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Proceedings Paper

Automatic estimation of volcanic ash plume height using WorldView-2 imagery
Author(s): David McLaren; David R. Thompson; Ashley G. Davies; Magnus T. Gudmundsson; Steve Chien
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Paper Abstract

We explore the use of machine learning, computer vision, and pattern recognition techniques to automatically identify volcanic ash plumes and plume shadows, in WorldView-2 imagery. Using information of the relative position of the sun and spacecraft and terrain information in the form of a digital elevation map, classification, the height of the ash plume can also be inferred. We present the results from applying this approach to six scenes acquired on two separate days in April and May of 2010 of the Eyjafjallajökull eruption in Iceland. These results show rough agreement with ash plume height estimates from visual and radar based measurements.

Paper Details

Date Published: 24 May 2012
PDF: 8 pages
Proc. SPIE 8390, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII, 83901H (24 May 2012); doi: 10.1117/12.919499
Show Author Affiliations
David McLaren, Jet Propulsion Lab. (United States)
David R. Thompson, Jet Propulsion Lab. (United States)
Ashley G. Davies, Jet Propulsion Lab. (United States)
Magnus T. Gudmundsson, Univ. of Iceland (Iceland)
Steve Chien, Jet Propulsion Lab. (United States)


Published in SPIE Proceedings Vol. 8390:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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