The spatial patterns of four types of crimes (assault, robbery, auto-theft, and burglary) and their relationships with the selected socio-economic characteristics for the City of Omaha, Nebraska, were examined in this research. The crime data were based on the 2000 police reported crime and the socio-economic data were extracted from the 1997 American Community Survey and land use data from the 2000 Omaha parcel file. The location quotients of crimes (LQCs) were used to measure the relative specialization and structure of crimes for each census tract, and as the dependent variables for the statistical analysis. GIS techniques such as geocoding, spatial aggregation, and spatial analysis were used for crime mapping and crime analysis. Factor analysis and multiple regression models were employed to reveal the crime-causation relationships. Major findings of this research include: (1) LQCs highlight the specialization of crime and can be effectively used for GIS-based visualization and statistical analysis of crime; (2) the North Omaha and the downtown areas (high-crime districts) have relatively higher occurrences of violent crime and diversified structure of crimes while west Omaha (low crime districts) has a relatively specialized crime structure that is dominated by property crimes; (3) a modest proportion of the variance of crimes can be significantly explained by the statistical models