Geo-Profiling: beyond the Current Limits. A Preliminary Study of Mathematical Methods to Improve the Monitoring of Invasive Species
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The Geographic Profiling (GP) is a data analysis tool that has great potential. Presently, it is used only minimally, and is almost always used “as it is”, independently on other analysis or data processing methods. GP was initially created as a forensic tool, to find the origin of a series of events (crimes) done by a single actor. However, using this method in integration with others, it is possible to enlarge the opportunities of geographical data analysis. The promising results of this method in integration with others, even if some of them are quite well known methods since many years–and thus well tested–show a number of further possible applications. Here we treat data clustering and partitioning with Kmeans and Dbscan methods; space partitioning (Voronoi tessellation) and a method to assign weights to the events constituting the data set. The software used in this review was written in Python, was released under GPL license and is available on Bitbucket (https://bitbucket.org/ugosnt/al_and_ugo/).
KeywordsGeographic profiling invasive species clustering DBSCAN weighted geoprofiling
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