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Bivariate Spatial Clustering Analysis of Point Patterns: A Graph-Based Approach

  • Colin Robertson
  • Steven Roberts
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7974)

Abstract

Point pattern analysis is concerned with characterizing a spatial point process. A bivariate point process is one that generates points that are marked with binary values. There exists of dearth of methods for the spatial-analysis of non-numerical marked point pattern data, while these forms of data are increasingly common as a result of volunteered geographic information and geographically-indexed social media data. This paper highlights the problem of bivariate point clustering. A new method based on Delaunay triangulation is presented. Simulation studies are carried out to compare the new approach to existing methods. A case study examines clustering of antimicrobial resistance in Sri Lankan shrimp farms to illustrate the strengths and weaknesses of the method.

Keywords

clustering spatial analysis bivariate join-counts spatial graphs 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Colin Robertson
    • 1
  • Steven Roberts
    • 1
  1. 1.Wilfrid Laurier UniversityWaterlooCanada

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