Using GIS to Problem Solve across Public Safety Agencies

By Julie Wartell

How many people do you know that have had a collision with a fire truck? Not a common occurrence, but it does happen. As a matter of fact, I crashed into one a few years ago (and I‘ve heard all the jokes about not seeing it!). The crash itself, while not a big deal (beyond the embarrassment and having a hole in my bumper from the hook on the back of the truck), was illuminating on a number of fronts. At this point, you’re asking, “what does this have to do with crime mapping?” Hang with me. The crash occurred with a San Diego Fire Department truck in the City of San Diego, but because there was a lot of traffic, the firefighter suggested we drive up to the next street and pull off into a lot to do the report. He contacted his supervisor who would meet us there. Because the call of a collision went out on the air, the next thing we knew, the City of Del Mar (where we were parked) Fire Department arrived – lights and sirens! Del Mar Fire also contacted the Sheriff’s Department (who has jurisdiction in Del Mar) to report the collision. When the deputy arrived, he asked us to describe the collision, and we pointed to the place where it happened. He put down his pen and said that’s not my jurisdiction; you have to call San Diego Police. Anyone see how GIS could have helped?

Beyond this experience (which was a ridiculous waste of time and taxpayer money), several things had occurred that led me to believe that Police and Fire should be working together on public safety problems. Having spent my career analyzing crime and disorder problems and working as an advisor on a regional project for using GIS to share police and fire data, my interest was piqued. Added to this was my invitation to speak about problem solving at the Colorado Fire and Life Safety Educators Conference of the Rockies in 2009. Why would a crime analyst speak at a fire conference? An attendee at the 2008 Problem Oriented Policing Conference realized that if Police could do Problem Solving/SARA model, why couldn’t Fire?   As a matter of fact, police had “borrowed” the crime triangle concept from fire.[1]

So I attempted to learn more about what fire departments do (besides drive around in shiny red trucks and run on the beach when they are not driving around in shiny red trucks). Just kidding! I educated myself by speaking with a cop friend who works on the San Diego Metro Arson Strike Team (and ended up doing a map for him on arson registrants), asking a firefighter friend to talk to his ‘mapping guy’ about things they could do, and then using my own brain and experience.

I came up with the following problems that both police and fire handle: 1) traffic collisions; 2) arson/explosives; 3) homeless encampments; 4) Serial inebriates; and 5) insurance fraud. “We” in policing deal with these all the time (to some extent anyway), right? Well, so does the fire department! So how can we use GIS to analyze these problems? As with any problem, it starts with the data. In order to respond effectively (to reduce or prevent the problem), we need to fully understand it. Most police agencies (and researchers) analyze crime and disorder problems using solely police data such as crimes, arrests and calls for service. We need to go beyond these data sources, and GIS is an ideal tool.

Whether you’re in a large or small jurisdiction, urban, suburban or rural, traffic collisions occur. Many agencies map and analyze their collisions, whether it’s for increased enforcement, resource allocation or problem solving, but most are not integrating fire department data into the analysis which would add to the understanding. While not using GIS, the California Highway Patrol was on the right track when they were analyzing collisions along State Routes 41 and 46; their task force and analysis included not only fire but also traffic engineers and other relevant stakeholders.[2]

Neither arson nor insurance fraud is a common police problem but do take police resources, as well as those of fire and often medical and private sector. In 2009, the Coalition Against Insurance Fraud was seeing an increase in different types of fraud such as auto giveups and arson. Howard Goldblatt, Director of Government Affairs at the Coalition, noted “Fraud bureaus are telling us this, we’re hearing it from the state fire marshals, and we’re hearing about it anecdotally through news stories. It’s clear that as the economy has gone down, the opportunity to commit fraud, to recover monies they think they need, has increased.” Throughout the U.S., there are regional law enforcement task forces that focus on vehicle theft and insurance fraud; how many of them are analyzing their problem in conjunction with their local fire agencies? And how many people are using GIS to analyze arson and insurance fraud at all?

