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Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp

Maite Dewinter (UGent) , Philipp M. Dau (UGent) , Christophe Vandeviver (UGent) , Tom Vander Beken (UGent) and Frank Witlox (UGent)
(2021)
Author
Organization
Abstract
Police patrol distinguishes itself from other routing problems due to the interaction between reactive and proactive patrol. Therefore, it is important to understand the spatiotemporal patterns of police patrol and criminal activity to logistically optimize resource allocation. Moreover, crime deterrent effects of preventative or proactive motor patrol have to be quantified and, to increase its effectiveness, it is of great value to determine the optimal dosage on the street segment level. Police presence and its deterrent effect on crime in time and space influences the optimal spatial deployment of patrol cars. In this research on police patrol, we analyse crime incidents, 911 calls, and GPS data of the Antwerp Local Police Department (ALPD) in Belgium. In 2018, the ALPD registered more than 43,000 crimes and tracked the routes of more than one hundred police vehicles. Successive data cleaning, map matching, and geocoding of the data make it possible to visualize spatiotemporal patterns of crimes, 911 calls, and police patrol. Combining these patterns is a first important step in developing an algorithm for police patrol as well as determining the relationship between police presence and crime prevention.
Keywords
Supply & Demand, Police Provision, GPS, Big Data

Citation

Please use this url to cite or link to this publication:

MLA
Dewinter, Maite, et al. Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp. 2021.
APA
Dewinter, M., Dau, P. M., Vandeviver, C., Vander Beken, T., & Witlox, F. (2021). Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp. Presented at the RGS-IBG Annual International Conference, London.
Chicago author-date
Dewinter, Maite, Philipp M. Dau, Christophe Vandeviver, Tom Vander Beken, and Frank Witlox. 2021. “Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp.” In .
Chicago author-date (all authors)
Dewinter, Maite, Philipp M. Dau, Christophe Vandeviver, Tom Vander Beken, and Frank Witlox. 2021. “Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp.” In .
Vancouver
1.
Dewinter M, Dau PM, Vandeviver C, Vander Beken T, Witlox F. Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp. In 2021.
IEEE
[1]
M. Dewinter, P. M. Dau, C. Vandeviver, T. Vander Beken, and F. Witlox, “Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp,” presented at the RGS-IBG Annual International Conference, London, 2021.
@inproceedings{8722081,
  abstract     = {{Police patrol distinguishes itself from other routing problems due to the interaction between reactive and proactive patrol. Therefore, it is important to understand the spatiotemporal patterns of police patrol and criminal activity to logistically optimize resource allocation. Moreover, crime deterrent effects of preventative or proactive motor patrol have to be quantified and, to increase its effectiveness, it is of great value to determine the optimal dosage on the street segment level. Police presence and its deterrent effect on crime in time and space influences the optimal spatial deployment of patrol cars. In this research on police patrol, we analyse crime incidents, 911 calls, and GPS data of the Antwerp Local Police Department (ALPD) in Belgium. In 2018, the ALPD registered more than 43,000 crimes and tracked the routes of more than one hundred police vehicles. Successive data cleaning, map matching, and geocoding of the data make it possible to visualize spatiotemporal patterns of crimes, 911 calls, and police patrol. Combining these patterns is a first important step in developing an algorithm for police patrol as well as determining the relationship between police  presence and crime prevention.}},
  author       = {{Dewinter, Maite and Dau, Philipp M. and Vandeviver, Christophe and Vander Beken, Tom and Witlox, Frank}},
  keywords     = {{Supply & Demand,Police Provision,GPS,Big Data}},
  language     = {{eng}},
  location     = {{London}},
  title        = {{Unravelling Spatiotemporal Patterns of Everyday Police Patrol in Antwerp}},
  year         = {{2021}},
}