ANALYSING THE TEMPORAL PATTERN OF CRIME HOTSPOTS IN SOUTH YORKSHIRE, UNITED KINGDOM

Main Article Content

Idowu Innocent Abbas

Abstract

Visualizing the temporal pattern of crime hot spots supports the police authority in allocating resources, tactical planning, better management and decision making processes. This paper aimed at identifying temporal pattern of selected crime types (Antisocial behaviour (ASB), Vehicle crime and violent crime) in South Yorkshire, United Kingdom (UK).The study analysed  2011 South Yorkshire Police recorded crime data using statistical based method (graphical display) in Microsoft excel to identify monthly, seasonal pattern and trends of each crime type. Visual inspection from the temporal pattern of each crime type hot spot (figure 1 to 6) shows relationship between each crime type and months or seasons of the year. Result of the study reveals that autumn 2011 recorded the highest rates of violent crime and Spring 2011 had the lowest rates (figure 6).Finding of the research depicts that vehicle crime were higher in autumn and lower in spring 2011 (figure 4). July 2011 had the highest rates of ASB rates while December 2011 displayed lowest rates in figure 1.Monthly trend of crime in 2011 indicates (figure 5)  that March 2011 had the highest rates of violent crime while September had the lowest rates. An interesting pattern in monthly violent crime was shown in figure 5, as R2 value of 0.67 which reveals strong positive correlation between of the months of the year while R2 value of 0.3967 indicates weak correlation in seasonal trend of violent crime (figure 6). Rates of vehicle crime were higher in January 2011 and lower in April 2011 (figure 3). Monthly pattern of vehicle shows R2 value of 0.01048 in figure 3 shows no correlation between vehicle crime and the months of the year while figure 4 displays a remarkable pattern with R2 value of 0.75 that indicates strong positive correlation between the seasons and vehicle crime. Interestingly, an examination from the R2 of ASB temporal hot spots shows(figure 1 to 2), R2 of 0.00112 shows that no correlation exists between ASB hot spots and the months while strong positive exist between the seasons with R2 value of 0.7392.

Article Details

How to Cite
Abbas, I. I. (2018). ANALYSING THE TEMPORAL PATTERN OF CRIME HOTSPOTS IN SOUTH YORKSHIRE, UNITED KINGDOM. Advances in Social Sciences Research Journal, 5(6). https://doi.org/10.14738/assrj.56.4822
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Articles
Author Biography

Idowu Innocent Abbas, Kaduna State University, Kaduna, Nigeria

Department of Geography, Senior Lecturer

References

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.

CHAINEY, S. and RATCLIFFE, J. (2005). GIS and crime mapping. Wil ley.
COHN, E. G. (1990). Weather and crime. British Journal of criminology, 30 (1), 51-64.

ECK,J.,CHAINEY,S,.CAMERON,J and WILSON,R. (2005). Mapping crime: Understanding hotspots.

EVANS, D. J. and FLETCHER, M. (2000). Fear of crime: Testing alternative hypotheses. Applied geography, 20 (4), 395-411.

HARRIES, K. (2006). Extreme spatial variations in crime density in Baltimore county, MD. Geoforum, 37 (3), 404-416.

LEBEAU, J. L. (2001). 7 mapping out hazardous space for police work1, 2. Mapping and analysing crime data: Lessons from research and practice, 139.

NELSON, A. L., BROMLEY, R. D. F. and THOMAS, C. J. (2001). Identifying micro-spatial and temporal patterns of violent crime and disorder in the British city centre. Applied geography, 21 (3), 249-274.

RATCLIFFE, J. (2010) Crime mapping: Spatial and temporal challenges. Handbook of quantitative criminology, , 5-24.

SANTOS, R. B. (2012). Crime analysis with crime mapping. Sage Publications, Incorporated.
South Yorkshire Police (2011). Police crime data. [online]. Last accessed 30th October 2012 at: http://www.police.uk/data.

TAKAGI, D, IKEDA, Ken’ichi and KAWACHI, Ichiro (2012). Neighborhood social capital and crime victimization: Comparison of spatial regression analysis and hierarchical regression analysis. Social science & medicine, 75 (10), 1895-1902.