Objectives We illustrate how a machine learning algorithm, Random Forests, can provide
accurate long-term predictions of crime at micro places relative to other popular techniques …

Background Several studies have tested the reliability of Risk Terrain Modelling (RTM) by
focusing on different geographical contexts and types of crime or events. However, to date …

Gun violence is a serious issue in many countries across the globe. It has been shown that
there is an elevated risk for a further shooting nearby within a short time span of a shooting …

The spatiotemporal distribution of crime is closely related to the environment, exhibiting a
typical characteristic of “spatiotemporal autocorrelation”. However, most of the existing …

The Kansas City, Missouri Police Department sought to reduce violent crime with an
evidence-based approach to problem analysis and intervention planning. Informed by hot …

Decades of empirical work have confirmed that experiences with violence are associated
with a variety of adverse behavioral and mental health as well as academic outcomes for …

Abstract 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 …

Purpose The purpose of this study is to identify potential changes in crime generators and
attractors based on monthly models in a high-tourist destination. Design/methodology …

In this paper, we explore the conditions under which clearance rates improve by looking at
the experience across New York City. Using one agency provides a control on the …

Objectives: Assessing the predictive accuracy of using prior crime, place attributes, ambient
population, community structural, and social characteristics, in isolation and combined when …