Integrating spatial and time sensitive data to monitor social patterns: A dynamic methodology for studying social issues

This research introduces a dynamic methodology that can be used to monitor social issues using spatial and time sensitive data. The methodology was used in a project funded to assess the Highway Watch (R) program administered by the American Trucking Associations, United States Department of Homeland Security. The application of the methodology is of interest to a much wider social science audience, and is the focus of this manuscript. The Highway Watch (R) program was established to be America's 'eyes on the road' in the wake of a post-9/11 society. The program was implemented to train trucking professionals to be on alert and report suspicious activity as a means of public safety. In an assessment of this program, our research team combined two unique datasets to measure the density and frequency of freight truck traffic in a sample of urban and interstate roadways to measure the coverage of potential 'eyes on the road.' Of interest to social scientists and spatial analysts is the use of social, spatial, and industry segment data, integrated with interactive data visualization software to analyze at-risk places and populations. The method serves as a useful tool for monitoring social issues in time and space.