A computationally efficient method for delineating irregularly shaped spatial clusters

J.C. Duque, J. Aldstadt, E. Velasquez, Jose L. Franco, A. Betancourt Arango

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7 Citations (Scopus)

Abstract

In this paper, we present an efficiency improvement for the algorithm called AMOEBA, A Multidirectional Optimum Ecotope-Based Algorithm, devised by Aldstadt and Getis (Geogr Anal 38(4):327-343, 2006). AMOEBA embeds a local spatial autocorrelation statistic in an iterative procedure in order to identify spatial clusters (ecotopes) of related spatial units. We provide an analysis of the computational complexity of the original AMOEBA and develop an alternative formulation that reduces computational time without losing optimality. Empirical evidence is provided using georeferenced socio-demographic data in Accra, Ghana.

Original languageEnglish
Pages (from-to)355-372
Number of pages18
JournalJournal of Geographical Systems
Volume13
Issue number4
DOIs
Publication statusPublished - Dec 2011
Externally publishedYes

Keywords

  • AMOEBA
  • Cluster detection
  • Ecotope
  • Local G statistic

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    Duque, J. C., Aldstadt, J., Velasquez, E., Franco, J. L., & Betancourt Arango, A. (2011). A computationally efficient method for delineating irregularly shaped spatial clusters. Journal of Geographical Systems, 13(4), 355-372. https://doi.org/10.1007/s10109-010-0137-1