An analysis about the accuracy of geographic profiling in relation to the number of observations and the buffer zone

Ugo Santosuosso () and Alessio Papini ()
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Ugo Santosuosso: University of Florence
Alessio Papini: University of Florence

Journal of Geographical Systems, 2022, vol. 24, issue 4, No 5, 656 pages

Abstract: Abstract Geographic Profiling (GP) attempts to reconstruct the spreading centre of a series of events due to the same cause. The result of the analysis provides an approximated localization of the spreading centre within an area (often represented as a red red), where the probability of finding it is higher than a given threshold (typically 95%). The analysis has as an assumption that the events will be likely to occur at very low probability around the spreading centre, in a ring-shaped zone called the buffer zone. Obvious examples are series of crimes perpetrated by an offender (unwilling to perpetrate offences close to home), or the localities of spread of an invasive species, where the buffer zone, if present, depends on the biological features of the species. Our first aim was to show how the addition of new events may change the preliminary approximate localization of the spreading centre. The analyses of the simulated data showed that if B, the parameter used to represent the radius of the buffer zone, varies within a range of 10% from the real value, after a low number of events (7–8), the method yields converging results in terms of distance between the barycentre of the red zone and the “real” user provided spreading centre of a simulated data set. The convergence occurs more slowly with the increase in inaccuracy of B. These results provide further validity to the method of the GP, showing that even an approximate choice of the B value can be sufficient for an accurate location of the spreading centre. The results allow also to quantify how many samples are needed in relation to the uncertainty of the chosen parameters, to obtain feasible results.

Keywords: Geographic profiling; Criminal geographic targeting algorithm; Modelling; Centre of origin; Buffer zone; Crimes mapping (search for similar items in EconPapers)
JEL-codes: C13 C15 C31 Q56 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10109-022-00379-5

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