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Automatic Estimation of Volcanic Ash Plume Height using WorldView-2 Imagery

NASA NTRS · Conference Paper · 20130009129 · Published 2019-07-12 · Jet Propulsion Laboratory · 5 authors

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Abstract and citation only, verbatim from NASA NTRS; full text lives there. All credit to the authors and Jet Propulsion Laboratory.

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 Eyjafjallajokull eruption in Iceland. These results show rough agreement with ash plume height estimates from visual and radar based measurements.

Authors

  • McLaren, David Jet Propulsion Lab., California Inst. of Tech.
  • Thompson, David R. Jet Propulsion Lab., California Inst. of Tech.
  • Davies, Ashley G. Jet Propulsion Lab., California Inst. of Tech.
  • Gudmundsson, Magnus T. Iceland Univ.
  • Chien, Steve Jet Propulsion Lab., California Inst. of Tech.

Keywords

  • pattern recognition
  • machine learning
  • computer vision
  • sensorweb
  • WorldView-2
  • multispectral
  • volcanic ash

Citation

McLaren, David, Thompson, David R., Davies, Ashley G. , et al. (2019). Automatic Estimation of Volcanic Ash Plume Height using WorldView-2 Imagery. Jet Propulsion Laboratory. NASA NTRS ID 20130009129. https://ntrs.nasa.gov/citations/20130009129 ↗