Applying Crime Prediction Techniques to Japan: A Comparison Between Risk Terrain Modeling and Other Methods

2018 ◽  
Vol 24 (4) ◽  
pp. 469-487 ◽  
Author(s):  
Tomoya Ohyama ◽  
Mamoru Amemiya
Keyword(s):  
Terrain Modeling ◽  
Crime Prediction ◽  
Risk Terrain Modeling ◽  
Prediction Techniques

Assessing the Differential Impact of Vacancy on Criminal Violence in the City of St. Louis, MO

2021 ◽  
pp. 073401682199679
Author(s):  
Branson Fox ◽  
Anne Trolard ◽  
Mason Simmons ◽  
Jessica E. Meyers ◽  
Matt Vogel
Keyword(s):  
Violent Crime ◽  
Situational Crime Prevention ◽  
Empirical Literature ◽  
Terrain Modeling ◽  
Criminal Violence ◽  
Aggravated Assault ◽  
Environmental Correlates ◽  
Risk Terrain Modeling ◽  
The City ◽  
North And South

This study employs risk terrain modeling to identify the spatial correlates of aggravated assault and homicide in St. Louis, MO. We build upon the empirical literature by (1) replicating recent research examining the role of vacancy in the concentration of criminal violence and (2) examining whether the environmental correlates of violence vary between north and south St. Louis, a boundary that has long divided the city along racial and socioeconomic lines. Our results indicate that vacancy presents a strong, consistent risk for both homicide and aggravated assault and that this pattern emerges most clearly in the northern part of the city which is majority African American and has suffered chronic disinvestment. The concentration of criminal violence in South City is driven primarily by public hubs including housing, transportation, and schools. Our results underscore the importance of vacancy as a driver of the spatial concentration of violent crime and point to potential heterogeneity in risk terrain modeling results when applied to large metropolitan areas. Situational crime prevention strategies would be well served to consider such spatial contingencies as the risk factors driving violent crime are neither uniformly distributed across space nor uniform in their impact on criminal violence.

scholarly journals Vulnerability and Exposure to Crime: Applying Risk Terrain Modeling to the Study of Assault in Chicago

2015 ◽  
Vol 9 (4) ◽  
pp. 529-548 ◽  
Author(s):  
Leslie W. Kennedy ◽  
Joel M. Caplan ◽  
Eric L. Piza ◽  
Henri Buccine-Schraeder
Keyword(s):  
Terrain Modeling ◽  
Risk Terrain Modeling

Crime in an Affluent City: Applications of Risk Terrain Modeling for Residential and Vehicle Burglary in Coral Gables, Florida, 2004–2016

2019 ◽  
Vol 13 (2) ◽  
pp. 441-459 ◽  
Author(s):  
Derek Vildosola ◽  
Julian Carter ◽  
Eric R. Louderback ◽  
Shouraseni Sen Roy
Keyword(s):  
Terrain Modeling ◽  
Risk Terrain Modeling

scholarly journals Forecasting Organized Crime Homicides: Risk Terrain Modeling of Camorra Violence in Naples, Italy

2017 ◽  
Vol 35 (19-20) ◽  
pp. 4013-4039 ◽  
Author(s):  
Marco Dugato ◽  
Francesco Calderoni ◽  
Giulia Berlusconi
Keyword(s):  
Risk Factors ◽  
Organized Crime ◽  
Violent Behavior ◽  
Terrain Modeling ◽  
Policy Makers ◽  
Risk Terrain Modeling ◽  
Future Events ◽  
Short And Long Term ◽  
Organized Crime Groups

Mafia homicides are usually committed for retaliation, economic profit, or rivalry among groups. The variety of possible reasons suggests the inefficacy of a preventive approach. However, like most violent crimes, mafia homicides concentrate in space due to place-specific social and environmental features. Starting from the existing literature, this study applies the Risk Terrain Modeling approach to forecast the Camorra homicides in Naples, Italy. This approach is based on the identification and evaluation of the underlying risk factors able to affect the risk of a homicide. This information is then used to predict the most likely location of future events. The findings of this study demonstrate that past homicides, drug dealing, confiscated assets, and rivalries among groups make it possible to predict up to 85% of 2012 mafia homicides, identifying 11% of city areas at highest risk. By contrast, variables controlling for the socio-economic conditions of areas are not significantly related to the risk of homicide. Moreover, this study shows that, even in a restricted space, the same risk factors may combine in different ways, giving rise to areas of equal risk but requiring targeted remedies. These results provide an effective basis for short- and long-term targeted policing strategies against organized crime- and gang-related violence. A similar approach may also provide practitioners, policy makers, and local administrators in other countries with significant support in understanding and counteracting also other forms of violent behavior by gangs or organized crime groups.

