SPATIOTEMPORAL PATTERNS IN BEHAVIORAL & OPPORTUNISTIC CRIME IN DENVER, COLORADO (2020–2025)

Abstract

Understanding how different types of crime respond to major societal disruptions is essential for effective public safety planning and resource allocation. This study explores the spatiotemporal patterns of reported crime in Denver, Colorado, from 2020 to 2025, with a focus on changes in crime type and frequency across phases of the COVID-19 pandemic. Denver’s consolidated city-county jurisdiction ensures consistent geographic coverage and data reliability. Crimes are grouped into two broad categories: behavioral offenses, such as assault and domestic violence; and opportunistic offenses, such as burglary and theft. Comparing these classifications provides insight into how offender motivations may vary in response to external pressures such as lockdowns, economic instability, and diminished public activity. Using geocoded incident data aggregated at the census tract level, this study applies geographic information systems (GIS) and interactive visualizations in Tableau Public to identify emerging trends and spatial shifts over time. The project adopts an exploratory approach, allowing users to filter and compare crime patterns across pandemic phases and neighborhoods. Preliminary findings suggest that behavioral and opportunistic crimes responded differently to pandemic-related disruptions. This dashboard-driven model highlights how large-scale societal changes can influence criminal behavior and underscores the necessity for adaptable, data-informed public safety strategies. The framework is adaptable to other cities, temporal contexts, or forms of disruption, demonstrating the utility of exploratory geovisualization tools in understanding complex urban dynamics.