Hot spots and burning times: A spatiotemporal analysis of calls for service to establish police demand

Dewinter, Maite; Vandeviver, Christophe; Dau, Philipp M.; Beken, Tom Vander; Witlox, Frank

doi:10.1016/j.apgeog.2022.102712

Cited by 5 publications

(2 citation statements)

References 56 publications

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“…Methods of determining the extent of spatial autocorrelation have either been used as a way of determining overall, citywide clustering (or dispersion) using a Global Moran's I statistic (e.g., Andresen, 2011b), or relatedly, as a means of identifying localized clustering of (dis)similar values using the Local Moran's I (e.g., Dewinter et al, 2022) or Getis-Ord Gi* (e.g., Bocker Parks, 2015) which can then be plotted visually on a map. The former provides a straightforward test to reject the null hypothesis of randomness: a precursor to more complex analysis which seeks to explain the observed patterns (e.g., Ellison et al, 2021).…”

Section: Descriptives Methodsmentioning

confidence: 99%

“…The former provides a straightforward test to reject the null hypothesis of randomness: a precursor to more complex analysis which seeks to explain the observed patterns (e.g., Ellison et al, 2021). The latter is presented as a substantive finding in its own right, sometimes framed as 'hotspot analysis' (Lersch & Christy, 2020) or outlier identification (Dewinter et al, 2022), to identify clusters of highdemand areas.…”

Section: Descriptives Methodsmentioning

confidence: 99%

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The spatial patterning of emergency demand for police services: a scoping review

Langton,

Ruiter,

Schoonmade

2024

Crime Sci

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This preregistered scoping review provides an account of studies which have examined the spatial patterning of emergency reactive police demand (ERPD) as measured by calls for service data. To date, the field has generated a wealth of information about the geographic concentration of calls for service, but the information remains unsynthesised and inaccessible to researchers and practitioners. We code our literature sample (N = 79) according to the types of demand studied, the spatial scales used, the theories adopted, the methods deployed and the findings reported. We find that most studies focus on crime-related call types using meso-level (e.g., neighborhood) spatial scales. Descriptive methods demonstrate the non-random distribution of calls, irrespective of their type, while correlational findings are mixed, providing minimal support for theories such as social disorganization theory. We conclude with suggestions for future research, focusing on how the field can better exploit open data sources to ‘scale-up’ analyses.

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Section: Descriptives Methodsmentioning

confidence: 99%

Section: Descriptives Methodsmentioning

confidence: 99%

The spatial patterning of emergency demand for police services: a scoping review

Langton,

Ruiter,

Schoonmade

2024

Crime Sci

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Reducing police response times: Optimization and simulation of everyday police patrol

Dewinter,

Jagtenberg,

Vandeviver

et al. 2024

Networks

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Police forces around the world are adapting to optimize their current practices through intelligence‐led and evidence‐based policing. This trend towards increasingly data‐driven policing also affects daily police routines. Police patrol is a complex routing problem because of the combination of reactive and proactive tasks. Moreover, a trade‐off exists between these two patrol tasks. In this article, a police patrol algorithm that combines both policing strategies into one strategy and is applicable to everyday policing, is developed. To this end, a discrete event simulation model is built that compares a p‐median redeployment strategy with several benchmark strategies, that is, p‐median deployment, hotspot (re)deployment, and random redeployment. This p‐median redeployment strategy considers the continuous alternation of idle and non‐idle vehicles. The mean response time was lowest for the p‐median deployment strategy, but the redeployment strategy results in better coverage of the area and low mean response times.

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Assessing spatial configuration of barrier-free facilities from the perspective of age-friendliness: A case Study of Beijing, China

Liu,

Lai,

Meng

et al. 2024

Applied Geography

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Hot spots and burning times: A spatiotemporal analysis of calls for service to establish police demand

Cited by 5 publications

References 56 publications

The spatial patterning of emergency demand for police services: a scoping review

The spatial patterning of emergency demand for police services: a scoping review

Reducing police response times: Optimization and simulation of everyday police patrol

Assessing spatial configuration of barrier-free facilities from the perspective of age-friendliness: A case Study of Beijing, China

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