Abstract
This article presents the results of a quantitative survey in a central European city, where more than 1,500 citizens were asked about their fear of becoming a victim of burglary. Additionally, vulnerabilities to crimes were measured. A large set of spatial data was analyzed with different spatial-statistic methods and visualized in maps intended to serve as a summarized overview of the citizens’ fear of crime. First results show that there are specific hot spots in fear of burglary, majorly in the core of the city, and statistically significant differences in the pattern of fear of burglary between the districts. Furthermore, areas with a lack of technical safety standards were identified. This information shall help to start local crime prevention programs to reduce fear of crime and increase the quantity of protected homes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Anselin, L., Cohen, J., Cook, D., Gorr, W., Tita, G.: Spatial Analyses of Crime. Criminal Justice 4, 213–262 (2000)
Cohen, L.E., Felson, M.: Social Change and Crime Rate Trends: A Routine Activity Approach. American Sociological Review 44, 588–608 (1979)
Cornish, D.B., Clarke, R.V. (eds.): The Reasoning Criminal: Rational Choice Perspectives on Offending. Springer, New York (1986)
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)
Harries, K.: Mapping Crime: Principle and Practice. U.S. Department of Justice, National Institute of Justice, Washington, DC (1999)
McIntyre, J.: Public Attitudes toward Crime and Law Enforcement. The Annals of the American Academy of Political and Social Science 374(1), 34–46 (1967)
Doran, B.J., Burgess, M.B.: Putting Fear of Crime on the Map. Investigating Perceptions of Crime Using Geographic Information Systems. Springer, New York (2012)
Skogan, W.G.: Public Policy and the Fear of Crime in Large American Cities. In: Gardiner, J.A. (ed.) Public Law and Public Policy, pp. 1–18. Praeger, New York (1977)
Holt, J.B., Lo, C.P., Hodler, T.W.: Dasymetric Estimation of Population Density and Areal Interpolation of Census Data. Cartography and Geoinformation Science 31(2), 103–121 (2004)
Openshaw, S.: The Modifiable Areal Unit Problem. Concepts and Techniques in Modern Geography 38 (1984)
Bailey, T.C., Gatrell, A.C.: Interactive Spatial Data Analysis. Longman (1995)
Anselin, L.: Local Indicators of Spatial Association-LISA. Geographical Analysis 27(2), 93–115 (1995)
Eck, J., Chainey, S.P., Cameron, J., Leitner, M., Wilson, R. (eds.): Mapping Crime: Understanding Hotspots. National Institute of Justice, Washington DC (2005)
Levine, N.: CrimeStat 3.0. A Spatial Statistics Program for the Analysis of Crime Incident Locations. Ned Levine & Associates, Houston and U.S. Department of Justice, Washington DC (2004), http://www.icpsr.umich.edu/CrimeStat/download.html
Getis, A., Ord, J.K.: Local Spatial Statistics: An Overview. In: Longley, P., Batty, M. (eds.) Spatial Analysis: Modelling in a GIS Environment. John Wiley & Sons (1996)
Gatrell, A.C., Bailey, T.C., Diggle, P.J., Rowlingson, B.S.: Spatial Point Pattern Analysis and Its Application in Geographical Epidemiology. Transactions of the Institute of British Geographers 21, 256–274 (1996)
Borruso, G.: Network Density Estimation: Analysis of Point Patterns over a Network. In: Gervasi, O., Gavrilova, M.L., Kumar, V., Laganá, A., Lee, H.P., Mun, Y., Taniar, D., Tan, C.J.K. (eds.) ICCSA 2005. LNCS, vol. 3482, pp. 126–132. Springer, Heidelberg (2005)
Moran, P.A.P.: The Interpretation of Statistical Maps. Journal of the Royal Statistical Society. Series B. Methodological. 10(2), 243–251 (1948)
Moran, P.A.P.: Notes on Continuous Stochastic Phenomena. Biometrika 37(1/2), 17–23 (1950)
Silverman, B.W., Jones, M.C., Fix, E., Hodges, J.L.: An Important Contribution to Nonparametric Discriminant Analysis and Density Estimation. Commentary on Fix and Hodges (1951). International Statistical Review 57(3), 233–238 (1951)
Clark, P.J., Evans, F.C.: Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations. Ecology 35, 445–453 (1954)
King, B.: Step-Wise Clustering Procedures. Journal of the American Statistical Association 62(317), 86–101 (1967)
Danese, M., Lazzari, M., Murgante, B.: Kernel Density Estimation Methods for a Geostatistical Approach in Seismic Risk Analysis: The Case Study of Potenza Hilltop Town (Southern Italy). In: Gervasi, O., Murgante, B., Laganà, A., Taniar, D., Mun, Y., Gavrilova, M.L. (eds.) ICCSA 2008, Part I. LNCS, vol. 5072, pp. 415–429. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lederer, D. (2012). Am I Safe in My Home? Fear of Crime Analyzed with Spatial Statistics Methods in a Central European City. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31075-1_20
Download citation
DOI: https://doi.org/10.1007/978-3-642-31075-1_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31074-4
Online ISBN: 978-3-642-31075-1
eBook Packages: Computer ScienceComputer Science (R0)