Are Measures of Patrollability Affected by Tessellating Shape

Implications for Grid-Based Crime Hot Spot Maps


  • Carli Rickson The University of Tampa
  • Timothy Hart The University of Tampa
  • Gabriel Paez The University of Tampa
  • Nathan Connealy The University of Tampa



hot spots, crime mapping, tessellating shape, patrollability


A grid-based thematic map is a spatial analysis tool that can be used to identify crime patterns, aiding law enforcement agencies in identifying problem areas within their jurisdictions and allocating resources to address them. Grids used to create these maps are comprised of shapes that tessellate (i.e., squares, hexagons, triangles). Square grids are used most often in crime hot spot mapping, but little is known whether the choice of tessellating shape affects performance metrics used to assess prospective hot spot forecasts. Using a purposive sample of known crime locations in St. Petersburg, Florida, the current study investigated whether tessellating shape used in grid-based thematic maps affects one particular performance metric: patrollability. Findings were mixed, showing that the effect tessellating shape has on grid-based thematic maps varies by type of crime and on which patrollability metric is used to assess forecasting performance. Results are discussed in terms of their impact on practioners' use of crime hot spot mapping in law enforcement and on future research.


Download data is not yet available.


Metrics Loading ...

References or Bibliography

Adepeju, M., Cheng, T., Shawe-Taylor, J., & Bowers, K. (2014). A new metric of crime hotspots for operational policing. A paper presented at the 19th Geographical Information Science Research UK Conference, Leeds, UK.

Adepeju, M., Rosser, G., & Cheng, T. (2016). Novel evaluation metrics for sparse spatio-temporal point process hotspot predictions: A crime case study. International Journal of Geographical Information Science, 30(11), 2133–2154. DOI: 10.1080/ 13658816.2016.1159684.

Bender, E. (1962). Area-perimeter relations for two dimensional lattices. The American Mathematical Monthly, 69, 742–774.

Berry, J. K. (2007). Map analysis: Understanding spatial patterns and relationships. GeoTech Media: San Francisco, CA.

Birch, C. P. D., Oom, S. P., & Beecham, J. A. (2007). Rectangular and hexagonal grids used for observation, experiment, and simulation in ecology. Ecological Modelling, 206(3–4), 347–359.

Birks, D., Townsley, M., & Stewart, A. (2012). Generative explanations of crime: Using simulation to test criminological theory. Criminology, 50(1), 221–254.

Bottoms, A. E., & Wiles, P. (1997). Environmental Criminology. In M. Maguire, R. Moran, & R. Reiner (Eds.), The Oxford handbook of Criminology (pp. 620–656). Oxford: Clarendon Press.

Bowers, K. J., Johnson, S. D., & Pease, K. (2004). Prospective hot-spotting: The future of crime mapping? British Journal of Criminology, 44(5), 641–658. DOI: 10.1093/bjc/azh036.

Brantingham, P. J. & Brantingham, P. L. (1991). Environmental Criminology. Prospect Heights, IL: Waveland Press.

Brantingham, P. J. & Brantingham, P. L. (1995). Criminality of place: Crime generators and crime attractors. European Journal on Criminal Policy and Research, 3(3), 5–26.

Brantingham, P. J., Brantingham, P. L. (1998). Environmental criminology: From theory to urban planning practice. Studies on Crime and Crime Prevention.

Brantingham, P. J., & Brantingham, P. L. (2013). Environmental criminology and crime analysis.

Brantingham, P. L., & Brantingham, P. J. (1993). Nodes, paths and edges: Considerations on the complexity of crime and the physical environment. Journal of Environmental Psychology, 13(1), 3–28.

Brantingham, P. J., Brantingham, P. L., & Andresen, M. A. (2016). The geometry of crime and crime pattern theory.

Bruinsma, G. N., & Johnson, S. D. (2018). The oxford handbook of environmental criminology. New York, NY: Oxford University Press.

Chainey, S., Tompson, L., & Uhlig, S. (2008). The utility of hotspot mapping for predicting patterns of crime. Security Journal, 21, 4–28.

Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44, 588–608.

Cornish, D. B., & Clarke, R.V. (1987). Understanding crime displacement: An application of rational choice theory. Criminology, 25(4), 933–948.

Cornish D.B., & Clarke R.V. (2008) The rational choice perspective. In: Wortley R, Mazerolle L (eds) Environmental criminology and crime analyses. Willian, Cullompton

Eck, J. E., Chainey, S., Cameron, J. G., Leitner, M., & Wilson, R. E. (2005). Mapping crime: Understanding hotspots. National Institute of Justice Special Report.

Federal Bureau of Investigation (FBI). (2004). Uniform crime reporting handbook: UCR. Retrieved from

Felson, M. & Eckert, M. (2016). Crime and everyday life (5th ed.). Sage: New York, NY.

Hart, T. C. (2021). Investigating crime pattern stability at micro-temporal intervals: Implications for crime analysis and hotspot policing strategies. Criminal Justice Review, 46(2), 173–189.

Hart, T. C., & Miethe, D. (2014). Street robbery and public bus stops: A case study of activity nodes and situational risk. Security Journal, 27, 180–193. DOI: 10.1057/sj.2014.5

Hart, T. C., & Zandbergen, P. A. (2014). Kernel density estimation and hotspot mapping: examining the influence of interpolation method, grid cell size, and bandwidth on crime forecasting. Policing: An International Journal of Police Strategies & Management, 37(2), 305–323. 10.1108/PIJPSM-04-2013-0039.

Jones, R. W., & Pridemore, W. A. (2019). Toward an integrated multilevel theory of crime at place: Routine activities, social disorganization, and the law of crime concentration. Journal of Quantitative Criminology, 35, 543–572.

Nelson, J. K., & Brewer, C. A. (2017). Evaluating data stability in aggregation structures across spatial scales: revisiting the modifiable areal unit problem. Cartography and Geographic Information Science, 44(1), 35–50.

Olgahere, A., & Lum, C. (2018). Classifying “micro” routine activities of street-level drug transactions. Journal of Research in Crime and Delinquency, 55(4), 466–492.

Song, J., Andresen, M. A., Brantingham, P. L., & Spicer, V. (2017). Crime on the edges: Patterns of crime and land use change. Cartography and Geographic Information Science, 44(1), 51–61.

Townsley, M., & Sidebottom, A. (2010). All offenders are equal, but some are more equal than others: variation in journeys to crime between offenders. American Society of Criminology, 48(3).

Tukey, J. W. (1977). Exploratory data analysis. Reading, Massachusetts: Addison-Wesley.

Turner, M. G. (1989). Landscape ecology: The effect of pattern on process. Annual Review of Ecology and Systematics, 20(1), 171–197. doi:10.1146/

Wortley, R., & Townsley, M. (2017). Environmental criminology and crime analysis. New York: Routledge.



How to Cite

Rickson, C., Hart, T., Paez, G., & Connealy, N. (2023). Are Measures of Patrollability Affected by Tessellating Shape: Implications for Grid-Based Crime Hot Spot Maps. Journal of Student Research, 12(3).



Research Articles