When speaking with my firefighter friend a few years ago, he and his co-workers were complaining about the homeless encampment fires that they were constantly responding to. I knew that police are also responding to these same encampments. Why not merge the data? Actually, the police and fire in that city had a common CAD, which made it a lot easier, but unfortunately no interest in working on the problem together. Recently, the police chief from a small city in northern California asked me to work with them to improve the crime analysis capacity. As part of that effort, I met with the fire chief and his ‘data guy’. We started comparing notes on homeless calls for police and fire and discussed how a joint analysis could help people 1) understand the problem better and 2) be used to garner resources (if police are spending 200 hours and fire is spending 50 hours annually, the real amount is 250 hours of public safety resources).

Last fall, the San Diego District Attorney asked me to speak to an organization that “has homeless data and wants to map it.” The homeless data they had was enormous – spreadsheets upon spreadsheets of survey data and piles of paper maps with x, o, and v markings. Not only did I get excited about the potential of digitizing the paper maps (ok, not me but perhaps a student?), but really started learning more about homeless issues – and that police captured only a very small percentage of the data that could be used for analysis. I learned from my colleague at the Chula Vista Police Department that she had recently analyzed homeless-related calls and found that it was their third most frequent call for service.

While the examples above relate to practitioners analyzing public safety issues, several researchers did a revealing study on this topic in Canada examining the temporal and spatial distribution of residential structure fire and residential burglary.[3] By applying environmental criminology theories to the study of fire events, they found that the spatial clustering overlapped but the temporal patterns were different. The results of this analysis could contribute greatly to prevention strategies for police and fire as well as help promote the idea of analyzing disparate data together to understand public safety issues.

So in the ideal world, how could GIS be used in a problem solving effort to reduce homeless encampments? Whether it’s the police or fire or the community who identify the problem, the analysis is key to creating effective responses.[4] We may start with mapping calls for service and supplement the data with observation or survey data (e.g. how many people and demographics in the encampment, temporary or more permanent living arrangements, etc.). We would look at topography and land use to identify patterns (e.g. are they predominantly in residential, commercial or open space; in canyons or near water bodies). We would then add in facilities (e.g. shelters, public bathrooms/showers and food banks) and examine distances. Depending on your jurisdiction and your homeless “problem,” there may be other types of data and spatial analysis that can be done as well as using the maps to communicate the problem to the other stakeholders and community.

This type of analysis can be done for traffic collisions, arson, serial inebriates, meth labs and other public safety issues to which the police and fire respond. Instead of simply making “hot spot” maps of police crimes and doing more enforcement in those areas, people working on these problems (whether it’s the crime analyst, crime prevention specialist, city GIS analyst, or researcher) should use GIS to integrate police and fire events with the variety of relevant data to conduct the analysis. This may include demographics, code enforcement, road conditions and other risk factors. I guarantee you will discover spatial relationships and patterns

Where do you go from here? Do you currently work on a regular basis with other public safety agencies in your jurisdiction? What data is available for geospatial analysis? What data might we want to collect on a regular basis? What problems are common across agencies in your jurisdiction? Create a means to share and analyze data in a systematic way to focus on these problems. Share your successes (and challenges) with others.

  1. More information about the crime/problem analysis triangle can be found at
  2. A write-up of the project is at
  3. Wuschke, K., J. Clare and L. Garis. “Temporal and geographic clustering of residential structure fires: A theoretical platform for targeted fire prevention,” Fire Safety Journal, Elsevier (2013).
  4. See the Homeless Encampments POP Guide for additional guidance.
Julie Wartell

Julie Wartell is the Founder of The Analysis Group and is a Science Advisor for the Police Foundation. She is an independent advisor on public safety issues relating to crime analysis, problem solving and justice systems, and is an adjunct lecturer at the University of California, San Diego. She has performed a wide range of research on and analysis of crime problems and police-related issues, has worked on strategic planning efforts, and has developed crime analysis and GIS training. Wartell has a Master’s Degree in Public Administration and a postgraduate diploma in applied criminology and police management. She can be reached at

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