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Proceedings Paper

Multiresolution processing for fractal analysis of airborne remotely sensed data
Author(s): Sandeep Jaggi; Dale A. Quattrochi; Nina Siu-Ngan Lam
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Paper Abstract

Fractal geometry is increasingly becoming a useful tool for modeling natural phenomenon. As an alterative to Euclidean concepts, fractals allow for a more accurate representation of the nature of complexity in natural boundaries and surfaces. Since they are characterized by self- similarity, an ideal fractal surface is scale-independent; i.e. at different scales a fractal surface looks the same. This is not exactly true for natural surfaces. When viewed at different spatial resolutions parts of natural surfaces look alike in a statistical manner and only for a limited range of scales. In this paper, images acquired by NASA's Calibrated Airborne Multispectral Scanner are used to compute the fractal dimension as a function of spatial resolution. Three methods are used to determine the fractal dimension--Shelberg's line-divider method, the variogram method and the triangular prism method. A description of these methods and the result of applying these methods to a remotely-sensed image is also presented. The scanner data was acquired over western Puerto Rico in January, 1990 over land and water. The aim is to study impacts of man-induced changes on land that affect sedimentation into the near-shore environment. The data was obtained over the same area at 3 different pixel sizes--10 m, 20 m and 30 m.

Paper Details

Date Published: 1 October 1992
PDF: 12 pages
Proc. SPIE 1705, Visual Information Processing, (1 October 1992); doi: 10.1117/12.138442
Show Author Affiliations
Sandeep Jaggi, Lockheed/Stennis Space Ctr. (United States)
Dale A. Quattrochi, NASA/Stennis Space Ctr. (United States)
Nina Siu-Ngan Lam, Loiusiana State Univ. (United States)


Published in SPIE Proceedings Vol. 1705:
Visual Information Processing
Friedrich O. Huck; Richard D. Juday, Editor(s)

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