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Proceedings Paper

Terrain categorization using LIDAR and multispectral data
Author(s): Angela M. Puetz; R. C. Olsen; Michael A. Helt
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Paper Abstract

LIDAR data taken over the Elkhorn Slough region in central California were analyzed for terrain classification. Data were collected on April 12th, 2005 over a 10 km × 20 km region that is mixed use agriculture and wetlands. LIDAR temporal information (elevation values), intensity of returned light and distribution of point returns (in both vertical and spatial dimensions) were used to distinguish land-cover types. Terrain classification was accomplished using LIDAR data alone, multi-spectral QuickBird data alone and a combination of the two data-types. Results are compared to significant ground truth information.

Paper Details

Date Published: 14 May 2007
PDF: 6 pages
Proc. SPIE 6565, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII, 65650V (14 May 2007); doi: 10.1117/12.719885
Show Author Affiliations
Angela M. Puetz, Naval Postgraduate School (United States)
R. C. Olsen, Naval Postgraduate School (United States)
Michael A. Helt, Naval Postgraduate School (United States)


Published in SPIE Proceedings Vol. 6565:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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