Crimes between 2000 and 2013 were used to identify different trajectory groups at street segments and intersections. Zero-inflated Poisson regression models were used to identify the trajectories. Pin maps, Ripley's K and neighbor transition matrices were used to show the spatial patterning of the trajectory groups. The trajectory solution with eight classes was selected, based on several model selection criteria. The trajectory of each of those groups followed the overall citywide decline, and were only separated by the mean level of crime. Spatial analysis shows that higher crime trajectory groups were more likely to be nearby one another, potentially suggesting a diffusion process. This study adds additional support to others that have found tight coupling of crime at micro-places. The clustering of trajectories identified a set of street units that disproportionately contributed to the total level of crime citywide in Albany, consistent with previous research; however, the temporal trends over time in Albany differed from those exhibited in previous work in Seattle, but were consistent with patterns in Vancouver. (Publisher abstract modified)
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