scholarly journals Using risk terrain modeling to predict homeless related crime in Los Angeles, California

2019 ◽  
Vol 109 ◽  
pp. 102039 ◽  
Author(s):  
Youngmin Yoo ◽  
Andrew P. Wheeler
2019 ◽  
Author(s):  
Youngmin Yoo ◽  
Andrew Palmer Wheeler

We apply Risk Terrain Modeling (RTM) to identify the factors that predict homeless related crime at micro grid cells in Los Angeles, CA. We find that place based factors predicting whether homeless individuals are victimized or the offender being homeless are largely consistent with one another. Out of 26 different crime attractors and generators, prior drug arrests, homeless shelters, and bus stops are the three biggest factors in predicting homeless related crime. We show how the RTM model can effectively forecast future homeless related crimes as well. This suggests that targeted spatial strategies can reduce both homeless offending and victimization risk. Given that the majority of homeless individuals are only intermittently homeless, place based strategies may be a more an effective way to limit risk than strategies that focus on individuals. Original data and RTM output can be obtained at https://www.dropbox.com/s/a9kj0dkl8mcy90e/LA_Homeless_RTM.zip?dl=0.


2021 ◽  
pp. 073401682199679
Author(s):  
Branson Fox ◽  
Anne Trolard ◽  
Mason Simmons ◽  
Jessica E. Meyers ◽  
Matt Vogel

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.


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

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

2017 ◽  
Vol 35 (19-20) ◽  
pp. 4013-4039 ◽  
Author(s):  
Marco Dugato ◽  
Francesco Calderoni ◽  
Giulia Berlusconi

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.


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

2020 ◽  
pp. 073401682093885
Author(s):  
Hannah Steinman ◽  
Grant Drawve ◽  
Jyotishka Datta ◽  
Casey T. Harris ◽  
Shaun A. Thomas

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.


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