My colleague, Tamara, and I contributed a chapter to the recently released Risk Terrain Modeling Compendium published by Joel Caplan and Les Kennedy of the Rutgers Center on Public Security. The compendium expands on the original Risk Terrain Modeling Manual with additional known crime risk factors, case studies, and thought pieces on the future direction for Risk Terrain Modeling (RTM).
You might ask: Jeremy, what is RTM all about?
The concept of RTM is to forecast risk based on the context within which crime incidents occur. One of the strengths of RTM is it’s relative simplicity, which results in easy to understand models.
Let’s say that we notice that shootings seem to frequently occur near public housing and in areas with a high density of drug incidents. While we can’t necessarily say that these risk factors cause the shootings, we can statistically test whether there is correlation present in the data. We convert these two risk factors into two GIS raster layers — a representation of each dataset as a landscape of risk values. We then combine the two risk layers to form one landscape — our RTM. The model can then be used to prioritize areas in which to address shootings in the coming weeks and months.
Thus far, RTM has been largely a manual process in desktop GIS tools. Our compendium chapter addresses how moving to a server-based approach to RTM could tranform its application. By dramatically reducing model computation time, a user can interact with RTM quite differently — testing more datasets, generating multiple models from which to choose, and even publishing interactive models on mobile devices such as tablets and smartphones.
You can download the Compendium PDF from: http://www.rutgerscps.org/rtm/
An excerpt from Chapter 29: “Transforming RTM with Server-based Geoprocessing”:
Recent advances in computing and spatial analysis technology—namely distributed processing and mobile technology—make it possible to implement an intelligence-led policing model, such as ACTION, more comprehensively.
Azavea’s ongoing research to optimize GIS data processing performance by distributing computation across multiple threads, processors and servers demonstrates the potential to make RTM available as a scalable, web-based application. This would provide a number of advantages to law enforcement agencies.
First, it would make the automated application of RTM simultaneously available to multiple users across a network.
Second, it would provide faster processing and response times even with large datasets or greater geographic extents, enabling crime analysts to more easily experiment with and fine-tune models.
Third, and perhaps most importantly, it would enable the display of interactive risk terrain maps on mobile devices and make them available to officers in the field, where they could be updated on-the-fly based on current conditions.
This chapter will outline several potential approaches to enabling processing to occur with sufficient speed that an RTM application could be deployed to a much broader audience within a police department.
