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Proceedings Paper

Terrain classification of ladar data over Haitian urban environments using a lower envelope follower and adaptive gradient operator
Author(s): Amy L. Neuenschwander; Melba M. Crawford; Lori A. Magruder; Christopher A. Weed; Richard Cannata; Dale Fried; Robert Knowlton; Richard Heinrichs
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Paper Abstract

In response to the 2010 Haiti earthquake, the ALIRT ladar system was tasked with collecting surveys to support disaster relief efforts. Standard methodologies to classify the ladar data as ground, vegetation, or man-made features failed to produce an accurate representation of the underlying terrain surface. The majority of these methods rely primarily on gradient- based operations that often perform well for areas with low topographic relief, but often fail in areas of high topographic relief or dense urban environments. An alternative approach based on a adaptive lower envelope follower (ALEF) with an adaptive gradient operation for accommodating local slope and roughness was investigated for recovering the ground surface from the ladar data. This technique was successful for classifying terrain in the urban and rural areas of Haiti over which the ALIRT data had been acquired.

Paper Details

Date Published: 4 May 2010
PDF: 9 pages
Proc. SPIE 7684, Laser Radar Technology and Applications XV, 768408 (4 May 2010); doi: 10.1117/12.866033
Show Author Affiliations
Amy L. Neuenschwander, The Univ. of Texas at Austin (United States)
Melba M. Crawford, Purdue Univ. (United States)
Lori A. Magruder, The Univ. of Texas at Austin (United States)
Christopher A. Weed, MIT Lincoln Lab. (United States)
Richard Cannata, Harris Corp. (United States)
Dale Fried, MIT Lincoln Lab. (United States)
Robert Knowlton, MIT Lincoln Lab. (United States)
Richard Heinrichs, MIT Lincoln Lab. (United States)

Published in SPIE Proceedings Vol. 7684:
Laser Radar Technology and Applications XV
Monte D. Turner; Gary W. Kamerman, Editor(s)

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