Summary
This paper deals with a new method of constructing homogenous clusters of geographical regions taking spatial autocorrelation into account. Overall variograms are calculated to represent the individual variograms describing each of the measured variables. A modified distance matrix is then determined based on the overall variogram and accounting for geographical distances between the centroids of the regions as well as for the angles between them. The clustering solution based on this procedure gives better results than other conventional techniques.
This paper was financially supported by the Fond zur Forderung der wissenschaftlichen Forschung (FWF), Project No. P09878- BIO. The authors gratefully acknowledge the constructive remarks of the editor and two referees.
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© 1996 Springer-Verlag Berlin · Heidelberg
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Hussain, M., Fuchs, K. (1996). Cluster Analysis Using Spatial Autocorrelation. In: Bock, HH., Polasek, W. (eds) Data Analysis and Information Systems. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-80098-6_5
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DOI: https://doi.org/10.1007/978-3-642-80098-6_5
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