Abstract
Since the Agent-based simulation tool was introduced into criminology research, most work concentrated on crime theory validation or hypothesis testing, little was contributed to crime spatial pattern replication. In this paper, using street network and subway network as the landscape and proposing a statistic-based instead of predefined human mobility pattern as the individual’s routine activity, the spatial distribution of burglary in Beijing is simulated and valid by the actual pattern. The result indicates that the Agent-based modeling method partly detects the crime hotspots and the spatial pattern of crime, and specifically the crime level on the nodes with different accessibility is proved to be identical to the actual one. The study made in this work demonstrates that Agent-based modeling is a potential tool to predict or explain crime pattern in space, and also some further work which aims to improve its validation is discussed in the end of this paper.
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References
Brantingham, P.L., Glasser, U., Kinney, B., et al.: A computational model for simulating spatial aspects of crime in urban environments. In: IEEE International Conference on Systems, Man and Cybernetics, vol. 4, pp. 3667–3674 (2005)
Malleson, N., Heppenstall, A., See, L.: Crime reduction through simulation: An Agent-based model of burglary. Computers, Environment and Urban Systems 34(3), 236–250 (2009)
Groff, E.R.: Simulation for theory testing and experimentation: An example using routine activity theory and street robbery. Journal of Quantitative Criminology 23, 75–103 (2007a)
Groff, E.R.: ‘Situating’ simulation to model human spatial-temporal interactions: An example using crime events. Transactions in GIS 11(4), 507–530 (2007b)
Groff, E.R.: Adding the Temporal and Spatial Aspects of Routine activities: A further test of routine activity theory. Security Journal 21, 95–116 (2008)
Malleson, N., Birkin, M.: Analysis of crime pattern through the integration of an agent-based model and a population microsimulation. Computer, Environment and Urban system 36(6), 551–561
Brantingham, P.L., Brantingham, P.J.: Nodes, paths and edges: considerations on the complexity of crime and the physical environment. Journal of Environmental Psychology 13, 3–28 (1993)
Brantingham, P.L., Brantingham, P.J.: Mobility, notoriety, and crime: A study of crime patterns in urban nodal points. Journal of Environmental Systems 11, 89–99 (1982)
Gonzálaz, M., Hidalgo, C., Barbasi, A.: Understanding individual human mobility patterns. Nature 453(06958) (2008)
Ni, S.J., Weng, W.G.: Impact of travel patterns on epidemic dynamics in Heterogeneous Spatial Metapopulation networks. Physical Review E 79, 016111 (2009)
Cohen, L.E., Felson, M.: Social change and crime rate trends: A routine activity approach. American Sociological Review 44(4), 588–608 (1979)
Pyle, D.J., Deadman, D.: Crime and the business cycle in post-war Britain. British Journal of Criminology 34, 339–357 (1994)
Deadman, D., Pyle, D.J.: Forecasting Recorded Property Crime Using a Time-Series Econometric Model. British Journal of Criminology 37, 437–445 (1997)
Clarke, R.V., Cornish, D.B.: Rational choice. In: Paternoster, R., Bachman, R. (eds.) Explaining Criminals and Crime, pp. 23–42. Roxbury Publishing Co., Los Angeles (2001)
Cornish, D., Clarke, R.: The Reasoning criminal: Rational choice perspectives on offending. Springer, New York (1986)
Clarke, R.V., Cornish, D.B.: Modeling offender’s decisions: A framework for research and policy. In: Tonry, M., Morris, N. (eds.) Crime and Justice: An Annual Review of Research, vol. 6. University of Chicago Press, Chicago (1985)
Reynald, D.M.: Guardians on Guardianship: Factors affecting the willingness to supervise, the ability to detect potential offenders, and the willingness to intervene. Journal of Research in Crime and Delinquency 47(3), 358–390 (2010)
Anselin, L., Syabri, I., Kho, Y.: GeoDa: An Introduction to Spatial Data Analysis. Geographical Analysis 38(1), 5–22 (2006)
Zipf, G.K.: Human Behavior and the Principle of Least Effort. Addison-Wesley Press, Oxford (1949)
Zhang, L., Messner, S., Liu, J.: An Exploration of the Determinants of Reporting Crime to the Police in the City of Tianjin. China Criminology 45, 959–983 (2007)
Beavon, D.J.K., Brantingham, P.L., Brantingham, P.J.: The influence of street networkson the patterning of property offenses. In: Clarke, R.V. (ed.) Crime Prevention Studies, vol. 2. Criminal Justice Press, New York (1994)
Bevis, C., Nutter, J.B.: Changing Street Layouts to Reduce esidential Crimes. Paper presented at the Annual Meeting of the American Society of Criminology, Atlanta, GA (1977)
Hiller, B.: Can streets be made safe? Urban Design 9, 31–45 (2004)
Newman, O.: Defensible Space: Crime Prevention Through Urban Design. Macmillan, New York (1972)
Johnson, S.D., Bowers, K.J.: Permeability and crimes risk: Are cul-de-sacs safer? Journal of Quantitative Criminology 26(1), 89–111 (2010)
Brantingham, P.J., Brantingham, P.L.: Criminality of place: Crime generators and crime attractors. European Journal of Criminal Policy and Research 3, 5–26 (1995)
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Peng, C., Kurland, J. (2014). The Agent-Based Spatial Simulation to the Burglary in Beijing. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8582. Springer, Cham. https://doi.org/10.1007/978-3-319-09147-1_3
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DOI: https://doi.org/10.1007/978-3-319-09147-1_3
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