Abstract
While the geography of crime has been a focal concern in criminology from the very start of the discipline, the development and use of statistical methods specifically designed for spatially referenced data has evolved more recently. This chapter gives an overview of the application of such methods in research on crime and criminal justice, and provides references to the general literature on geospatial statistics, and to instructive and innovative applications in the crime and criminal justice literature.The chapter consists of three sections. The first section introduces the subject matter and delineates it from descriptive spatial statistics and from visualization techniques (“crime mapping.”) It discusses the relevance of spatial analysis, the nature of spatial data, and the issues of sampling and choosing a spatial unit of analysis. The second section deals with the analysis of spatial distributions. We discuss the specification of spatial structure, address spatial autocorrelation, and review a variety of spatially informed regression models and their applications. The third section addresses the analysis of movement, including spatial interaction models, spatial choice models, and the analysis of mobility triads, in the field of crime and criminal justice.
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Notes
- 1.
Some spatial interaction models are also known as gravity models, because their mathematical form resembles Newton’s Law of Gravitation. This law asserts that the gravitational attraction between two bodies is proportional to the product of their masses divided by the squared distance between them, or \(F = g \cdot {M}_{1} \cdot {M}_{2} \cdot {D}^{-2}\), where g is the gravitational constant. As the physics analogy tends to isolate the model from fruitful application and development in social science (Haynes and Fotheringham, 1984), the term spatial interaction model is preferred here.
- 2.
Note that in the aggregate spatial interaction models, we used index i to refer to the origin location. Here, in the disaggregated discrete choice model, i denotes an individual actor.
References
Andresen MA (2006) Crime measures and the spatial analysis of criminal activity. Br J Criminol 46:258–285
Anselin L (1988) Spatial econometrics: methods and models. Kluwer, Dordrecht
Anselin L (1995) Local indicators of spatial association – Lisa. Geogr Anal 27:93–115
Anselin L (2001) Spatial econometrics. In: Baltagi BH (ed) A companion to theoretical econometrics. Blackwell, Oxford, pp 310–330
Anselin L (2003) Spatial externalities, spatial multipliers, and spatial econometrics. Int Reg Sci Rev 26:153–166
Anselin L, Cohen J, Cook D, Gorr W, Tita G (2000) Spatial analysis of crime. In: Duffee D (ed) Measurement and analysis of crime and justice. National Institute of Justice/NCJRS, Rockville, MD, pp 213–262
Bailey T, Gatrell T (1995) Interactive spatial data analysis. Longman, London
Baller RD, Anselin L, Messner SF, Deane G, Hawkins DF (2001) Structural covariates of U.S. county homicide rates: incorporating spatial effects. Criminology 39:561–590
Baltagi BH, Heun Song S, Cheol Jung B, Koh W (2007) Testing for serial correlation, spatial autocorrelation and random effects using panel data. J Econom 140:5–51
Beirne P (1987) Adolphe Quetelet and the origins of positivist criminology. Am J Sociol 92:1140–1169
Ben-Akiva ME, Lerman SR (1985) Discrete choice analysis: theory and applications to travel demand. MIT Press, Cambridge, MA
Bergstrand JH (1985) The gravity equation in international trade: some microeconomic foundations and empirical evidence. Rev Econ Stat 67:474–481
Berk R, MacDonald JM (2008) Overdispersion and Poisson regression. J Quant Criminol 24:269–284
Bernasco W (2006) Co-offending and the choice of target areas in burglary. J Invest Psychol Offender Profiling 3:139–155
Bernasco W, Block R (2009) Where offenders choose to attack: a discrete choice model of robberies in Chicago. Criminology 47:93–130
Bernasco W, Luykx F (2003) Effects of attractiveness, opportunity and accessibility to burglars on residential burglary rates of urban neighborhoods. Criminology 41:981–1001
Bernasco W, Nieuwbeerta P (2005) How do residential burglars select target areas? A new approach to the analysis of criminal location choice. Br J Criminol 45:296–315
