Spatiotemporal Crime Patterns Across Six U.S. Cities: Analyzing Stability and Change in Clusters and Outliers

Area of Science:

• Criminology
• Urban Studies
• Spatial Analysis

Background:

• Crime concentration at micro-places is a key area of criminological research.
• Understanding spatial crime patterns is crucial for effective law enforcement and urban planning.

Purpose of the Study:

• To examine crime concentration at micro-places across six large US cities.
• To analyze the spatial clustering of high and low crime areas and identify outliers.
• To assess the temporal stability of micro-place crime classifications.

Main Methods:

• Utilized crime incident data from six US municipal police departments.
• Employed Local Moran's I to identify statistically significant crime clusters and outliers at the street segment level.

Main Results:

• Crime segment classifications demonstrated significant stability over time within cities.
• A large proportion of street segments maintained their classification (47.5%–69.3%) over the study period.
• Outliers revealed significant street-to-street crime variability, indicating localized crime differences.

Conclusions:

• Findings highlight considerable stability in micro-place crime patterns across cities, with variations in spatial clustering.
• Further research into mechanisms shaping spatiotemporal crime patterns can enhance strategic resource allocation at micro-levels.