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Fractal Analysis of Multiscale Spatial Autocorrelation among Point Data

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  • L De Cola

    (US Geological Survey, 521 National Center, Reston, VA 22092, USA)

Abstract

The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D , may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems.

Suggested Citation

  • L De Cola, 1991. "Fractal Analysis of Multiscale Spatial Autocorrelation among Point Data," Environment and Planning A, , vol. 23(4), pages 545-556, April.
    • Handle: RePEc:sae:envira:v:23:y:1991:i:4:p:545-556
    DOI: 10.1068/a230545
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    References listed on IDEAS

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    1. J B Parr & G J O'Neill, 1989. "Aspects of the Lognormal Function in the Analysis of Regional Population Distribution," Environment and Planning A, , vol. 21(7), pages 961-973, July.
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