Besag J, Diggle PJ (1977) Simple Monte Carlo test for spatial pattern. Appl Stat 26:327–333
Block R, Galary A, Brice D (2007) The journey to crime: victims and offenders converge in violent index offences in Chicago. Secur J 20:123–137
Bowers KJ, Johnson SD (2003) Measuring the geographical displacement and diffusion of benefit effects of crime prevention activity. J Quant Criminol 19:275–301
Bowers KJ, Johnson SD (2005) Domestic burglary repeats and space-time clusters: the dimensions of risk. Eur J Criminol 2:67–92
Braga AA (2001) The effects of hot spots policing on crime. Ann Am Acad Pol Soc Sci 578:104–125
Brunsdon C (2001) Is ‘statistix inferens’ still the geographical name for a wild goose? Trans GIS 5:1–3
Brunsdon C, Fotheringham AS, Charlton ME (1996) Geographically weighted regression: a method for exploring spatial nonstationarity. Geogr Anal 28:281–298
Bullock HA (1955) Urban homicide in theory and fact. J Crim Law Criminol Police Sci 45:565–575
Bursik RJ Jr, Grasmick HG (1993) Neighborhoods and crime: the dimensions of effective community control. Lexington Books, New York
Cahill M, Mulligan G (2007) Using geographically weighted regression to explore local crime patterns. Soc Sci Comput Rev 25:174–193
Cascetta E, Pagliara F, Papola A (2007) Alternative approaches to trip distribution modelling: a retrospective review and suggestions for combining different approaches. Pap Reg Sci 86:597–620
Caywood TOM (1998) Routine activities and urban homicides: a tale of two cities. Homicide Stud 2:64–82
Chainey S, Ratcliffe J (2005) GIS and crime mapping. Wiley, London
Chaix B, Merlo J, Chauvin P (2005) Comparison of a spatial approach with the multilevel approach for investigating place effects on health: the example of healthcare utilisation in France. J Epidemiol Community Health 59: 517–526
Clare J, Fernandez J, Morgan F (2009) Formal evaluation of the impact of barriers and connectors on residential burglars’ macro-level offending location choices. Aust N Z J Criminol 42:139–158
Cliff AD (1973) A note on statistical hypothesis testing. Area 5:240
Cliff AD Ord JK (1973) Spatial autocorrelation. Pion Limited, London
Cohen LE, Felson M (1979) Social change and crime rate trends: a routine activity approach. Am Sociol Rev 44: 588–608
Deane G, Messner S, Stucky T, McGeever K, Kubrin C (2008) Not ‘islands, entire of themselves’: exploring the spatial context of city-level robbery rates. J Quant Criminol 24:337–421
Dubin RA (1998) Spatial autocorrelation: a primer. J Hous Econ 7:304–327
Eck JE, Weisburd D (1995) Crime places in crime theory. In: Eck JE, Weisburd D (eds) Crime and place. Crime prevention studies, vol 4. Criminal Jutice Press and The Police Executive Forum, Monsey, NY and Washington, DC, pp 1–33
Edgington ES (1980) Randomization tests, vol 31. Marcel Dekker Inc, New York
Elffers H (2003) Analysing neighbourhood influence in criminology. Stat Neerl 57:347–367
Elffers H, Reynald D, Averdijk M, Bernasco W, Block R (2008) Modelling crime flow between neighbourhoods in terms of distance and of intervening opportunities. Crime Prev Community Saf 10:85–96
Elffers H, van Baal P (2008) Realistic spatial backcloth is not that important in agent based simulation research. An illustration from simulating perceptual deterrence. In: Eck JE, Liu L (eds) Artificial crime analysis systems: using computer simulations and geographic information systems. IGI Global, Hershey, PA, pp 19–34
Flowerdew R, Aitkin M (1982) A method of fitting the gravity model based on the Poisson distribution. J Reg Sci 22:191–202
Flowerdew R, Lovett A (1988) Fitting constrained Poisson regression models to interurban migration flows. Geogr Anal 20:297–307
Fotheringham AS (1983a) A new set of spatial interaction models: the theory of competing destinations. Environ Plan A 15:15–36
Fotheringham AS (1983b) Some theoretical aspects of destination choice and their relevance to production-constrained gravity models. Environ Plan A 15:1121–1132
Fotheringham AS, Pitts TC (1995) Directional variation in distance decay. Environ Plan 27:715–729
Fotheringham AS, Brunsdon C, Charlton M (2002) Geographically weighted regression: the analysis of spatially varying relationships. Wiley, West Sussex, UK
Friendly M (2007) A.-M. Guerry’s moral statistics of France: challenges for multivariable spatial analysis. Stat Sci 22:368–399
