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Spatial and Temporal Patterns of Risk: A Risk Terrain Modeling Approach in Stockholm, Sweden

Puur, Mia LU ; Camacho Doyle, Maria LU orcid ; Guldåker, Nicklas LU orcid and Gerell, Manne (2025) In European Journal on Criminal Policy and Research
Abstract
Decades of criminological research have highlighted the principle that “place matters” when analysing crime dynamics. While acknowledging this, our study emphasises that place matters at specific times of the day and days of the week. This paper explores spatiotemporal patterns of assaults in public spaces in Stockholm, Sweden, using a time–space modeling approach. By segmenting annual crime registry data into time-specific models (e.g., weekday mornings and weekend nights), sixteen models were created covering two years. Using Risk Terrain Modeling, spatio-temporal cells were analysed with Spearman’s Rank Correlations and Predictive Accuracy and Efficiency measures to explore and compare time-specific models to a more generalised annual... (More)
Decades of criminological research have highlighted the principle that “place matters” when analysing crime dynamics. While acknowledging this, our study emphasises that place matters at specific times of the day and days of the week. This paper explores spatiotemporal patterns of assaults in public spaces in Stockholm, Sweden, using a time–space modeling approach. By segmenting annual crime registry data into time-specific models (e.g., weekday mornings and weekend nights), sixteen models were created covering two years. Using Risk Terrain Modeling, spatio-temporal cells were analysed with Spearman’s Rank Correlations and Predictive Accuracy and Efficiency measures to explore and compare time-specific models to a more generalised annual model. Results suggest that timespecific models perform better in smaller geographical areas compared to a yearly model. However, correlations and GIS mapping show that micro-grid crime hotspots fluctuate within larger hotspots and between years. These findings underscore the need for dynamic hotspot monitoring within crime analysis and for law enforcement to adapt resource allocation at both hotspots and within hot times. By shifting from static annual models to more nuanced temporal models, authorities can enhance crime prevention strategies and optimise interventions at high-risk locations during critical temporal windows. (Less)
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author
; ; and
organization
publishing date
type
Contribution to journal
publication status
epub
subject
in
European Journal on Criminal Policy and Research
pages
28 pages
publisher
Springer
external identifiers
  • scopus:105006933510
ISSN
0928-1371
DOI
10.1007/s10610-025-09625-0
language
English
LU publication?
yes
id
8efd4d06-7850-48b1-aab0-2b628ff7e9f2
date added to LUP
2025-06-16 09:02:41
date last changed
2025-06-17 04:01:19
@article{8efd4d06-7850-48b1-aab0-2b628ff7e9f2,
  abstract     = {{Decades of criminological research have highlighted the principle that “place matters” when analysing crime dynamics. While acknowledging this, our study emphasises that place matters at specific times of the day and days of the week. This paper explores spatiotemporal patterns of assaults in public spaces in Stockholm, Sweden, using a time–space modeling approach. By segmenting annual crime registry data into time-specific models (e.g., weekday mornings and weekend nights), sixteen models were created covering two years. Using Risk Terrain Modeling, spatio-temporal cells were analysed with Spearman’s Rank Correlations and Predictive Accuracy and Efficiency measures to explore and compare time-specific models to a more generalised annual model. Results suggest that timespecific models perform better in smaller geographical areas compared to a yearly model. However, correlations and GIS mapping show that micro-grid crime hotspots fluctuate within larger hotspots and between years. These findings underscore the need for dynamic hotspot monitoring within crime analysis and for law enforcement to adapt resource allocation at both hotspots and within hot times. By shifting from static annual models to more nuanced temporal models, authorities can enhance crime prevention strategies and optimise interventions at high-risk locations during critical temporal windows.}},
  author       = {{Puur, Mia and Camacho Doyle, Maria and Guldåker, Nicklas and Gerell, Manne}},
  issn         = {{0928-1371}},
  language     = {{eng}},
  month        = {{05}},
  publisher    = {{Springer}},
  series       = {{European Journal on Criminal Policy and Research}},
  title        = {{Spatial and Temporal Patterns of Risk: A Risk Terrain Modeling Approach in Stockholm, Sweden}},
  url          = {{http://dx.doi.org/10.1007/s10610-025-09625-0}},
  doi          = {{10.1007/s10610-025-09625-0}},
  year         = {{2025}},
}