Skip to main content
SpringerLink
Log in
Book cover

Crime Modeling and Mapping Using Geospatial Technologies pp 3–23Cite as

Spatial Heterogeneity in Crime Analysis

  • Chapter
  • First Online:

Part of the book series: Geotechnologies and the Environment ((GEOTECH,volume 8))

Abstract

Issues related to the modifiable areal unit problem are well-understood within geography. Though these issues are acknowledged in the spatial crime analysis literature, there is little research that assesses their impact. In fact, much of the cited spatial crime analysis literature that investigates the impact of modified areal units suggests that there is no problem—there is, however, an alternative literature. In this paper, we employ a new area-based spatial point pattern test to investigate the impact of modified areal units on crime patterns. We are able to show that despite the appearance of similarity in a (spatial) regression context, smaller units of analysis do show a high degree of variation within the larger units they are nested. Though this result in and of itself is not new, we also quantify how much spatial heterogeneity is present. This quantification is undertaken using multiple crime classifications and in a cross-national comparison.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    We define spatial heterogeneity being present when a large spatial unit of analysis has smaller spatial units of analysis within it that do not all exhibit the same properties.

  2. 2.

    There is also the issue of missing data because of underreporting of crime and/or systemic biases in reporting crime. This may or may not have spatial implications, but we are unaware of any research that addresses this issue.

  3. 3.

    Wooldredge (2002) is not the first to make this type of claim (see Land et al. 1990, for example), but is the most often cited research on this topic.

  4. 4.

    Prior to the 2001 census, these census boundaries were called enumeration areas.

  5. 5.

    The street network in Vancouver recognizes to which side of the street a point is geocoded. If that particular street is a boundary for a spatial unit, the point is assigned to the census unit on the appropriate side of the street in the spatial join.

  6. 6.

    There are two general forms of spatial point pattern tests: area-based and distance based. See Andresen (2009) for a discussion of their respective benefits and limitations.

  7. 7.

    An 85% sample is based on the minimum acceptable hit rate to maintain spatial patterns, determined by Ratcliffe (2004). Maintaining the spatial pattern of the complete data set is important so we used this as a benchmark for sampling. An 85% sample was for the purposes of generating as much variability as possible while maintaining the original spatial pattern. Also note that “replacement” in this context refers to subsequent samples; any one point may only be sampled once per iteration in this procedure to mimic Ratcliffe (2004).

  8. 8.

    The program written to perform the test uses double precision that has at least 14 decimal points when dealing with numbers less than unity. The smallest number that we have to deal with in the current analysis (regardless of scale) is 0.000034553. This is well within the limits of double precision.

  9. 9.

    It should be noted that the role of local spatial analysis has been growing in interest in recent years (Lloyd 2011).

References

  • Andresen MA (2006) A spatial analysis of crime in Vancouver, British Columbia: a synthesis of social disorganization and routine activity theory. Can Geogr 50(4):487–502

    Article  Google Scholar 

  • Andresen MA (2009) Testing for similarity in area-based spatial patterns: a nonparametric Monte Carlo approach. Appl Geogr 29(3):333–345

    Article  Google Scholar 

  • Andresen MA (2010) Canada – United States interregional trade: quasi-points and spatial change. Can Geogr 54(2):139–157

    Article  Google Scholar 

  • Andresen MA, Malleson N (2011) Testing the stability of crime patterns: implications for theory and policy. J Res Crime Delinq 48(1):58–82

    Article  Google Scholar 

  • Anselin L (1995) Local indicators of spatial association – LISA. Geogr Anal 27(2):93–115

    Article  Google Scholar 

  • Bernasco W, Block R (2009) Where offenders choose to attack: a discrete choice model of robberies in Chicago. Criminology 47(1):93–130

    Article  Google Scholar 

  • Blalock HM (1964) Causal inferences in nonexperimental research. University of North Carolina Press, Chapel Hill

    Google Scholar 

  • Burgess EW (1916) Juvenile delinquency in a small city. J Am Inst Crim Law Criminol 6(5):724–728

    Article  Google Scholar 

  • Cayo NR, Talbot TO (2003) Positional error in automated geocoding of residential addresses. Int J Heal Geogr 2(1):1–12

    Article  Google Scholar 

  • Clark WAV, Avery KL (1976) The effects of data aggregation in statistical analysis. Geogr Anal 8(4):428–438

    Article  Google Scholar 

  • Farrell G, Tseloni A, Mailley J, Tilley N (2011) The crime drop and the security hypothesis. J Res Crime Delinq 48(2):147–175

    Article  Google Scholar 

  • Fotheringham AS, Wong DW (1991) The modifiable areal unit problem in multivariate statistical analysis. Environ Plan A 23(7):1025–1044

    Article  Google Scholar 

  • Gehlke CE, Biehl K (1934) Certain effects of grouping upon the size of the correlation coefficient in census tract material. J Am Stat Assoc Suppl 29(185):169–170

    Article  Google Scholar 

  • Glyde J (1856) Localities of crime in Suffolk. J Stat Soc Lond 19(2):102–106

    Article  Google Scholar 

  • Guerry A-M (1833) Essai sur la statistique morale de la France. Crochard, Paris

    Google Scholar 

  • Hipp JR (2007) Block, tract, and levels of aggregation: neighborhood structure and crime and disorder as a case in point. Am Sociol Rev 72(5):659–680