Getis A (1990) Screening for spatial dependence in regression analysis. Pap Reg Sci 69:69–81
Getis A (1995) Spatial filtering in a regression framework: experiments on regional inequality, government expenditures, and urban crime. In: Anselin L, Florax RJGM (eds) New directions in spatial econometrics. Springer, Berlin, pp 172–188
Getis A (2007) Reflections on spatial autocorrelation. Reg Sci Urban Econ 37:491–496
Getis A, Griffith D (2002) Comparative spatial filtering in regression analysis. Geogr Anal 34:130–140
Golledge RG, Stimson RJ (1997) Spatial behavior. The Guilford Press, New York
Goodchild MF, Anselin L, Appelbaum RP, Harthorn BH (2000) Toward spatially integrated social science. Int Reg Sci Rev 23:139–159
Gould P (1970) Is statistix inferens the geographical name for a wild goose? Econ Geogr 46:439–448
Greene WH (1997) Econometric analysis, 3rd edn. Prentice-Hall, Upper Saddle River, NJ
Griffith DA (2000) A linear regression solution to the spatial autocorrelation problem. J Geogr Syst 2:141
Griffith D (2006) Hidden negative spatial autocorrelation. J Geogr Syst 8:335–355
Griffiths E, Chavez JM (2004) Communities, street guns and homicide trajectories in Chicago, 1980–1995: merging methods for examining homicide trends across space and time. Criminology 42:941–978
Groff E (2007) Simulation for theory testing and experimentation: an example using routine activity theory and street robbery. J Quant Criminol 23:75–103
Groff ER, McEwen T (2006) Exploring the spatial configuration of places related to homicide events. Institute for Law and Justice, Alexandra, VA
Groff ER, McEwen T (2007) Integrating distance into mobility triangle typologies. Soc Sci Comput Rev 25:210–238
Groff E, Weisburd D, Morris NA (2009) Where the action is at places: examining spatio-temporal patterns of juvenile crime at places using trajectory analysis and GIS. In: Weisburd D, Bernasco W, Bruinsma GJN (eds) Putting crime in its place: units of analysis in geographic criminology. Springer, New York, pp 61–86
Grubesic T, Mack E (2008) Spatio-temporal interaction of urban crime. J Quant Criminol 24:285–306
Guldmann J-M (1999) Competing destinations and intervening opportunities interaction models of inter-city telecommunication. Pap Reg Sci 78:179–194
Haining RP (2003) Spatial data analysis: theory and practice. Cambridge University Press, Cambridge
Harries K, LeBeau J (2007) Issues in the geographic profiling of crime: review and commentary. Police Pract Res 8:321–333
Haynes KA, Fotheringham AS (1984) Gravity and spatial interaction models. Sage, Beverly Hills, CA
Heiss F (2002) Structural choice analysis with nested logit models. Stata J 2:227–252
Heitgerd JL, Bursik RJ Jr (1987) Extracommunity dynamics and the ecology of delinquency. Am J Sociol 92:775–787
Hipp JR (2007) Income inequality, race, and place: does the distribution of race and class within neighborhoods affect crime rates? Criminology 45:665–697
Hunt LM, Boots B, Kanaroglou PS (2004) Spatial choice modelling: new opportunities to incorporate space into substitution patterns. Prog Hum Geogr 28:746–766
Johnson S (2008) Repeat burglary victimisation: a tale of two theories. J Exp Criminol 4:215–240
Kanaroglou PS, Ferguson MR (1996) Discrete spatial choice models for aggregate destinations. J Reg Sci 36:271–290
Kleemans ER (1996) Strategische misdaadanalyse en stedelijke criminaliteit. Een toepassing van de rationele keuzebenadering op stedelijke criminaliteitspatronen en het gedrag van daders, toegespitst op het delict woninginbraak.. Universiteit Twente, Enschede, the Netherlands
Kubrin CE (2003) Structural covariates of homicide rates: does type of homicide matter? J Res Crime Delinq 40: 139–170
Kubrin CE, Stewart EA (2006) Predicting who reoffends: the neglected role of neighborhood context in recidivism studies. Criminology 44:165–197
Land KC, Deane G (1992) On the large-sample estimation of regression models with spatial- or network-effects terms: a two-stage least squares approach. Sociol Methodol 22:221–248
LeSage JP (2004) A family of geographically weighted regression models. In: Anselin L, Florax RJGM, Rey SJ (eds) Advances in spatial econometrics: methodology, tools and applications. Springer, Berlin, pp 241–264
Malczewski J, Poetz A (2005) Residential burglaries and neighborhood socioeconomic context in London, Ontario: global and local regression analysis. Prof Geogr 57:516–529
