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 language | English |
|---|---|
| Pages (from-to) | 355-372 |
| Number of pages | 18 |
| Journal | Journal of Geographical Systems |
| Volume | 13 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Dec 2011 |
| Externally published | Yes |
Keywords
- AMOEBA
- Cluster detection
- Ecotope
- Local G statistic
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Cite this
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