Amy L. Neuenschwander,1 Melba M. Crawford,2 Lori A. Magruder,1 Christopher A. Weed,3 Richard Cannata,4 Dale Fried,3 Robert Knowlton,3 Richard Heinrichs3
1The Univ. of Texas at Austin (United States) 2Purdue Univ. (United States) 3MIT Lincoln Lab. (United States) 4Harris Corp. (United States)
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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.
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Amy L. Neuenschwander, Melba M. Crawford, Lori A. Magruder, Christopher A. Weed, Richard Cannata, Dale Fried, Robert Knowlton, Richard Heinrichs, "Terrain classification of ladar data over Haitian urban environments using a lower envelope follower and adaptive gradient operator," Proc. SPIE 7684, Laser Radar Technology and Applications XV, 768408 (4 May 2010); https://doi.org/10.1117/12.866033