Risk Terrain Modeling: How to Reduce Crime by Targeting Places

Estimated reading time: 7 minutes

The headlines are everywhere. Robberies are on the rise, and the community wants answers. At the next city council meeting, frustration fills the room. “What’s being done about it?” someone asks. The pressure is on.

It’s a familiar moment for many police leaders. The instinct is to respond with what has been done in the past: flood the hot spots with lots of stops, make arrests, and hope the numbers come down.

But what if there’s another way? What if the answer isn’t about chasing more offenders, but about changing the places where crime happens?

That’s the situation Atlantic City Police Department (NJ) faced when robberies suddenly surged in late 2016. Instead of reverting to old habits, they took a different path, one based on data, geography, and the simple but powerful idea that crime happens in places, not just because of people.

What Is Place-Based Crime Prevention?

Place-based crime prevention focuses on the environments that make certain locations more likely to experience crime. It’s grounded in environmental criminology and routine activities theory, which tell us that crime doesn’t occur randomly. It’s shaped by how spaces attract opportunities and interactions.

Some places naturally draw crime because of how they’re used. As attractors, they offer targets for predatory crimes like robbery or theft. Think of the quick cash and easy access that come with late-night convenience stores. As generators, they can serve as venues that support or concentrate illegal activity, attracting disorder and unruly behavior because of their long hours, limited supervision, and steady stream of people.

If we can make those spaces less attractive or less vulnerable, we can reduce crime without relying on more arrests or stops.

One tool that helps agencies understand and respond to risky places is Risk Terrain Modeling (RTM). RTM is a spatial diagnostic tool grounded in crime pattern theory and environmental criminology. It examines how features of the environment, such as convenience stores, gas stations, or vacant lots, interact to create conditions that make crime more likely. Using software such as RTMDx, RTM analyzes multiple risk factors at once to identify the locations most prone to criminal activity.

Think of it like a weather forecast for crime: RTM doesn’t just show where incidents have occurred. It highlights where the environment itself creates risk, giving police commanders actionable information to tailor responses in the places that need it most.

The Study: Atlantic City’s Robbery Problem

By early 2017, Atlantic City was facing a stubborn rise in robberies. The city’s permanent population is under 40,000, but it sees around 25 million visitors each year, creating a constantly shifting mix of residents, tourists, and transient offenders. This made traditional, person-focused deterrence especially challenging: the individuals committing crimes were always changing, so targeting specific offenders wasn’t a reliable solution.

Instead, ACPD partnered with researchers Leslie Kennedy, Joel Caplan, and Grant Drawve to use RTM to focus on the city’s most vulnerable locations, particularly convenience stores.

Why convenience stores? They are neighborhood hubs, offering essentials like milk, bread, snacks, and personal care items, along with quick cash access through ATMs or lottery ticket sales. But they’re also often open late, lightly staffed, and situated near roads, bus stops, and gas stations, creating environments that can attract robbery and other disorder.

In short, these stores aren’t just stops on a map. They’re locations where the situational conditions make crime more likely, making them key places to target for prevention.

How Atlantic City Used RTM to Target High-Risk Stores

ACPD decided to focus on reducing risk, not increasing arrests.

Using RTM, analysts identified 101 convenience stores in the city and determined which were surrounded by the highest robbery risk. Officers conducted regular property checks and brief “meet-and-greets” with store managers, logging each interaction. On average, there were over 1,100 business check-ins during the four-month initiative so about 279 per month, or roughly 3 per officer per shift. Each 8-hour shift also included directed patrols within one block of the selected stores.

Because resources were limited, the team didn’t blanket every store all at once. Instead, they re-evaluated which stores to prioritize each month using the previous two months’ crime data. Stores that overlapped with high-risk areas and current hot spots were given priority, ensuring officers were deployed with pinpoint accuracy where they could have the greatest impact.

This approach kept the strategy dynamic, data-driven, and sustainable, requiring no overtime or extra funding, just smarter deployment of existing resources.

Robberies Drop 63% in Four Months

Within four months, robberies around convenience stores dropped from 79 incidents in the pre-intervention period (October 1, 2016–January 31, 2017) to 29 incidents during the intervention (February 1–May 31, 2017)—a 63% reduction.

The benefits didn’t stop at the targeted stores. Robberies in surrounding blocks also fell, likely because officers patrolling high-risk stores were also present in nearby areas—a clear example of expanded, or spillover, benefits.

Researchers checked for displacement, comparing areas just outside the one-block target zones. Robberies in these displacement areas fell from 29 pre-intervention to 20 post-intervention, showing that crime wasn’t simply moving elsewhere.

And here’s the kicker: fewer arrests were made during the intervention compared to the same months the previous year (886 arrests vs. 1,024), showing that the reduction in crime didn’t rely on increased enforcement.

With a data-driven focus on the right places, this initiative achieved a substantial and sustainable drop in robberies without extra funding, overtime, or an increase in arrests.

Bringing It to Your Agency

Every agency faces that moment when crime spikes and pressure mounts. It’s tempting to lean on what’s familiar: saturation patrols, warrant sweeps, zero-tolerance enforcement. While these approaches can show short-term results, they can strain officer resources and sometimes overlook the underlying conditions that make crime likely.

This study offers a practical alternative:

• Use spatial analysis tools like RTM to identify high-risk environments. For a step-by-step guide on how RTM works, check out this HUD guide.
• Engage businesses in those locations (your local convenience stores, motels, or gas stations) and make them part of the solution.
• Invest in training. Free online RTM training, like the one offered by Rutgers Center on Public Security, can help your team understand the tools and analytics behind the method: RTM Online Training.
• Continuously monitor patterns and focus on the highest-risk places, using data to deploy officers with pinpoint accuracy where they can have the greatest impact. You can see an example of another agency putting RTM into action in the video below.

If you have a local university or research partner, collaborate. The Atlantic City project succeeded because police and researchers designed the approach together, combining operational insight with rigorous data analysis.

Final Thoughts

When robberies rise, it’s easy to feel trapped by the same old playbook. But as Atlantic City showed, innovation doesn’t always mean complexity. Sometimes it’s as simple as checking in with store managers, showing presence where it matters most, and letting the data point the way.

A simple, place-based strategy led to a 63% drop in robberies in just four months.

That’s the kind of result that should make any command staff pause and ask: what if we stopped trying to arrest our way out of every problem, and instead focused on the places where we can make the biggest difference?

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Carlee Ruiz

Carlee Ruiz is the founder of PoliceResearchHub, a platform that turns academic research into practical insights for law enforcement. She brings seven years of experience as a crime analyst and justice researcher, with a focus on evidence based policing, gun violence prevention, and public safety strategy. Carlee currently works as a researcher at National Policing Institute, where she supports evaluations of law enforcement programs and criminal justice initiatives across the country. Through PoliceResearchHub, she aims to make research easier to understand and more useful for the people doing the work on the ground.