Crime mapping and related research can be divided between analysis of places, distances, and directions. Authors Richard Frank, Martin A. Andresen, and Patricia L. Brantingham argue that directionality is the most underrepresented of the three crime mapping analysis elements. Places and distances traveled are sometimes not comprehensive enough for crime patterns or for particular directions crime is more likely to target. The authors argue that people are directionally biased towards certain locations. Strong directionality is found when a person travels from the home to other locations, such as entertainment, work, and shopping, all within a 45 degree angle from the home. Another way to put this is that a person with strong directionality is likely to travel to locations that are closer to one another and then go home, rather than circling around or returning home before completion of these activities. Directionality is also influenced by frequency of trips to particular locations.
The authors analyzed data from five municipalities in British Columbia, Canada: Coquitlam, Maple Ridge, Surrey (all within the Metro Vancouver area), Prince George (just outside of the Metro Vancouver area), and Nanaimo (on Vancouver Island). They used two different kinds of analysis: arrows to show the direction from the home to the criminal incident (exclusive of distance) and colored dots to show the direction of the crime (green equates to south, red equates to north, west equates to blue, and east equates to yellow). The authors argue that this type of crime mapping visualization technique is an improvement on previously used techniques which appeared convoluted.
The authors found that this technique was largely successful for mapping the directional bias of criminal activity for each of the municipalities. They found that the directional arrows or colored dots accurately depicted where criminal opportunity was likely to occur (shopping centers and downtown areas). The authors suggest analyzing strength of directionality for future research to show which areas are more likely to have higher amounts of criminal activity stemming from them.
This study does a good job emphasizing the importance of directionality for crime mapping. It is easily applicable to law enforcement intelligence as a tool to locate origin points in neighborhoods with particularly high quantities of crime emanating from them. The same idea can be used for other topics such as competitive analysis for product information distribution (ex: examining the magnitude of where people from certain areas like to shop).
I was somewhat confused how geometry was critical to this analysis as directionality was only shown in one direction instead of the interconnectivity of home, work, entertainment, and shopping. Additionally, the authors argue the arrows simplify the mapping process. However, I believe some areas are unreadable due to the quantity of arrows in a particular location. Lastly, the rainbow dots symbolizing crime direction seem like a good idea at first, but are not easily readable in reality. I found myself examining the color key on many occasions trying to remember which color symbolized which direction. This analysis could be improved by changing how the arrows are represented (maybe one big arrow for a higher crime area), remove similar arrows for simplification, or simplifying the colors to four or eight colors for readability.
Frank, R., Andresen, M.A., & Brantingham, P.L. (2013). Visualizing the directional bias in property crime incidents for ﬁve Canadian municipalities. The Canadian Geographer, 57(1), 31-42. Retrieved from: http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0064.2012.00450.x/pdf