Predictive crime mapping

J. Fitterer, Trisalyn Nelson, F. Nathoo

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Geographic Information Systems (GIS) have emerged as a key tool in intelligence-led policing and spatial predictions of crime are being used by many police services to reduce crime. Break and entries (BNEs) are one of the most patterned and predictable crime types, and may be particularly amendable to predictive crime mapping. A pilot project was conducted to spatially predict BNEs and property crime in Vancouver, Canada. Using detailed data collected by the Vancouver Police Department on where and when observed crimes occur, the statistical model was able to predict future BNEs for residential and commercial locations. Ideally implemented within a mobile GIS, the automated model provides continually updated predictive maps and may assist patrol units in self-deployment decisions. Future research is required to overcome computational and statistical limitations, and to preform model validation.

Original languageEnglish (US)
Pages (from-to)121-135
Number of pages15
JournalPolice Practice and Research
Volume16
Issue number2
DOIs
StatePublished - Mar 4 2015
Externally publishedYes

Fingerprint

offense
information system
police
pilot project
intelligence
Canada

Keywords

  • break and entries (BNEs)
  • Geographic Information Systems (GIS)
  • intelligence led policing
  • predictive mapping
  • statistical modeling
  • Vancouver

ASJC Scopus subject areas

  • Law
  • Social Sciences (miscellaneous)

Cite this

Predictive crime mapping. / Fitterer, J.; Nelson, Trisalyn; Nathoo, F.

In: Police Practice and Research, Vol. 16, No. 2, 04.03.2015, p. 121-135.

Research output: Contribution to journalArticle

Fitterer, J. ; Nelson, Trisalyn ; Nathoo, F. / Predictive crime mapping. In: Police Practice and Research. 2015 ; Vol. 16, No. 2. pp. 121-135.
@article{ed818e6d668543f9a058866efaab2d3e,
title = "Predictive crime mapping",
abstract = "Geographic Information Systems (GIS) have emerged as a key tool in intelligence-led policing and spatial predictions of crime are being used by many police services to reduce crime. Break and entries (BNEs) are one of the most patterned and predictable crime types, and may be particularly amendable to predictive crime mapping. A pilot project was conducted to spatially predict BNEs and property crime in Vancouver, Canada. Using detailed data collected by the Vancouver Police Department on where and when observed crimes occur, the statistical model was able to predict future BNEs for residential and commercial locations. Ideally implemented within a mobile GIS, the automated model provides continually updated predictive maps and may assist patrol units in self-deployment decisions. Future research is required to overcome computational and statistical limitations, and to preform model validation.",
keywords = "break and entries (BNEs), Geographic Information Systems (GIS), intelligence led policing, predictive mapping, statistical modeling, Vancouver",
author = "J. Fitterer and Trisalyn Nelson and F. Nathoo",
year = "2015",
month = "3",
day = "4",
doi = "10.1080/15614263.2014.972618",
language = "English (US)",
volume = "16",
pages = "121--135",
journal = "Police Practice and Research",
issn = "1561-4263",
publisher = "Routledge",
number = "2",

}

TY - JOUR

T1 - Predictive crime mapping

AU - Fitterer, J.

AU - Nelson, Trisalyn

AU - Nathoo, F.

PY - 2015/3/4

Y1 - 2015/3/4

N2 - Geographic Information Systems (GIS) have emerged as a key tool in intelligence-led policing and spatial predictions of crime are being used by many police services to reduce crime. Break and entries (BNEs) are one of the most patterned and predictable crime types, and may be particularly amendable to predictive crime mapping. A pilot project was conducted to spatially predict BNEs and property crime in Vancouver, Canada. Using detailed data collected by the Vancouver Police Department on where and when observed crimes occur, the statistical model was able to predict future BNEs for residential and commercial locations. Ideally implemented within a mobile GIS, the automated model provides continually updated predictive maps and may assist patrol units in self-deployment decisions. Future research is required to overcome computational and statistical limitations, and to preform model validation.

AB - Geographic Information Systems (GIS) have emerged as a key tool in intelligence-led policing and spatial predictions of crime are being used by many police services to reduce crime. Break and entries (BNEs) are one of the most patterned and predictable crime types, and may be particularly amendable to predictive crime mapping. A pilot project was conducted to spatially predict BNEs and property crime in Vancouver, Canada. Using detailed data collected by the Vancouver Police Department on where and when observed crimes occur, the statistical model was able to predict future BNEs for residential and commercial locations. Ideally implemented within a mobile GIS, the automated model provides continually updated predictive maps and may assist patrol units in self-deployment decisions. Future research is required to overcome computational and statistical limitations, and to preform model validation.

KW - break and entries (BNEs)

KW - Geographic Information Systems (GIS)

KW - intelligence led policing

KW - predictive mapping

KW - statistical modeling

KW - Vancouver

UR - http://www.scopus.com/inward/record.url?scp=84921024901&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84921024901&partnerID=8YFLogxK

U2 - 10.1080/15614263.2014.972618

DO - 10.1080/15614263.2014.972618

M3 - Article

AN - SCOPUS:84921024901

VL - 16

SP - 121

EP - 135

JO - Police Practice and Research

JF - Police Practice and Research

SN - 1561-4263

IS - 2

ER -