Spatial Pattern of Burglary in South Yorkshire Using Geographic Information System (GIS)
International Journal of Astrophysics and Space Science
Volume 4, Issue 1, February 2016, Pages: 1-11
Received: Jan. 3, 2016; Accepted: Jan. 11, 2016; Published: Jan. 23, 2016
Views 3933      Downloads 108
Author
Gaylan Rasul Faqe Ibrahim, Geography Department, Faculty of Arts, Soran University, Soran City, Erbil, Kurdistan Region, Iraq
Article Tools
Follow on us
Abstract
Burglary is an offence committed against others’ property and it is considered a violent crime. Nowadays to monitor and detect burglary crime geographic information system (GIS) is used broadly. The aim of this study is to analyses spatial pattern and spatial dependency of burglary in the study area by applying GIS techniques. For understanding the crime pattern better and creating plans for preventing and reducing crime and using the resources and places, sometimes might make greatest differences; the identification of hotspots in time is very important. The data for this study obtained from the secondary data; boundary shape file of the study area, socioeconomic data and burglary data for November 2012 were gained. The outcome of the study shows that the distribution of burglary is clustered. It is clear from the results that the rate of burglary strongly affects the percentage of unemployed people; also the percentage of non-white and young people (aged 20-24) does not significantly correlate with burglary.
Keywords
Crime, Burglary, Spatial Pattern, GIS, South Yorkshire
To cite this article
Gaylan Rasul Faqe Ibrahim, Spatial Pattern of Burglary in South Yorkshire Using Geographic Information System (GIS), International Journal of Astrophysics and Space Science. Vol. 4, No. 1, 2016, pp. 1-11. doi: 10.11648/j.ijass.20160401.11
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
AKINS, S. (2003). Racial segregation and property crime: Examining the mediating effect of police strength. Justice quarterly, 20 (4), 675-695.
[2]
BRUNSDON, Chris, CORCORAN, Jonathan and HIGGS, Gary (2007). Visualising space and time in crime patterns: A comparison of methods. Computers, environment and urban systems, 31 (1), 52-75.
[3]
BUONANNO, Paolo and MONTOLIO, Daniel (2008). Identifying the socio-economic and demographic determinants of crime across Spanish provinces. International review of law and economics, 28 (2), 89-97.
[4]
CARMICHAEL, F. and WARD, R. (2000). Youth unemployment and crime in the English regions and wales. Applied economics, 32 (5), 559-571.
[5]
CHAINEY, S. and RATCLIFFE, J. (2005). GIS and crime mapping. Wiley.
[6]
Home Office (2012). A new approach to fighting crime. [online]. Last accessed 20 October 2012 at: http://www.jdi.ucl.ac.uk.
[7]
KAWACHI, I., KENNEDY, B. P. and WILKINSON, R. G. (1999). Crime: Social disorganization and relative deprivation. Social science & medicine, 48 (6), 719-731.
[8]
MARTIN, D. (2000). Towards the geographies of the 2001 UK census of population. Transactions of the institute of British geographers, 25 (3), 321-332.
[9]
MESEV, V. (1998). The use of census data in urban image classification. Photogrammetric engineering and remote sensing, 64 (5), 431-436.
[10]
NAGIN, D. S. and PATERNOSTER, R. (1993). Enduring individual differences and rational choice theories of crime. Law & soc'y rev., 27, 467.
[11]
OPENSHAW, S. (1983). The modifiable areal unit problem. Geo Books Norwich. 38.
[12]
RATCLIFFE, J. H. (2002). Aoristic signatures and the spatio-temporal analysis of high volume crime patterns. Journal of quantitative criminology, 18 (1), 23-43.
[13]
SANTOS, R. B. (2012). Crime analysis with crime mapping. Sage Publications, Incorporated.
[14]
South Yorkshire Police (2012). NOT PROTECTIVELY MARKED SOUTH YORKSHIRE POLICE [online]. Last accessed 17th January 2013 at: http://www.southyorks.police.uk.
[15]
SOUTH YORKSHIRE POLICE (2012). Police crime data. [online]. Last accessed November 2012 at: http://www.police.uk/data.
[16]
STILLWELL, J. and DUKE-WILLIAMS, O. (2007). Understanding the 2001 UK census migration and commuting data: The effect of small cell adjustment and problems of comparison with 1991. Journal of the royal statistical society: Series A (statistics in society), 170 (2), 425-445.
[17]
THE GUARDIAN (2010). Crime statistics: Get the rates where you live. [Online]. Last accessed 15th January 2013 at: http://www.guardian.co.uk/.
[18]
THOMAS, W. I. and ZNANIECKI, F. (2012). Social disorganization theory.
[19]
WILLIAMSON, D., MCLAFFERTY, S., GOLDSMITH, V., MOLLENKOPF, J AND MCGUIRE, P., (1999). `A better method to smooth crime incident data’, ESRI news. [online]. Last accessed 20 January 2013 at: http://www.esri.com.
[20]
WINCHESTER, S., JACKSON, H. and BRITAIN, G. (1982). Residential burglary: The limits of prevention. HM Stationery Office.
ADDRESS
Science Publishing Group
548 FASHION AVENUE
NEW YORK, NY 10018
U.S.A.
Tel: (001)347-688-8931