This study applies the crime heartbeat methodology to empirically examine the temporal concentration of crime in a European city (Ghent, Belgium) in relation to police-registered data collected for five specific crime types (aggressive theft, residential burglary, assault and battery incidents, bicycle theft, and car theft) spanning a 12-year period (2007–2018). The temporal concentration of these crime types is quantified by computing the crime heartbeats for each crime type and deriving the Gini index from these heartbeats. In addition to a city-level analysis, this study also examines the temporal concentration of different crime types at the microgeographic level, focusing on grid cells of 200 by 200 m. The results demonstrate that the temporal concentration of crime remains a stable signature across different crime types over the 12-year period. Residential burglaries and bicycle thefts exhibit more homogeneous patterns between Monday and Friday, with two prominent peaks occurring during nighttime and midday. Car theft displays the highest temporal concentration, with a higher intensity during nighttime hours. Furthermore, substantial variations in temporal concentration were identified between hot and hottest spots for each crime type, indicating that crimes rarely coincide temporally across microgeographic units. This study's findings further highlights the importance of understanding the temporal distribution of (microgeographic) crime patterns as well how fine-grained spatiotemporal crime analysis can inform future crime prevention initiatives.
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