In a study of 36 neighbourhood watch schemes, 56% showed a positive outcome in terms of crime reduction. With the effort of creating a neighbourhood watch scheme, you want to give it the best chance of success – enter maps!
This may not seem like the most important tool for a neighborhood watch. At face value I would agree with you. Surely you would want flash lights, vehicles and a bunch of cool security gadgets, not to mention the ever-popular two-way radio? Yes, these are all tools that allow a neighborhood watch to perform its tasks (click here for a detailed discussion on this topic).
But let’s take a strategic look at your suburb’s safety. Considering the amount of effort that goes into putting a neighborhood watch scheme together; you want to ensure that you are getting the most bang for your buck. Here are some questions that need answering: Are you patrolling in the right place? Are your patrols having an effect on the local crime?
How Maps are Used
Obviously the most fun kind of maps are treasure maps. The exciting big red X marks the spot. Who wouldn’t want one, or maybe even ten, of those? But maps don’t only show the location of treasure chests. With the advent of electronic and online mapping techniques, a multitude of uses have emerged. This includes directing us from A to B in the car, or finding the closest hospital. Better yet; the local pizza joint (another kind of treasure).
Maps are a powerful way to represent spatial information. Take a road trip from Johannesburg to Cape Town, South Africa (it’s a worthwhile holiday destination). A quick mapping exercise tells us that it’s a 1398-kilometre drive (that’s 868 miles for those of you who have not been lucky enough to grow up with the metric system). The map will show you that you are going to travel in a southwest direction. It will show you how many towns you will travel through and the attractions on route. It even shows that you will travel through a desert before emerging into green winelands.
But while you are holidaying in the Fair Cape, you want to know that you have not had some unwelcomed house guests and your TV stays just where you left it. So how do we make maps that will help keep your TV out of the hands of a greedy pillager?
Space Age Maps
Maps can be drawn by hand just like your childhood treasure maps. You may quickly jot down a map on a piece of paper, while taking directions down on the phone.
Luckily for us, with the increase in technology, maps can now be made using a variety of computer programs. These are commonly known as Geographic Information Systems (GIS). As the name suggests, these systems represent geographic information (the position of a thing on Earth or in space) in picture format.
In other words, a map. Since 2005, Google Maps and cellular technology have made the use of GIS very popular, if not essential. New uses of GIS and maps are continuously being identified, from mapping locations of street art (and categorising the good from the bad), to processing satellite imagery for crop growth and harvest volume predictions. The truth is, the only real limitation to modern maps is the imagination of the user.
Let’s have a closer look at crime. In the context of mapping, we are saying that crime is spatial in nature. Each incident takes place at a specific location, at a time or in a time frame with an unfortunate outcome. In some instances, the outcome is less severe such as a car theft. In the event of a home invasion or murder the result is devastating. Let’s add a few more variables. Were there other incidents connected to this incident? Was a specific modus operandi used? Is there a specific region that keeps getting hit? Unless your brain is like a super computer, it is difficult to accurately place each crime in space relative to one another.
To add a little complication to the issue, it turns out that perception is a powerful thing. When you start your neighbourhood watch you are going to have to decide how your patrols take place. The last piece of advice you need is something like: “We need to get lots of patrols down Francolin Street because that’s where all those foreigners live”. This leaves you with a few options:
- Let your patrollers drive where ever they like and hope for the best results.
- Let your patrollers patrol in the areas that worry them the most and hope that they are right.
- Patrol all the streets because that’s what makes people feel safer.
- Apply some science to the system by adding extra patrols into hot spots and criminal infiltration areas.
Researchers Natalie Lopez and Chris Lukinbeal, report that there are various studies showing that there is a difference between where crime actually happens and where people perceive that crime happens. This applies to citizens and even to the police. People create what is called a “mental map”. This is a type of mentally visualised Google Earth, complete with images, locations and street names. However, mental maps don’t only include locational data. Like the old treasure maps that got you excited as a 10-year-old want to be pirate, they include emotional metadata. This often manifests as an “impression” of where an event takes place. These maps are often informed by various events, biases and emotions. Certain publications also supply mental maps with data, including social media posts, the press or crime data that is supplied to the police.
Studies into this phenomenon have shown that there are differences between where residents and police perceive crime hotspots. Yup, the pro’s also get it wrong. In a paper titled “Chasing Ghosts? Police Perception of High Crime Areas”, researchers Ratcliffe and McCullagh describe how the type of crime and even the emotional effect of a crime can influence a policeman’s perception of a high crime zone. While the academics delve into this mystery, you are on holiday and worrying about the safety of your TV. You want your neighbourhood watch to get the best results for your efforts. Enter maps and GIS.
Crime maps for your suburb
By creating a map containing all the locations of all the crime events, it is possible to very accurately, start understanding the relationship between crimes and their spatial position. A pattern then starts to unfold. For example, two crimes have taken place. One happened at 35 de Beer Road and the other at 65 Crystal Road. This is useful information, as we know that two crimes have occurred and where they occurred. Once a map is employed, it is possible to see that 35 de Beer Road is directly across a greenbelt area from 65 Crystal Road. Then comes the lightbulb moment: Everyone knows that houses along greenbelts are targeted more frequently. It’s easy to escape down the greenbelt with the bounty.