scholarly journals Risk terrain modeling predicts child maltreatment

2016 ◽  
Vol 62 ◽  
pp. 29-38 ◽  
Author(s):  
Dyann Daley ◽  
Michael Bachmann ◽  
Brittany A. Bachmann ◽  
Christian Pedigo ◽  
Minh-Thuy Bui ◽  
...  
Keyword(s):  
Child Maltreatment ◽  
Terrain Modeling ◽  
Risk Terrain Modeling

Risky Business: Examining the 80-20 Rule in Relation to a RTM Framework

2020 ◽  
pp. 073401682093885
Author(s):  
Hannah Steinman ◽  
Grant Drawve ◽  
Jyotishka Datta ◽  
Casey T. Harris ◽  
Shaun A. Thomas
Keyword(s):  
Predictive Power ◽  
Environmental Criminology ◽  
Department Stores ◽  
Terrain Modeling ◽  
Forecasting Models ◽  
Risk Terrain Modeling ◽  
Liquor Stores ◽  
Risky Facilities ◽  
Apartment Complexes ◽  
Risky Business

The spatial elements of crime occurrence and the identification of crime generators/attractors have remained a prominent area of research. We focus on the utility of the 80-20 rule and the labeling of risky facilities in crime forecasting models with risk terrain modeling (RTM). We first examine whether the rule holds across types of crime generating places including liquor stores, department stores, hotels/motels, restaurants/bars, and apartment complexes. Next, we use our findings to test whether conducting preliminary analyses to identify risky facilities increases the predictive power of RTM versus using all possible facilities. When restricting the RTM approach to only risky facilities, results were more accurate than a traditional RTM approach. Findings and implications are nested in the utilization of the wider body of environmental criminology research to increase our understanding of where crime is likely to occur.

scholarly journals Crime in Context: Utilizing Risk Terrain Modeling and Conjunctive Analysis of Case Configurations to Explore the Dynamics of Criminogenic Behavior Settings

2017 ◽  
Vol 33 (2) ◽  
pp. 133-151 ◽  
Author(s):  
Joel M. Caplan ◽  
Leslie W. Kennedy ◽  
Jeremy D. Barnum ◽  
Eric L. Piza
Keyword(s):  
Risk Factors ◽  
Environmental Risk ◽  
Geographic Area ◽  
Environmental Risk Factors ◽  
Analysis Tool ◽  
Terrain Modeling ◽  
Risk Terrain Modeling ◽  
Straightforward Method ◽  
Behavior Settings ◽  
Conjunctive Analysis

Risk terrain modeling (RTM) is a geospatial crime analysis tool designed to diagnose environmental risk factors for crime and identify the places where their spatial influence is collocated to produce vulnerability for illegal behavior. However, the collocation of certain risk factors’ spatial influences may result in more crimes than the collocation of a different set of risk factors’ spatial influences. Absent from existing RTM outputs and methods is a straightforward method to compare these relative interactions and their effects on crime. However, as a multivariate method for the analysis of discrete categorical data, conjunctive analysis of case configurations (CACC) can enable exploration of the interrelationships between risk factors’ spatial influences and their varying effects on crime occurrence. In this study, we incorporate RTM outputs into a CACC to explore the dynamics among certain risk factors’ spatial influences and how they create unique environmental contexts, or behavior settings, for crime at microlevel places. We find that most crime takes place within a few unique behavior settings that cover a small geographic area and, further, that some behavior settings were more influential on crime than others. Moreover, we identified particular environmental risk factors that aggravate the influence of other risk factors. We suggest that by focusing on these microlevel environmental crime contexts, police can more efficiently target their resources and further enhance place-based approaches to policing that fundamentally address environmental features that produce ideal opportunities for crime.

Risk Terrain Modeling (RTM)

2021 ◽  
pp. 873-874
Author(s):  
Henri Buccine‐Schraeder ◽  
Leslie W. Kennedy
Keyword(s):  
Terrain Modeling ◽  
Risk Terrain Modeling
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