Articles | Volume 8, issue 12
https://doi.org/10.5194/amt-8-5089-2015
https://doi.org/10.5194/amt-8-5089-2015
Research article
 | 
08 Dec 2015
Research article |  | 08 Dec 2015

Automatic volcanic ash detection from MODIS observations using a back-propagation neural network

T. M. Gray and R. Bennartz

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Cited articles

Ackerman, S. A.: Remote sensing aerosols using satellite infrared observations, J. Geophys. Res.-Atmos., 102, 17069–17079, 1997.
Ackerman, S. A., Schreiner, A. J., Schmit, T. J., Woolf, H. M., Li, J., and Pavolonis, M.: Using the GOES Sounder to monitor upper level SO2 from volcanic eruptions, J. Geophys. Res., 113, D14s11, https://doi.org/10.1029/2007jd009622, 2008.
Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227–1230, 1989.
Caldeira, K. G. and Rampino, M. R.: Deccan volcanism, greenhouse warming, and the Cretaceous/Tertiary boundary, Geol. S. Am. S., 247, 117–124, 1990.
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Volcanic ash poses a serious threat to aircraft traffic. A simple neural-network based technique was developed to detect volcanic ash from space using satellite infrared observations. A validation study shows promising results for several individual case studies. Issues remain near the edge of the satellite's field of view as well as in situations where ash is mixed with meteorological clouds.