    Article  Google Scholar 

  • Kong R (1997) Canadian crime statistics, 1996. Statistics Canada, Canadian Centre for Justice Statistics, Ottawa

    Google Scholar 

  • Land KC, McCall PL, Cohen LE (1990) Structural covariates of homicide rates: are there any invariances across time and social space? Am J Sociol 95(4):922–963

    Article  Google Scholar 

  • Lloyd CD (2011) Local models for spatial analysis, 2nd edn. CRC Press, Taylor & Francis Group, Boca Raton

    Google Scholar 

  • Matthews SA, Yang T-C, Hayslett KL, Ruback RB (2010) Built environment and property crime in Seattle, 1998–2000: a Bayesian analysis. Environ Plan A 42(6):1403–1420

    Article  Google Scholar 

  • Office for National Statistics (2010). 2008-based subnational population projections for England. Newport, Office for National Statistics. Report available on-line http://www.ons.gov.uk/ons/ . Accessed July 2011

  • Openshaw S (1984a) The modifiable areal unit problem. CATMOG (Concepts and Techniques in Modern Geography) 38. Geo Books, Norwich

    Google Scholar 

  • Openshaw S (1984b) Ecological fallacies and the analysis of areal census data. Environ Plan A 16(1):17–31

    Article  Google Scholar 

  • Osgood DW, Anderson AL (2004) Unstructured socializing and rates of delinquency. Criminology 42(3):519–549

    Article  Google Scholar 

  • Ouimet M (2000) Aggregation bias in ecological research: how social disorganization and criminal opportunities shape the spatial distribution of juvenile delinquency in Montreal. Can J Criminol 42(2):135–156

    Google Scholar 

  • Quetelet LAJ (1831) [1984] Research on the propensity for crime at different ages. Anderson Publishing, Cincinnati

    Google Scholar 

  • Quetelet LAJ (1842) A treatise on man and the development of his faculties. W. and R. Chambers, Edinburgh

    Google Scholar 

  • Ratcliffe JH (2001) On the accuracy of TIGER type geocoded address data in relation to cadastral and census areal units. Int J Geogr Inf Sci 15(5):473–485

    Article  Google Scholar 

  • Ratcliffe JH (2004) Geocoding crime and a first estimate of a minimum acceptable hit rate. Int J Geogr Inf Sci 18(1):61–72

    Article  Google Scholar 

  • Robinson WS (1950) Ecological correlations and the behavior of individuals. Am Sociol Rev 15(3):351–357

    Article  Google Scholar 

  • Savoie J (2002) Crime statistics in Canada, 2001. Statistics Canada, Canadian Centre for Justice Statistics, Ottawa

    Google Scholar 

  • Schulenberg JL (2003) The social context of police discretion with young offenders: an ecological analysis. Can J Criminol Crim Justice 45(2):127–157

    Article  Google Scholar 

  • Shaw CR, McKay HD (1931) Social factors in juvenile delinquency. U.S. Government Printing Office, Washington, DC

    Google Scholar 

  • Shaw CR, MacKay HD (1942) Juvenile delinquency and urban areas: a study of rates of delinquency in relation to differential characteristics of local communities in American cities. University of Chicago Press, Chicago

    Google Scholar 

  • Sherman LW, Gartin PR, Buerger ME (1989) Hot spots of predatory crime: routine activities and the criminology of place. Criminology 27(1):27–56

    Article  Google Scholar 

  • Tseloni A, Mailley J, Farrell G, Tilley N (2010) Exploring the international decline in crime rates. Eur J Criminol 7(5):375–394

    Article  Google Scholar 

  • Wallace M (2003) Crime statistics in Canada, 2002. Statistics Canada, Canadian Centre for Justice Statistics, Ottawa

    Google Scholar 

  • Weisburd D, Bernasco W, Bruinsma GJN (2009) Putting crime in its place: units of analysis in geographic criminology. Springer, New York

    Book  Google Scholar 

  • Weisburd D, Bushway S, Lum C, Yang S-M (2004) Trajectories of crime at places: a longitudinal study of street segments in the City of Seattle. Criminology 42(2):283–321

    Article  Google Scholar 

  • Wooldredge J (2002) Examining the (ir)relevance of aggregation bias for multilevel studies of neighborhoods and crime with an example of comparing census tracts to official neighborhoods in Cincinnati. Criminology 40(3):681–709

    Article  Google Scholar 

  • Zandbergen PA (2008) A comparison of address point, parcel and street geocoding techniques. Comput Environ Urban Syst 32(3):214–232

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Criminology, Institute for Canadian Urban Research Studies, Simon Fraser University, Burnaby, BC, Canada

    Martin A. Andresen

  2. School of Geography, Centre for Spatial Analysis and Policy, Centre for Computational Geography, University of Leeds, Leeds, UK

    Nicolas Malleson

Authors
  1. Martin A. Andresen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nicolas Malleson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Martin A. Andresen .

Editor information

Editors and Affiliations

  1. , Department of Geography & Anthropology, Louisiana State University, E104 Howe-Russell Geoscience Bldg., Baton Rouge, 70803, USA

    Michael Leitner

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Andresen, M.A., Malleson, N. (2013). Spatial Heterogeneity in Crime Analysis. In: Leitner, M. (eds) Crime Modeling and Mapping Using Geospatial Technologies. Geotechnologies and the Environment, vol 8. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-4997-9_1

Download citation

Publish with us

Policies and ethics

Search

Navigation