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Proceedings Paper

Quantifying topographic fabric: eigenvector analysis using digital elevation models
Author(s): Peter L. Guth
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Paper Abstract

Digital elevation models provide an estimate of the topographic fabric (the tendency for topography to have a preferred orientation) of the earth's surface. The algorithm extracts the eigenvectors and eigenvalues from a 3 X 3 matrix of the sums of the cross products of the directional cosines of the surface normals computed at each point in the DEM. The ratio of eigenvalues S1 (largest) and S2 measures the ruggedness of the terrain. The ratio of eigenvalues S2 and S3 (smallest) measures the tendency for the terrain to have a preferred orientation, while their orientation reflects the direction of dominant topographic fabric. Sample sizes of about 500 - 2500 points provide robust statistics, allowing sample regions of 1/2 to 1/3 square degree for global data sets and about 600 meters on a side with 30 m US topography. Topographic fabric appears to be a fundamental characteristic of landforms amenable to quantitative study. It should be included in terrain analysis and classification, and may lead to better estimates for cross-country mobility.

Paper Details

Date Published: 29 January 1999
PDF: 9 pages
Proc. SPIE 3584, 27th AIPR Workshop: Advances in Computer-Assisted Recognition, (29 January 1999); doi: 10.1117/12.339825
Show Author Affiliations
Peter L. Guth, U.S. Naval Academy (United States)

Published in SPIE Proceedings Vol. 3584:
27th AIPR Workshop: Advances in Computer-Assisted Recognition
Robert J. Mericsko, Editor(s)

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