McCord ES, Ratcliffe JH (2007) A micro-spatial analysis of the demographic and criminogenic environment of drug markets in Philadelphia. Aust N Z J Criminol 40:43–63
McFadden D (1973) Conditional logit analysis of qualitative choice behavior. In: Zarembka P (ed) Frontiers in econometrics. Academic, New York, pp 105–142
McFadden D (1978) Modeling the choice of residential location. In: Karlkvist A, Lundkvist L, Snikars F, Weibull J (eds) Spatial interaction theory and planning models. North-Holland, Amsterdam, pp 75–96
Mears DP, Bhati AS (2006) No community is an island: the effects of resource deprivation on urban violence in spatially and socially proximate communities. Criminology 44:509–548
Mei C-L, He S-Y, Fang K-T (2004) A note on the mixed geographically weighted regression model. J Reg Sci 44:143–157
Messner SF, Anselin L, Baller RD, Hawkins DF, Deane G, Tolnay SE (1999) The spatial patterning of county homicide rates: an application of exploratory spatial data analysis. J Quant Criminol 15:423–450
Messner SF, Tardiff K (1985) The social ecology of urban homicide: an application of the “routine activities” approach. Criminology 23:241–267
Morenoff JD (2003) Neighborhood mechanisms and the spatial dynamics of birth weight. Am J Sociol 108:976–1017
Morenoff JD, Sampson RJ, Raudenbush SW (2001) Neighbourhood inequality, collective efficacy, and the spatial dynamics of urban violence. Criminology 29:517–559
Nagin DS (1999) Analyzing developmental trajectories: semi-parametric, group-based approach. Psychol Methods 4:139–177
Nielsen AL, Lee MT, Martinez R (2005) Integrating race, place and motive in social disorganization theory: lessons from a comparison of Black and Latino homicide types in two immigrant destination cities. Criminology 43:837–872
Oberwittler D, Wikström P-OH (2009) Why small is better: advancing the study of the role of behavioral contexts in crime causation. In: Weisburd D, Bernasco W, Bruinsma GJN (eds) Putting crime in its place: units of analysis in geographic criminology. Springer, New York, pp 35–59
Openshaw S (1984) The modifiable areal unit problem. Geo Books, Norwich
Osgood W (2000) Poisson-based regression analysis of aggregate crime rates. J Quant Criminol 16:21–43
Peeters M (2007) The influence of physical barriers on the journey-to-crime of offenders. Leiden University, Leiden
Pellegrini PA, Fotheringham AS (2002) Modelling spatial choice: a review and synthesis in a migration context. Prog Hum Geogr 26:487–510
Pentland WE, Lawton MP, Harvey AS, McColl MA (eds) (1999) Time use research in the social sciences. Springer, New York
Pizarro JM, Corsaro N, Yu S-sV (2007) Journey to crime and victimization: an application of routine activities theory and environmental criminology to homicide. Vict Offenders 2:375–394
Pooler J (1994) An extended family of spatial interaction models. Prog Hum Geogr 18:17–39
Ratcliffe JH (2001) Residential burglars and urban barriers: a quantitative spatial study of the impact of canberra’s unique geography on residential burglary offenders. Criminology Research Council, Canberra
Ratcliffe JH (2006) A temporal constraint theory to explain opportunity-based spatial offending patterns. J Res Crime Delinq 43:261–291
Raudenbush SW, Sampson RJ (1999) Ecometrics: towards a science of assessing ecological settings, with application to the systematic social observation of neighbourhoods. Sociol Methodol 29:1–41
Rengert GF (1981) Burglary in Philadelphia: a critique of an opportunity structure model. In: Brantingham PJ, Brantingham PL (eds) Environmental criminology. Sage, Beverly Hills, CA, pp 189–202
Reynald D, Averdijk M, Elffers H, Bernasco W (2008) Do social barriers affect urban crime trips? The effects of ethnic and economic neighbourhood compositions on the flow of crime in The Hague, The Netherlands. Built Environ 34:21–31
Robinson WS (1950) Ecological correlations and the behavior of individuals. Am Sociol Rev 15:351–357
Rosenfeld R, Fornango R, Renfigo AF (2007) The impact of order-maintenance policing on New York City homicide and robbery rates: 1988–2001. Criminology 45:355–384
Rossmo DK (2000) Geographic profiling. CRC, Boca Raton, FL
Sampson RJ, Raudenbush SW, Earls F (1997) Neighborhoods and violent crime: a multilevel study of collective efficacy. Science 277:918–924
