International research has consistently shown that urban crime is highly concentrated in a relatively small number of microgeographical places, while most areas experience little or no crime. This finding has shaped the development of place-based crime prevention strategies and data-driven and predictive policing approaches in many countries. However, there is still limited empirical knowledge about whether and how these patterns appear in Norway, and to what extent international findings are transferable to a Norwegian urban context.
This PhD project investigates how crime is distributed across places in Oslo, how spatial patterns evolve over time, and how stable these patterns are. The analyses are based on geocoded police register data and cover multiple crime types at a fine spatial resolution in order to identify systematic differences in crime levels across locations, and their development.
A key premise of the project is that recent technological and methodological advances, particularly within GIS and data-driven spatial analysis, have enabled much more precise analysis of crime patterns than was previously possible. These developments have also contributed to increased use of spatial analytics in policing, including in resource allocation, patrol planning, and place-based interventions targeting so-called vulnerable areas and/or crime hot spots.
A central component of the project is the evaluation of statistical and analytical methods used to identify and model spatial and temporal crime patterns. Rather than assuming that these methods are valid or effective, the project empirically assesses their ability to capture meaningful patterns in the data and their usefulness for prediction and decision support in policing.
Overall, the project contributes to a more robust understanding of the relationship between place, time, and crime in Oslo, and to a more critical and empirically grounded assessment of how spatial crime analysis can inform crime prevention strategies in a Norwegian context.
