Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Using Vulnerability and Exposure to Improve Robbery Prediction and Target Area Selection

Using Vulnerability and Exposure to Improve Robbery Prediction and Target Area Selection A large body of research has found that crime is much more likely to occur at certain places relative to others. Attempting to capitalize on this finding to maximize crime prevention, many police administrators have sought to narrow their department’s operational focus and allocate resources and attention to the most problematic locations. However, in the face of a growing number of technological advances in crime forecasting that have facilitated this trend, it is still unclear how to best identify the most appropriate set of places to which resources and attention should be directed. Our goal was to examine this issue by exploring the ways in which spatial vulnerabilities and exposures could be used to identify the best target areas for policing. Using the Theory of Risky Places as a guide, we employed kernel density estimation (KDE) to measure crime exposures and risk terrain modeling (RTM) to identify crime vulnerabilities with the expectation that crime would be predicted more accurately by integrating the outputs from these two methods. To test this hypothesis, our analysis utilized 1 year of data on street robbery in Brooklyn, New York. A common metric, the prediction accuracy index (PAI), was computed for KDE, RTM, and the integrated approach, over 1 month and 3 month intervals. We found that the integrated approach, on average and most frequently, produces the most accurate predictions. These results demonstrate that place-based policing and related policies can be improved via actionable intelligence produced from multiple crime analysis tools that are designed to measure unique aspects of the spatial dynamics of crime. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Spatial Analysis and Policy Springer Journals

Using Vulnerability and Exposure to Improve Robbery Prediction and Target Area Selection

Download PDF
24 pages

Loading next page...
 
/lp/springer-journals/using-vulnerability-and-exposure-to-improve-robbery-prediction-and-nmIaRJZcXe
Publisher
Springer Journals
Copyright
Copyright © Springer Nature B.V. 2019
Subject
Social Sciences; Human Geography; Landscape/Regional and Urban Planning; Regional/Spatial Science
ISSN
1874-463X
eISSN
1874-4621
DOI
10.1007/s12061-019-09294-7
Publisher site
See Article on Publisher Site

Abstract

A large body of research has found that crime is much more likely to occur at certain places relative to others. Attempting to capitalize on this finding to maximize crime prevention, many police administrators have sought to narrow their department’s operational focus and allocate resources and attention to the most problematic locations. However, in the face of a growing number of technological advances in crime forecasting that have facilitated this trend, it is still unclear how to best identify the most appropriate set of places to which resources and attention should be directed. Our goal was to examine this issue by exploring the ways in which spatial vulnerabilities and exposures could be used to identify the best target areas for policing. Using the Theory of Risky Places as a guide, we employed kernel density estimation (KDE) to measure crime exposures and risk terrain modeling (RTM) to identify crime vulnerabilities with the expectation that crime would be predicted more accurately by integrating the outputs from these two methods. To test this hypothesis, our analysis utilized 1 year of data on street robbery in Brooklyn, New York. A common metric, the prediction accuracy index (PAI), was computed for KDE, RTM, and the integrated approach, over 1 month and 3 month intervals. We found that the integrated approach, on average and most frequently, produces the most accurate predictions. These results demonstrate that place-based policing and related policies can be improved via actionable intelligence produced from multiple crime analysis tools that are designed to measure unique aspects of the spatial dynamics of crime.