This leads to the next question: Are there any other spatial patterns that can be identified by developing a map? And the most important question is: Can we start identifying hot crime areas and target these areas for extra neighbourhood watching? By increasing presence and awareness in the neighbourhood through effectively identifying soft target spots and crime patterns, the crime in the area can be reduced.
Let’s have a look at an example.
The Murdersdrift Case Study
My folks live in small sector of the infamous Murdersdrift area. Actually, it’s called Muldersdrift, but due to the large murder count, cynical residents adopted its new nickname.
During 2013 and 2014 there was an increase in violent criminal activity in Muldersdrift. The area is composed of miles of open grassland, interspersed with large plots, or agricultural holdings. Most properties have poor fencing, unkempt dirt roads and are serviced by a struggling local police station. Security companies are active, but struggle to cover enough ground to monitor and provide a significant security presence. Facing a spate of murders, a sector of the community opted to initiate a neighbourhood watch scheme. Luckily, the community had members with experience in the security and military industries amongst their number. This helped to set up best practice strategies and safety precautions.
The team decided that a communication network and a rotation schedule for patrolling was a good starting point. They also started asking questions such as:
- Are there places that get hit most often?
- Can we see any patterns emerging with time?
- If we do more patrols in areas that get hit a lot, will the crime incidents reduce?
The team suspected that the answers to these questions may yield some interesting and important results.
The next step was to get data.
Step 1: Collect the data
To start the process, the team began recording as much information as possible about each crime incident. The most crucial piece of information that needed to be present was the location (GPS position) of the crime. Other information recorded included the time of day, date, type of crime, etc. The team recorded anything they could think of that may be of value.
Step 2: Represent the crime spatially
Because the GPS location of the crimes were recorded, a map showing the crimes could be made using GIS (Map 1). This map showed the team that there were places that had a higher concentration of crimes (as they suspected).
After hours of diligent patrols and data collection, the team started noticing certain patterns. One of which was that most of the crimes happened to people living along unfenced open areas and the river (Map 2). Immediately, all these vulnerable places were identified and placed in the map. Then the next bright idea hit! What about roads? Are there more crimes where there is better road access (for entry and high-speed escape)? And what about footpath access?
Step 3: Identify a pattern
Slowly a picture was emerging.
The team began plotting more and more things on their trusty maps. They started analysing the type of crime to see if it was location specific or maybe time of day specific (Map 3). Did houses with dogs get less crime than houses that have no dogs?
“How about the phase of the moon?” someone asked”. “Are more crimes happening when its new moon and therefore darker outside?”
There was an explosion of maps. Happily, none of them had to be drawn by hand thanks to the ever useful GIS.
As the GIS was utilised more and more, the functionality of the GIS map making programme was investigated and aggregate maps were created. Heat maps were discovered with the help of the all-knowing Google (Map 4). Filters and classifications were applied to the data. A second explosion of maps came about. At one point there were so many maps, the torches got lost under the pile.
Step 4: Create a prevention strategy
Eventually after sticking maps up like wallpaper, the team got their permanent markers out and started drawing links to common locations and having mini eureka moments. Hot spots were identified. Times when crimes were most likely to occur were identified. The team created a schedule that fitted into their predictive analysis of when and where they thought crimes would happen. In the neighbourhood, the crime dropped. Surrounding areas without such diligent methods continued on the trajectory of rising criminal activity.
The team also added some good old-fashioned prep to the scheme. This included first aid kits, radio and safe patrol procedures.
Step 5: Happy neighbourhood
The knowledge of the team combined with the power of maps allowed for an effective solution to a deadly problem. Since this time, the sector has been one of the safest in the region and the residents could get on with the day to day wonders of country life including fires, snakes and the occasional noisy party.
References & further reading
Bennett, T., Holloway, K., & Farrington, D. P. (2009). A Review of the Effectiveness of Neighbourhood. Security Journal. doi:10.1057/palgrave.sj.8350076
Johnson, C. P. (2000). Crime Mapping and Analysis Using GIS. Conference on Geomatics in Electronic Governanace. Pune : Geomatics Group .
Lopez, Natalie; Lukinbeal , Chris. (2010). Comparing Police and Residents’ Perceptions of Crime in a Phoenix. Yearbook of the Association of Pacific Coast Geographers,, 72, 33 -55. Retrieved from https://www.jstor.org/stable/pdf/24043341.pdf
Ratcliffe, J. H., & McCullagh, M. J. (2001). Chasing Ghosts? Police Perceptioln of High Crime Areas. Brit.J.Crimnol, 41, 300-341. Retrieved from http://www.jmu.edu/icle/pdf_files/Applied%20Research/Towards%20an%20Information%20Driven%20Organization/Chasing%20Ghosts%20-%20Police%20Perception%20of%20Hgh%20Crime%20Areas.pdf
Rosenberg, M. (2018, October 06). What is a Mental Map? Retrieved from ThoughtCo.: https://www.thoughtco.com/mental-map-definition-1434793