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Some Distinctions Between Self-Similar and Self-Affine Estimates of Fractal Dimension with Case History

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Abstract

Compass, power-spectral, and roughness-length estimates of fractal dimension are widely used to evaluate the fractal characteristics of geological and geophysical variables. These techniques reveal self-similar or self-affine fractal characteristics and are uniquely suited for certain analysis. Compass measurements establish the self-similarity of profile and can be used to classify profiles based on variations of profile length with scale. Power spectral and roughness-length methods provide scale-invariant self-affine measures of relief variation and are useful in the classification of profiles based on relative variation of profile relief with scale. Profile magnification can be employed to reduce differences between the compass and power-spectral dimensions; however, the process of magnification invalidates estimates of profile length or shortening made from the results. The power-spectral estimate of fractal dimension is invariant to magnification, but is generally subject to significant error from edge effects and nonstationarity. The roughness-length estimate is also invariant to magnification and in addition is less sensitive to edge effects and nonstationarity. Analysis of structural cross sections using these methods highlight differences between self-similar and self-affine evaluations. Shortening estimates can be made from the compass walk analysis that includes shortening contributions from predicted small-scale structure. Roughness-length analysis reveals systematic structural changes that, however, cannot be easily related to strain. Power-spectral analysis failed to extract useful structural information from the sections.

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REFERENCES

  • Brigham, E. O., 1974, The fast Fourier transform: Prentice-Hall, Englewood Cliffs, New Jersey.

    Google Scholar 

  • Brown, S., 1987, A note on the description of surface roughness using fractal dimension: Geophys. Res. Lett., v. 14, no. 11, p. 1085–1098.

    Google Scholar 

  • Douds, A. S. B., 1998, Fractal analysis of topography and structure across the Appalachian foreland of West Virginia: unpubl. Masters thesis, West Virginia University, 119 p.

  • Fox, C., 1985, Description, analysis, and prediction of sea-floor roughness using spectral models: Naval Oceanographic Office Technical Report 279, Bay St. Louis, MO, 218 p.

  • Fox, C., 1989, Empirically derived relationships between fractal dimension and power law form frequency spectra: Pure and Applied Geophysics, v. 131, p. 211–239.

    Google Scholar 

  • Gilbert, L., 1989, Are topographic data sets fractal? Pure and Applied Geophysics, v. 131, p. 241–254.

    Google Scholar 

  • Klinkenberg, B., 1994, A review of methods used to determine the fractal dimension of linear features: Math. Geology, v. 26, no. 1, p. 23–46.

    Google Scholar 

  • Malenverno, A., 1989, Testing linear models of sea-floor topography: Pure and Applied Geophysics, v. 131, p. 139–155.

    Google Scholar 

  • Mandelbrot, B. B., 1967, How long is the coast of Britain? Statistical similarity and fractional dimension: Science, v. 156, p. 636–638.

    Google Scholar 

  • Mandelbrot, B. B., 1985, Self-affine fractals and fractal dimension: Physica Scripta, v. 32, p. 257–260.

    Google Scholar 

  • Mandelbrot, B. B., and van Ness, J., 1968, Fractional Brownian motions, fractional noises and Applications: SIAM Review, v. 10, no. 7, p. 422–437.

    Google Scholar 

  • Mareschal, J., 1989, Fractal reconstruction of sea-floor topography: Pure and Applied Geophysics, v. 131, p. 197–210.

    Google Scholar 

  • Oppenheim, A., and Schafer, R., 1975, Digital signal processing: Prentice-Hall, Englewood Cliffs, New Jersey, 585 p.

    Google Scholar 

  • Press, W. H., Flannery, B. P., Teukolsky, S. A., and Vetterling, W. T., 1988, Numerical recipes: The art of scientific computing: Cambridge University Press, Cambridge, 818 p.

    Google Scholar 

  • Termonia, Y., and P. Meakin, 1986, Formation of fractal cracks in a kinetic fracture model: Nature, v. 320, p. 429–431.

    Google Scholar 

  • Turcotte, D. L., 1989, Fractals in geology and geophysics: Pure and Applied Geophysics, v. 131, p. 171–196.

    Google Scholar 

  • Turcotte, D. L., 1992, Fractals and chaos in geology and geophysics: Cambridge University Press, Cambridge, 221 p.

    Google Scholar 

  • Turcotte, D. L., 1997, Fractals and chaos in geology and geophysics, 2nd ed.: Cambridge University Press, Cambridge, 398 p.

    Google Scholar 

  • Voss, R. F., 1985a, Random fractals: Characterization and measurement: Scaling phenomena in disordered systems, R. Pynn and A Skejeltorp, eds.; Plenum Press, New York, pp. 1–11.

    Google Scholar 

  • Voss, R. F., 1985b, Random fractal forgeries: Fundamental algorithms for computer graphics, NATO ASI Series, vol. F17, R. A. Earnshaw, ed., Springer-Verlag, Berlin, pp. 805–835.

    Google Scholar 

  • Voss, R. F., 1988, Fractals in nature: From characterization to simulation: The Science of Fractal Images, H. O. Peitgen and D. Saupe, eds., Springer-Verlag, New York, pp. 21–70.

    Google Scholar 

  • Wilson, T. H., 1997, Fractal strain distribution and its implications for cross-section balancing further discussion: Jour. of Structural Geology, v. 19, no. 1, p. 129–132.

    Google Scholar 

  • Wilson, T. H., and Dominic, J., 1998, Fractal interrelationships between topography and structure: Earth Surf. Processes Landforms, v. 23, p. 509–525.

    Google Scholar 

  • Wong, P., 1987, Fractal Surfaces in porous media: Amer. Inst. Phys. v. 154, p. 304–318.

    Google Scholar 

  • Wu, S., 1993, Fractal strain distribution and its implications on cross-section balancing: Jour. of Structural Geology, v. 15, p. 1497–1507.

    Google Scholar 

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Wilson, T.H. Some Distinctions Between Self-Similar and Self-Affine Estimates of Fractal Dimension with Case History. Mathematical Geology 32, 319–335 (2000). https://doi.org/10.1023/A:1007585811281

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