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Computation of Surface Roughness of Mountains Extracted from Digital Elevation Models

Author(s): S. Dinesh

Journal: Journal of Applied Sciences
ISSN 1812-5654

Volume: 8;
Issue: 2;
Start page: 262;
Date: 2008;
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Keywords: Mountains | multiscale digital elevation models | lifting scheme | convex and concave regions | normalized distribution function | surface roughness

In this study, a procedure to compute the surface roughness of individual mountain objects extracted from Digital Elevation Models (DEMs) is proposed. First, mathematical morphology is employed to extract the mountains of the DEM. The lifting scheme is employed to perform the generation of multiscale DEMs. The mask of pixels modified in each mountain object at each scale is computed by performing the intersection operation between the mountain object and the mask of pixels modified at each scale. The normalized probability functions for each mountain object are computed as the ratio of the area of pixels modified in the mountain object at each scale to the area of the mountain object. The computed normalized probability functions are used to compute the scale-independent average roughness of the mountain objects due to the distribution of convex and concave regions averaged over the mountain objects. The proposed methodology allows for a more accurate quantification of a region`s convexity/concavity over varying scales, distinguishing between shallow and deep incisions and hence provides a more accurate surface roughness parameter. It is observed that the larger the area of the mountain object, the higher is its surface roughness.

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