Location is considered as an important element in studying tourism security. Therefore, mapping crime hotspots has recently been an interesting research topic in tourism development. In order to identify crime patterns and hotspots, it is essential to create a database containing the required spatial data. It should also be integrated with additional qualitative/quantitative attributes affecting criminal actions. Designing a geographic information system (GIS) can be considered as the most efficient way to deal with this problem considering the complex nature of tourism security. This paper presents the theoretical scheme of spatial data modeling with the purpose of indentifying potential crime zones within a developed park. From the spatial point of view, the factors and the constraints, which make a location vulnerable, are defined. The entities are identified by their attributes and characterized by their relationships. Finally, the conceptual and the logical models to create the crime suitability maps are generated. The models provided in this paper are designed in an explicit way; therefore, they can be easily modified or generalized for any specific case study. The presented data modeling procedure can be applied to generate essential databases for crime mapping via any GIS software.
This study is one of few studies which have investigated spatial data modeling from theoretical point of view for the reduced case of managing the security of a park.
Al-Barmalgy, M., A. Amin and R.M. Shaban, 2014. Methodology for monitoring the qualitative and quantitative features of the phenomenon of vandalism in open spaces using GIS. Journal of Sustainable Development Studies, 4(1): 96-114.
Boakye, K.A., 2010. Studying tourists’ suitability as crime targets. Annals of Tourism Research, 37(3): 727-743.
Brunt, P., R. Mawby and Z. Hambly, 2000. Tourist victimisation and the fear of crime on holiday. Tourism Management, 21(4): 417-424.
Chakrabarty, A., 2011. Ecotourism development and security restructuring: A GI based planning for peaceful dissuasion of anarchism in forest provinces of India. Procedia Social and Behavioral Sciences, 21(1): 108-115.
Chmura, A. and J.M. Heumann, 2005. Logical data modeling: What it is and how to do it. Springer's Integrated Series in Information Systems, US.
Crotts, J.C., 1996. Theoretical perspectives on tourist criminal victimisation. Journal of Tourism Studies, 7(1): 2-9.
Fajemirokun, F., O. Adewale, T. Idowu, A. Oyewusi and B. Maiyegun, 2006. A GIS approach to crime mapping and management in Nigeria: A case study of Victoria Island Lagos. Proceedings of XXIII FIG Congress. pp: 8-13.
Fajuyigbe, O., V.F. Balogun and O.M. Obembe, 2007. Web-based geographical information system (GIS) for tourism in Oyo State, Nigeria. Information Technology Journal, 6(5): 613-622.
Ferreira, S.L.A. and A.C. Harmse, 2000. Crime and tourism in South Africa: International tourists perception and risk. South African Geographical Journal, 82(2): 80-85.
Jones, C., E. Barclay and R. Mawby, 2012. The problem of pleasure: Leisure, tourism and crime. UK: Routledge.
Kalaikumaran, T. and S. Karthik, 2012. Criminals and crime hotspot detection using data mining algorithms: Clustering and classification. International Journal of Advanced Research in Computer Engineering & Technology, 1(10): 225-227.
Michalko, G., 2004. Tourism eclipsed by crime: The vulnerability of foreign tourists in hungary. Journal of Travel and Tourism Marketing, 15(2-3): 159-172.
Pizam, A. and Y. Mansfield, 2006. Tourism security and safety: From theory to practice. Butterworth Heinemann: John Wiley.
Ratcliffe, J. and S. Chainey, 2005. GIS and crime mapping. John Wiley & Sons.
Saravanan, M., R. Thayyil and S. Narayanan, 2013. Enabling real time crime intelligence using mobile GIS and prediction methods. IEEE Proceedings of Intelligence and Security Informatics Conference. pp: 125-128.
Simsion, G.C. and C.W. Graham, 2005. Data modeling essentials. 3rd Edn.: Morgan Kaufmann Publishers.
Teorey, T.J., S.S. Lightstone, T. Nadeau and H.V. Jagadish, 2011. Database modeling and design. 5th Edn.: Morgan Kaufmann Publishers.
Zhang, X., Z. Hu, R. Li and Z. Zheng, 2010. Detecting and mapping crime hot spots based on improved attribute oriented induce clustering. IEEE Proceedings of International Conference on Geoinformatics. pp: 1-5.