Journal

Applied Spatial Analysis and Policy – Springer Journals

Published: Mar 15, 2020

References

  • Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions: a crime case study
    Adepeju, M; Rosser, G; Cheng, T
  • The trajectories of crime at places: understanding the patterns of disaggregated crime types
    Andresen, MA; Curman, AS; Linning, SJ
  • Predictable policing: measuring the crime control benefits of hotspots policing at bus stops
    Ariel, B; Partridge, H
  • Where offenders choose to attack: a discrete choice model of robberies in Chicago
    Bernasco, W; Block, R
  • Robberies in Chicago: a block-level analysis of the influence of crime generators, crime attractors, and offender anchor points
    Bernasco, W; Block, R
  • CrimeStat III: A spatial statistics program for the analysis of crime incident locations
    Block, R; Block, CR
  • Explaining high-risk concentrations of crime in the city: social disorganization, crime opportunities, and important next steps
    Braga, AA; Clarke, RV
  • Policing problem places: Crime hot spots and effective prevention
    Braga, AA; Weisburd, D
  • The concentration and stability of gun violence at micro places in Boston, 1980–2008
    Braga, AA; Papachristos, AV; Hureau, DM
  • The relevance of micro places to citywide robbery trends: a longitudinal analysis of robbery incidents at street corners and block faces in Boston
    Braga, AA; Hureau, DM; Papachristos, AV
  • The effects of hot spots policing on crime: an updated systematic review and meta-analysis
    Braga, AA; Papachristos, AV; Hureau, DM
  • Criminality of place
    Brantingham, P; Brantingham, P
  • Environmental criminology and crime analysis
    Brantingham, P; Brantingham, P
  • Mapping the spatial influence of crime correlates: a comparison of operationalization schemes and implications for crime analysis and criminal justice practice
    Caplan, JM
  • Risk terrain modeling diagnostics utility (version 1.0)
    Caplan, JM; Kennedy, LW
  • Risk terrain modeling: Crime prediction and risk reduction
    Caplan, JM; Kennedy, LW
  • Risk terrain modeling: brokering criminological theory and GIS methods for crime forecasting
    Caplan, JM; Kennedy, LW; Miller, J
  • Joint utility of event-dependent and environmental crime analysis techniques for violent crime forecasting
    Caplan, JM; Kennedy, LW; Piza, EL
  • Risk terrain modeling diagnostics utility user manual (version 1.0)
    Caplan, JM; Kennedy, LW; Piza, EL
  • Risk terrain modeling for spatial risk assessment
    Caplan, JM; Kennedy, LW; Barnum, JD; Piza, EL
  • The utility of hotspot mapping for predicting spatial patterns of crime
    Chainey, S; Tompson, L; Uhlig, S
  • Situational crime prevention: theory and practice
    Clarke, RV
  • A metric comparison of predictive hot spot techniques and RTM
    Drawve, G
  • Predictability of gun crimes: a comparison of hot spot and risk terrain modelling techniques
    Drawve, G; Moak, SC; Berthelot, ER
  • Enhancing data-driven law enforcement efforts: exploring how risk terrain modeling and conjunctive analysis fit in a crime and traffic safety framework
    Drawve, G; Grubb, J; Steinman, H; Belongie, M
  • Assessing the validity of risk terrain modeling in a European city: preventing robberies in the City of Milan
    Dugato, M
  • Mapping crime: Understanding hot spots
    Eck, JE; Chainey, S; Cameron, JG; Leitner, M; Wilson, RE
  • Crime in the United States
  • Problem-oriented policing
    Goldstein, H
  • Criminogenic facilities and crime across street segments in Philadelphia: uncovering evidence about the spatial extent of facility influence
    Groff, ER; Lockwood, B
  • Essai sur la statistique morale de la France [Essay on the moral statistics of France]
    Guerry, AM
  • The variable impacts of public housing community proximity on nearby street robberies
    Haberman, CP; Groff, ER; Taylor, RB
  • Street robbery and public bus stops: a case study of activity nodes and situational risk
    Hart, TC; Miethe, TD
  • Effects of data quality on predictive hotspot mapping
    Hart, TC; Zandbergen, PA
  • Kernel density estimation and hotspot mapping: Examining the influence of interpolation method, grid cell size, and bandwidth on crime forecasting
    Hart, TC; Zandbergen, PA
  • Crime modeling and mapping using geospatial technologies
