Estimating fractal dimension of profiles: A comparison of methods |
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Authors: | John C. Gallant Ian D. Moore Michael F. Hutchinson Paul Gessler |
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Affiliation: | (1) Centre for Resource and Environmental Studies, Australian National University, 0200 Canberra, ACT, Australia;(2) Centre for Resource and Environmental Studies, Australian National University, Australia;(3) CSIRO Division of Soils, Canberra, ACT, Australia |
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Abstract: | This paper examines the characteristics of four different methods of estimating the fractal dimension of profiles. The semi-variogram, roughness-length, and two spectral methods are compared using synthetic 1024-point profiles generated by three methods, and using two profiles derived from a gridded DEM and two profiles from a laser-scanned soil surface. The analysis concentrates on the Hurst exponent H,which is linearly related to fractal dimension D,and considers both the accuracy and the variability of the estimates of H.The estimation methods are found to be quite consistent for Hnear 0.5, but the semivariogram method appears to be biased for Happroaching 0 and 1, and the roughness-length method for Happroaching 0. The roughness-length or the maximum entropy spectral methods are recommended as the most suitable methods for estimating the fractal dimension of topographic profiles. The fractal model fitted the soil surface data at fine scales but not at broad scales, and did not appear to fit the DEM profiles well at any scale. |
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Keywords: | power spectrum maximum entropy semi-variogram roughness-length confidence interval |
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