Count-Based Trajectory Analysis Applied to Spatio-Temporal Larceny Incidence in Urban Environments

Larceny is considered a high-impact crime in Mexico City because of its effect on public perceptions of safety. Understanding its spatial and temporal dynamics is therefore important for designing effective public safety policies. This study extends the Trajectory Analysis framework to examine the spatio-temporal evolution of larceny in Mexico City from 2020 to 2024. The proposed approach incorporates Kendall’s Tau (${\tau }_k$) to quantify trend strength across trajectory types, including Gain, Loss, and alternation patterns, and introduces a multi-resolution analysis to identify and quantify spatial exchange patterns in crime distribution. Results indicate an overall decline in larceny across the city, but also reveal spatial exchanges, suggesting that reductions in some areas may reflect displacement rather than elimination. By capturing both crime reduction and redistribution patterns, the framework provides a more nuanced basis for data-driven public safety strategies.