SPATIAL TEMPORAL ANALYSIS OF RURAL CRIME HOT SPOT ZONE USING GIS: A PART OF COIMBATORE


SPATIAL TEMPORAL ANALYSIS OF RURAL CRIME HOT SPOT ZONE USING GIS: A PART OF COIMBATORE


Thangavelu A1*, Sapna K2, Sathyaraj SR1, Balsubramanian S1

1*DRDO-BU CLS, Bharathiar University, Coimbatore – 641016.
2Department of Environmental Science, PSG College of Arts and Science, Coimbatore – 641004.


American Journal of Geographical Research and Reviews

Spatio-temporal analysis is one of the suitable method in crime analysis. It is ability to visualize the spatial patterns and control emotionally over a time-ordered sequence of spatial variation. It has been involved the spatial modeling and models of location- allocation, spatial interaction, spatial choice with search, spatial optimization and space-time. Spatio-Temporal Analysis of Crime (STAC) is a powerful tool to identify the crime patterns and detect the crime hot clusters in identifying the hotspot areas. The aim of the objective study is to analyze the spatial effects based on space and time difference among the divisions (space and time) and rate of change. The different types of crime occurrence data were collected from fourteen rural police jurisdiction (2003-2006) in Coimbatore district, TamilNadu. For this analysis, crime occurrence data were used through ArcGIS 10.2 version. The study was analyzed the random walk incidences, and moving path of the peak incidences which are effective models used for entire surrounding area. The study was concluded that spatial-temporal dimension of crime in rural police jurisdictions and explaining how these outcomes used to assist the advance development of crime prevention strategies.


Keywords: Crime, Coimbatore, GIS, Space, Time.

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How to cite this article:
Thangavelu A, Sapna K, Sathyaraj SR, Balsubramanian S. SPATIAL TEMPORAL ANALYSIS OF RURAL CRIME HOT SPOT ZONE USING GIS: A PART OF COIMBATORE. American Journal of Geographical Research and Reviews, 2020; 3:15.


References:

1. Al-Madfai, H., Ivaha, C., Higgs, G., Ware, A., Corcoran, J. (2007). “The Spatial Dissaggrega-tion Approach to Spatio-Temporal Crime Fore-casting,” International Journal of Innovative Computing, Information and Control, Vol. 3, Number 3.
2. Andrews, P. P. and Peterson, M. B. (1990) Crim-inal intelligence analysis. Loomis, CA: Palmer Enterprises.
3. Andrienko, N., Andrienko, G., & Gatalsky, P. (2003). Exploratory spatio-temporal visualisation: an analytical review. Journal of Visual Languages and Computing, 14, 503–541.
4. Audit Commission (1993). Helping with enquiries: Tackling crime effectively. London: HMSO.
5. Barnard, G. A. (1963). “Comment on ‘The Spec-tral Analysis of Point Processes’ by M. S. Bart-lett”, Journal of the Royal Statistical Society, Se-ries B, 25, 294.
6. Block, C. R. (1995) STAC hot-spot areas: a sta-tistical tool for law enforcement decisions, Crime Analysis through Computer Mapping, pp.15-32.
7. Block, R.L. & Block, C.R. (1995). Space, Place and Crime: Hot Spot Areas and Hot places of Liquor-Related Crime. In J.E. Eck, & D. Weis-burd (eds.), Crime and Place: Crime Prevention Studies Vol 5. Monsey NY: Criminal Justice Press.
8. Brantingham, P.J. and Jeffery, C.R. 1981. After-word: Crime, Space, and Criminological Theory. In P.J. Brantingham and P.L. Brantingham (eds.) Environmental Criminology. Sage Publications, Beverly Hills.
9. Canter, P. (1998). Geographic Information Sys-tems and Crime Analysis in Baltimore County, Maryland. In D. Weisburd & T. McEwen (eds.), Crime Mapping and Crime Prevention: Crime Prevention Studies Vol 8. Monsey NY: Criminal Justice Press. Distribution of Repeat Victimiza-tion, British Journal of Criminology, 37(2), 224–241.
10. Cook, P. (1998) Mapping a murderer’s path. In N. LaVigne and J. Wartell (Eds.), Crime mapping case studies: Successes in the field (pp. 123–128). Washington, DC: Police Executive Re-search Forum.
11. Diggle, P. J., Chetwynd, A. G., H¨aggkvist, R. and Morris, S. E. (1995) Second-order analysis of space-time clustering. Statistical Methods in Medical Research, 4, 124.136.
12. Dwass, M (1957). “Modified randomization tests for nonparametric hypotheses”. Annals of Math-ematical Statistics, 28, 181-187.
13. Dykes, J. A. (1996). Dynamic maps for spatial science: a unified approach to cartographic vis-ualisation. In D. Parker (Ed.), Innovation sin GIS 3 (pp. 177–187). Taylor and Francis.
14. Eck, J.E. (1998). What Do These Dots Mean? Mapping Theories with Data. In D. Weisburd, & T. McEwen (eds.), Crime Mapping and Crime Prevention: Crime Prevention Studies Vol 8. Monsey NY: Criminal Justice Press.
15. Fairbairn, D., Andrienko, G., Andrienko, N., Buz-iek, G., & Dykes, J. (2001). Representation and its relationship with cartographic visualisation. Cartography and Geographic Information Sci-ence, 28, 13–28. Fisher (Ed.), Innovations in GIS 2 (pp. 169–187). London: Taylor and Francis.
16. Gottlieb, S., Arenberg, S. and Singh, R. (1998) Crime analysis: From first report to final arrest. Montclair: Alpha Publishing.
17. Harries KD (1999) Mapping crime: principles and practice. US Department of Justice, Washington DC
18. Harries, K. (1990). Geographic Factors in Polic-ing. Washington, D.C.: Police Executive Re-search Forum.
19. Heaton, R. (2000) The prospects for intelligence-led policing: Some historical and quantitative considerations, Policing and Society, 9 (4), 337–356
20. Hirschfield, A. and Bowers, K. (2001) Mapping and Analysing Crime Data: Lessons from Re-search and Practice, Taylor and Francis, New York.
21. Hirschfield, A., Bowers, K., & Brown, P.J.B. (1995). Exploring Relationships between Crime and Disadvantage on Merseyside: An Analysis using Crime Statistics, Census Data and Geo-graphical Information Systems, European Jour-nal on Criminal Policy and Research, 3(3), 93–112.
22. HMIC [Her Majesty’s Inspectorate of Constabu-lary] (1997) Policing with intelligence. London: Her Majesty’s Inspectorate of Constabulary.
23. Hubbs, R. (1998). “The Greenway rapist case: Matching repeat offenders with crime locations.” In N. LaVigne & J. Wartell (Eds.). Crime Mapping Case Studies: Successes in the Field (pp. 93–98). Washington, DC: Police Executive Research Forum.
24. ICJIA [Illinois Criminal Justice Information Author-ity] (1996) STAC user manual. Chicago: ICJIA.
25. Johnson, S.D., Bowers, K., & Hirschfield, A. (1997). New Insights in the Spatial and Temporal.
26. Kennedy, D. M., Braga, A. A. and Piehl, A. M. (1998) The (un) known universe: Mapping gangs and gang violence in Boston. In D. Weisburd & T. McEwen (Eds.), Crime mapping and crime prevention (pp. 219–262). Monsey, NY: Criminal Justice Press.
27. Knox, E. G. (1964). “The detection of space-time interactions”. Applied Statistics, 13, 25-29.
28. Knox, E. G. (1963). “Detection of low intensity epidemicity: application in cleft lip and palate”. British Journal of Preventive and Social Medi-cine, 18, 17-24.
29. Koussoulakou, A., & Kraak, M.-J. (1992). Spatio-temporal maps and cartographic communication. Cartographic Journal, 29, 101–108.
30. Levine, Ned (2002).CrimeStat: A Spatial Statis-tics Program for the Analysis of Crime Incident Locations (version 2.0). Ned Levine & Associ-ates, Houston, TX; National Institute of Justice, Washington, DC.
31. Maguire, M. (2000) Policing by risks and targets: Some dimensions and implications of intelli-genceled crime control, Policing and Society, 9(4), 315–336.
32. Mantel, N. and J. C. Bailar (1970). “A class of permutational and multinomial test arising in epi-demiological research”, Biometrics, 26, 687-700.
33. Mantel, Nathan (1967). “The detection of disease clustering and a generalized regression ap-proach”. Cancer Research, 27, 209-220.
34. Miller HJ (2005) A measurement theory for time geography. Geogr Anal 37(1):17–45
35. Ratcliffe, J. H. (2002) Intelligence-led policing and the problems of turning rhetoric into prac-tice, Policing and Society, 12(1), 53–66.
36. RatCliffe, J.H. and McCullagh, M.J. (1998). Iden-tifying Repeat victimisation with GIS. British Journal of criminology, 38(4): 651-662
37. Rengert, G. (1997). Auto Theft in Central Phila-delphia. In R. Homel (ed.), Policing for Preven-tion: Reducing Crime, Public Intoxication and In-jury, Crime Prevention Studies Vol 7. Monsey NY: Criminal Justice Press.
38. Rich, T. (1995). The use of computerized map-ping in crime control and prevention programs. Washington, DC: US Department of Justice, Of-fice of Justice Programs.
39. Rich, T. (2001). “School COP: Software for ana-lyzing and mapping school incidents.” Crime Mapping News 3(2): 4-6.
40. Rossmo, Kim. 1995. Geographic Profiling: Tar-get Patterns Of Serial Murderers. Unpublished Ph.D. dissertation. Burnaby: Simon Fraser Uni-versity.
41. Shepherd, I. D. H. (1995). Putting time on the map: dynamic displays in data visualization and GIS. In P. F.
42. Smith, A. (1997) Intelligence led policing. Interna-tional Association of Law Enforcement Intelli-gence Analysts, Inc.
43. Weisburd, D (2001). Translating Research Into Practice: Reflections on the Diffusion of Innova-tion in Crime Mapping. Dallas: International Crime Mapping Research Conference, Texas, CMRC: NIJ.