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A computationally efficient method for delineating irregularly shaped spatial clusters |
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| Authors: | Juan C Duque Jared Aldstadt Ermilson Velasquez Jose L Franco Alejandro Betancourt |
| Institution: | 1. Research in Spatial Economics (RISE-group), Department of Economics, EAFIT University, Carrera 49 7 Sur-50, Medellin, Colombia 2. Department of Geography, University at Buffalo, 117 Wilkeson Quad, Buffalo, NY, 14261-0055, USA 3. Research in Spatial Economics (RISE-group), Department of Fundamental Sciences, EAFIT University, Carrera 49 7 Sur-50, Medellin, Colombia |
| 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?C343, 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. |
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