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A correlation method for volcanic ash detection using hyperspectral infrared measurements
Author(s) -
Clarisse Lieven,
Prata Fred,
Lacour JeanLionel,
Hurtmans Daniel,
Clerbaux Cathy,
Coheur PierreFrançois
Publication year - 2010
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2010gl044828
Subject(s) - volcanic ash , hyperspectral imaging , remote sensing , environmental science , volcanic hazards , volcano , satellite , plume , lidar , panache , meteorology , geology , engineering , seismology , aerospace engineering , physics
Remote satellite detection of airborne volcanic ash is important for mitigating hazards to aviation and for calculating plume altitudes. Infrared sounders are essential for detecting ash, as they can distinguishing aerosol type and can be used day and night. While broadband sensors are mainly used for this purpose, they have inherent limitations. Typically, water and ice can mask volcanic ash, while wind blown dust can yield false detection. High spectral resolution sounders should be able to overcome some of these limitations. However, existing detection methods are not easily applicable to hyperspectral sounders and there is therefore a pressing need for novel techniques. In response, we propose a sensitive and robust volcanic ash detection method for hyperspectral sounders based on correlation coefficients and demonstrate it on IASI observations. We show that the method differentiates ash from clouds and dust. Easy to implement, it could contribute to operational volcanic hazard mitigation.