Crime and risk mapping from historic count data in Leicester City

This thesis map crime and risk of three crimes from the historic count data in Leicester city from 1999/2003. Observed risk is assess by mapping the crime data and normalized with beat area and population density. As a result of the normalization different pattern emerges, these reveal the ability the GIS to show risk when normalized using different denominators. Objective risk is measured by statistical relationship between the various socio economic factors or variables that are used as surrogate to arrive at the statistical view of risk. To arrive at the statistical view of risk, these variables are regressed against crime. The model of mathematical risk assessment is the main focus of the current study. Using mathematical method risk assessment can be objectively defined so that two people can take the same data and come up with a similar result. The result of this study may be useful for insurance industry, police operation and decision making.