used small area offence data and has included several Swedish cases studies. The earliest work involved analysing the spatial incidence of various high volume crimes (e.g burglary, car theft) in Stockholm in the late 1990s in order to describe how crime patterns had changed since Wikstrom’s study of Stockholm using 1980s data. Two further studies have focused on Malmo. One of these has used a large data set on recorded crime before and after the opening of the Oresund Bridge from Malmo to Copenhagen. The aim was to show if there had been shifts in the volume and geography of crime arising from the construction of a bridge that has altered movement patterns of people between Sweden and Denmark. The work involved benchmarking crimes that were likely to be affected by the opening of the bridge (including narcotics and certain forms of theft) against those that were unlikely to be affected. The contexts for this work are first, the possible consequences of wider European integration including the expansion of EU borders and second, the greater mobility of populations linked to transport improvements within Europe. How have recent changes in Eastern Europe impacted on crime rates in those countries and what effect might wider European integration have on crime rates throughout the EU?

More recently Vania and I have analysed spatial variation in vandalism in Malmo and shown that higher rates of vandalism are associated with the physical presence of certain “collective resources” after controlling for social disorganization risk factors and land use factors (see figures 1 and 2 for the conceptual framework that underpinned the research). We have also completed a study of the incidence of homicides in Sao Paolo, Brazil. This is one of the first examples of a spatial analysis of a large crime dataset from a developing country. Research showed that an unusually large proportion of the variation in homicide rates can be explained by poverty, situational conditions determined by differences in land use and processes that indicate links with the geography of drugs markets and the local availability of firearms. The paper was published in 2007 (see publications list).

We have recently collaborated in the analysis of small area offence rates in the “transition states” of Estonia, Latvia and Lithuania. The aim here was to test a longstanding hypothesis due to Durkheim that citizens of countries experiencing profound social and economic change (in this case the end of the Soviet Union) experience uncertainty that creates a sense of alienation that leads to increased levels of crime and violence. There is also an hypothesis that where social institutions are strong this effect is mitigated (Messner-Rosenfeld, 1997). Again the work involved the spatial analysis of large, small area, data sets (see publications list). Currently Vania and I together with Guangquan Li (Northumbria) are analysing the small area geography of rape in public spaces in Stockholm using Bayesian modelling techniques. The aim is to examine the relationship between the occurence of rape and various socio-economic and landuse characterisitcs (e.g. nearness to subway stations, alcohol outlets). This work is in progress as of April 2014.

I am also currently collaborating with Guangquan Li, formerly of the BIAS II group at Imperial College London, in the spatial analysis of offence and offender data in Cambridgeshire using small area (Census Output Area) data. We have two projects currently underway as part of this ESRC funded project: (i) an assessment of no cold calling areas, seeking to establish whether the targetted introduction of these schemes to stop doorstep cold calling in selected neighbourhoods has impacted on burglary rates in those neighbourhoods; (ii) identifying burglary hotspots and non-hotspots in Peterborough (2005-08) and identifying their temporal trajectories. Over the study period which hotspots were heating up and which were cooling down?. Were there non-hotspot areas that were tending towards becoming hotspots? Both projects involve the application of new techniques of Bayesian spatial and spatial-temporal modelling. As of April 2014, one paper from the project has been published, another is in press. Further work is in progress on the spatial-temporal analysis of recorded crime data using Bayesian regression methods.

Yijing Li has successfully completed her PhD on a multi-scale analysis of crime in China which includes a study of selected neighbourhoods in Shenzen based on a questionnaire survey of peoples perceptions and experiences of crime.

Figure as described adjacent

Figure 1 – A conceptual framework for the link between collective resources and neighbourhood vandalism – a link that can be broken by “resistance/action”.

Figure 2 (below) expands the box labelled ‘Neighbourhood collective resources’.

Figure as described adjacent


Selected publications in this area:

  • ‘Space-time variability in burglary risk: a Bayesian spatio-temporal modelling approach.’ Spatial Statistics, 2014 (in press), (with G.Li, S.Richardson and N.Best).
  • “Evaluating the No Cold Calling zones in Peterborough, England: application of a novel statistical method for evaluating neighbourhood policing policies.” Environment and Planning, A.,2013, 45(8), 2012-2026. (with G.Li, S.Richardson and N.Best).
  • ‘Applying geostatistical analysis to crime data: car related thefts in the Baltic States.’ Geographical Analysis, 2010, 42, 53-77, (with V. Ceccato).
  • ‘Short and medium term dynamics and their influence on acquisitive crime rates in the transition states of Estonia, Latvia and Lithuania.’ Applied Spatial Analysis and Policy, 2008, 1, 215-44, (with V.Ceccato).
  • ‘Combining police perceptions with police records of serious crime areas: a modelling approach.’ Journal of the Royal Statistical Society Series A (Statistics in Society), 2007, 170, 1-16 (with J.Law).
  • ‘The geography of homicide in Sao Paolo, Brazil’ Environment and Planning, A, 2007, 39(7), 1632-53 (with V.Ceccato and T.Kahn)
  • ‘Assessing the geography of vandalism: evidence from a Swedish city. Urban Studies, 2005, 42, 1637-1656. (with V. Ceccato)
  • ‘Modelling high intensity crime areas: comparing police perceptions with offence/offender data in Sheffield.’ Environment & Planning A. 2005, 37(3), 503-524. (with M.Craglia and P.Signoretta).
  • ‘Crime in border regions: the Scandinavian case of Oresund 1998-2001.’ Annals, Association of American Geographers, 2004, 94, 807-826. (with V.Ceccato).
  • ‘Exploring offence statistics in Stockholm City using spatial analysis tools’ Annals, Association of American Geographers, 2002, 92, 29-51. (with V.Ceccato and P.Signoretta)
  • ‘Modelling high intensity crime areas in English cities’. Urban Studies, 2001, 38, 1921-41. (with M.Craglia and P.Signoretta).