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Critical issues in the evaluation of spatial autocorrelation

  • Spatial Analysis
  • Conference paper
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Spatial Information Theory A Theoretical Basis for GIS (COSIT 1993)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 716))

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Abstract

Spatial autocorrelation measures the degree to which a spatial phenomenon is correlated with itself in space. As such, it can be used as an indicator of the fundamental topological structure of the spatial relationship among geographic entities displayed on a map. Statistics of spatial autocorrelation are especially useful for characterizing the spatial pattern in the distribution of any phenomenon in question. This paper addresses three important issues pertaining to the evaluation of spatial autocorrelation: measurement of the study variable, definition of geographic units, and specification of spatial weighting functions. Theoretically, spatial autocorrelation is most adequately evaluated when the study variable is measured in either an interval or a ratio scale and geographic units are better delineated by polygons of homogeneous surfaces based on variables that are significant to the distribution of the study phenomenon. In evaluating spatial autocorrelation, weighting functions such as area, boundary length, distance, and their combinations must be examined carefully and specified whenever necessary.

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Authors and Affiliations

  1. Department of Earth Sciences, University of California, 92521-0423, Riverside, CA, USA

    Yue-Hong Chou

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  1. Yue-Hong Chou
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Andrew U. Frank Irene Campari

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© 1993 Springer-Verlag Berlin Heidelberg

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Chou, YH. (1993). Critical issues in the evaluation of spatial autocorrelation. In: Frank, A.U., Campari, I. (eds) Spatial Information Theory A Theoretical Basis for GIS. COSIT 1993. Lecture Notes in Computer Science, vol 716. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-57207-4_28

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  • DOI: https://doi.org/10.1007/3-540-57207-4_28

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-57207-7

  • Online ISBN: 978-3-540-47966-6

  • eBook Packages: Springer Book Archive

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