    Johnson, L; Ratcliffe, JH
  • The risk in crime
    Kennedy, LW; Brunschot, EG
  • Risk clusters, hotspots, and spatial intelligence: risk terrain modeling as an algorithm for police resource allocation strategies
    Kennedy, LW; Caplan, JM; Piza, EL
  • A primer on the spatial dynamics of crime emergence and persistence
    Kennedy, LW; Caplan, JM; Piza, EL
  • A multi-jurisdictional test of risk terrain modeling and place-based evaluation of environmental risk-based patrol deployment strategies
    Kennedy, LW; Caplan, JM; Piza, EL
  • Vulnerability and exposure to crime: applying risk terrain modeling to the study of assault in Chicago
    Kennedy, LW; Caplan, JM; Piza, EL; Buccine-Schraeder
  • Risk-based policing: evidence-based crime prevention with big data and spatial analytics
    Kennedy, LW; Caplan, JM; Piza, EL
  • Just enough police presence: reducing crime and disorderly behavior by optimizing patrol time in crime hot spots
    Koper, CS
  • A randomized test of initial and residual deterrence from directed patrols and use of license plate readers at crime hot spots
    Koper, CS; Taylor, BG; Woods, DJ
  • Preventing mass transit crime
    LaVigne, NG
  • The “hottest” part of a hotspot: comments on “the utility of hotspot mapping for predicting spatial patterns of crime”
    Levine, N
  • The crime fighter. How you can make your community crime-free
    Maple, J; Mitchell, C
  • Reducing firearms violence through directed police patrol: Final report on the evaluation of the Indianapolis Police Department’s directed patrol project
    McGarrell, EF; Chermak, S; Weiss, A
  • “A plague on both your houses?”: risks, repeats and reconsiderations of urban residential burglary
    Moreto, WD; Piza, EL; Caplan, JM
  • Applying crime prediction techniques to Japan: a comparison between risk terrain modeling and other methods
    Ohyama, T; Amemiya, M
  • Saturation foot-patrol in a high-violence area: a quasi-experimental evaluation
    Piza, EL; O’Hara, BA
  • The Newark foot patrol experiment
  • A treatise on man
    Quetelet, MA
  • The Philadelphia foot patrol experiment: a randomized controlled trial of police patrol effectiveness in violent crime hotspots
    Ratcliffe, JH; Taniguchi, T; Groff, ER; Wood, JD
  • Policing for prevention: Reducing crime, public intoxication and injury
    Rengert, GF
  • High schools and crime: A replication
    Roncek, DW; Faggiani, D
  • Bars, blocks, and crimes revisited: linking the theory of routine activities to the empiricism of “hot spots”
    Roncek, DW; Maier, PA
  • Housing projects and crime: testing a proximity hypothesis
    Roncek, DW; Bell, R; Francik, JM
  • The effects of directed patrol and self-initiated enforcement on firearm violence: a randomized controlled study of hot spot policing
    Rosenfeld, R; Deckard, MJ; Blackburn, E
  • Crime analysis with crime mapping
    Santos, RB
  • Juvenile delinquency in urban areas
    Shaw, CR; McKay, HD
  • Crime and place
    Sherman, LW
  • General deterrent effects of police patrol in crime “hot spots”: a randomized, controlled trial
    Sherman, LW; Weisburd, D
  • Hot spots of predatory crime: routine activities and the criminology of place
    Sherman, LW; Gartin, PR; Buerger, ME
  • Furthering the integration of routine activity and social disorganization theories: small units of analysis and the study of street robbery as a diffusion process
    Smith, WR; Frazee, SG; Davison, EL
  • Police innovation: Contrasting perspectives
    Sousa, W; Kelling, G
  • Pockets of crime: Broken windows, collective efficacy, and the criminal point of view
    St. Jean, PKB
  • A randomized controlled trial of different policing strategies at hot spots of violent crime
    Taylor, B; Koper, CS; Woods, DJ
  • A microspatial analysis of robbery: Prospective hot spotting in a small city
    Patten, IT; McKeldin-Coner, J; Cox, D
  • Ideas in American policing
    Weisburd, D
  • The criminology of place: Street segments and our understanding of the crime problem
    Weisburd, DL; Groff, ER; Yang, SM
  • Environmental criminology and crime analysis
    Wortley, R; Mazerolle, L
  • Armed robbers in action: Stickups and street culture
    Wright, RT; Decker, SH
  • Evaluating the temporal parameters of risk terrain modeling with residential burglary
    Yerxa, M