Schlich R, Axhausen K (2003) Habitual travel behaviour: evidence from a six-week travel diary. Transportation 30:13–36
Shaw CR, McKay HD (1942) Juvenile delinquency and urban areas. University of Chicago Press, Chicago
Smith TS (1976) Inverse distance variations for the flow of crime in urban areas. Soc Forces 54:802–815
Smith W, Bond JW, Townsley M (2009) Determining how journeys-to-crime vary: measuring inter- and intra-offender crime trip distributions. In: Weisburd D, Bernasco W, Bruinsma G (eds) Putting crime in its place: units of analysis in geographic criminology. Springer, New York, pp 217–236
St. Jean PKB (2007) Pockets of crime. broken windows, collective efficacy, and the criminal point of view. University of Chicago Press, Chicago
Stouffer SA (1940) Intervening opportunities: a theory relating mobility and distance. Am Sociol Rev 5:845–867
Stouffer SA (1960) Intervening opportunities and competing migrants. J Reg Sci 2:1–26
Summerfield MA (1983) Populations, samples and statistical inference in geography. Prof Geogr 35:143–149
Thill J-C (1992) Choice set formation for destination choice modelling. Prog Hum Geogr 16:361–382
Tita G, Griffiths E (2005) Traveling to violence: the case for a mobility-based spatial typology of homicide. J Res Crime Delinq 42:275–308
Tobler WR (1970) A computer movie simulating urban growth in the Detroit region. Economic Geography 46: 234–240
Tolnay SE, Deane G, Beck EM (1996) Vicarious violence: spatial effects on southern lynchings, 1890–1919. Am J Sociol 102:788–815
Van Wilsem J (2003) Crime and context: the impact of individual, neighborhood, city and country characteristics on victimization. Thela Thesis, Amsterdam
Van Wilsem J, Wittebrood K, De Graaf ND (2006) Socioeconomic dynamics of neighborhoods and the risk of crime victimization: a multilevel study of improving, declining, and stable areas in the Netherlands. Soc Probl 53: 226–247
Velez MB (2001) The role of public social control in urban neighborhoods: a multilevel study of victimization risk. Criminology 39:837–864
Wadycki W (1975) Stouffer’s model of migration: a comparison of interstate and metropolitan flows. Demography 12:121–128
Warren J, Reboussin R, Hazelwood RR, Cummings A, Gibbs N, Trumbetta S (1998) Crime scene and distance correlates of serial rape. J Quant Criminol 14:35–59
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 42:283–322
Weisburd D, Wyckoff LA, Ready J, Eck J, Hinkle JC, Gajewski F (2006) Does crime just move around the corner? A controlled study of spatial displacement and diffusion of crime control benefits. Criminology 44:549–592
Weisburd D, Bernasco W, Bruinsma GJN (eds) (2009) Putting crime in its place: units of analysis in geographic criminology. Springer, New York
Wikström P-OH, Sampson RJ (2003) Social mechanisms of community influences on crime and pathways in criminality. In: Lahey BB, Moffitt TE, Caspi A (eds) Causes of Conduct Disorder and Juvenile Delinquency. The Guildord Press, New York/London, pp. 118–148
Wilcox P, Madensen TD, Tillyer MS (2007) Guardianship in context: implications for burglary victimization risk and prevention. Criminology 45:771–803
Wiles P, Costello A (2000) The ‘road to nowhere’: the evidence for traveling criminals (No. Home Office Research Study (HORS) 207). Home Office, Research, Development and Statistics Directorate, London
Wilson AG (1971) A family of spatial interaction models, and associated developments. Environ Plan 3:1–32
Wilson AG, Bennett RJ (1985) Mathematical models in human geography. Wiley, New York
Wilson R, Maxwell C (2007) Research in geographic profiling: remarks from the guest editors. Police Pract Res 8:313–319
Wyant BR (2008) Multilevel impacts of perceived incivilities and perceptions of crime risk on fear of crime: isolating endogenous impacts. J Res Crime Delinq 45:39–64
Zipf GK (1946) The P1P2/D hypothesis: on the intercity movement of persons. Am Sociol Rev 11:677–686
Zipf GK (1949) Human behavior and the principle of least effort. an introduction to human ecology. Addison-Wesley, Cambridge, MA
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Bernasco, W., Elffers, H. (2010). Statistical Analysis of Spatial Crime Data. In: Piquero, A., Weisburd, D. (eds) Handbook of Quantitative Criminology. Springer, New York, NY. https://doi.org/10.1007/978-0-387-77650-7_33
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