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Unveiling the relationship between land use types and the temporal signals of crime: An empirical decomposition approach

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  • Chris Brunsdon

    (National University of Ireland, Ireland)

  • Jonathan Corcoran

Abstract

Whilst some land uses are highly criminogenic, others remain largely free of crime. This patterning is a reflection of the types and timing of daily activities that take place in a given land use and the opportunities that this presents for crime. While the criminology literature has developed a rigorous understanding of geographic component of crime, relatively less emphasis has been placed on the temporal dimension. Here, we address this through applying a technique to examine micro-temporal variations in crime at places. This technique adopts a factor approach to model hourly counts of crime across seven land use types (commercial, residential, parkland, agricultural, medical/hospital, industrial and education) to unveil the number and distribution of crime signals across a 24-hour period along with how these signals mix across each land use type. Results reveal clear and distinct differences between crime type and land use, highlighting the diurnal nature of crime patterns and speak to the literature on risky places and risky times. The utility of our approach lies in its capacity to delineate common temporal rhythms and how these rhythms are shared across different land use types.

Suggested Citation

  • Chris Brunsdon & Jonathan Corcoran, 2022. "Unveiling the relationship between land use types and the temporal signals of crime: An empirical decomposition approach," Environment and Planning B, , vol. 49(3), pages 847-865, March.
    • Handle: RePEc:sae:envirb:v:49:y:2022:i:3:p:847-865
    DOI: 10.1177/23998083211033304
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    References listed on IDEAS

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    1. J Corcoran & R Zahnow & A Kimpton & R Wickes & C Brunsdon, 2021. "The temporality of place: Constructing a temporal typology of crime in commercial precincts," Environment and Planning B, , vol. 48(1), pages 9-24, January.
    2. J. D. Nielsen & J. S. Rosenthal & Y. Sun & D. M. Day & I. Bevc & T. Duchesne, 2014. "Group-based Criminal Trajectory Analysis Using Cross-validation Criteria," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(20), pages 4337-4356, October.
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    4. Taylor, Ralph B. & Haberman, Cory P. & Groff, Elizabeth R., 2019. "Urban park crime: Neighborhood context and park features," Journal of Criminal Justice, Elsevier, vol. 64(C), pages 1-1.
    5. Malleson, Nick & Andresen, Martin A., 2016. "Exploring the impact of ambient population measures on London crime hotspots," Journal of Criminal Justice, Elsevier, vol. 46(C), pages 52-63.
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