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Automatic Estimation of Volcanic Ash Plume Height using WorldView-2 ImageryWe 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 Eyjafjallajokull eruption in Iceland. These results show rough agreement with ash plume height estimates from visual and radar based measurements.
Document ID
20130009129
Document Type
Conference Paper
External Source(s)
Authors
McLaren, David (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Thompson, David R. (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Davies, Ashley G. (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Gudmundsson, Magnus T. (Iceland Univ. Reykjavik, Iceland)
Chien, Steve (Jet Propulsion Lab., California Inst. of Tech. Pasadena, CA, United States)
Date Acquired
August 27, 2013
Publication Date
April 23, 2012
Subject Category
Geophysics
Meeting Information
SPIE Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XVIII(Baltimore, MD)
Distribution Limits
Public
Copyright
Other
Keywords
pattern recognition
machine learning
computer vision
sensorweb
WorldView-2
multispectral
volcanic ash