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AGU 2011 Session: V37: Surveillance of Volcanic Unrest - New Developments in Multi-Disciplinary Monitoring Methods
From: "Charlotte A. Rowe" <char@xxxxxxxx>
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Hello,
We would like to draw your attention to a special session at this fall's
AGU meeting,
V37: Surveillance of Volcanic Unrest - New Developments in
Multi-Disciplinary Monitoring Methods
Sponsor: Volcanology, Geochemistry, and Petrology (V)
Co-Sponsor(s): Natural Hazards (NH), Seismology (S)
Conveners:
Charlotte Rowe (char@xxxxxxxx), Los Alamos National Laboratory
Susanna Falsaperla (susanna.falsaperla@xxxxxxxxxx
), INGV Catania
Seth Moran (smoran@xxxxxxxx), U.S.G.S. Cascades Volcano Observatory
Description: This session details advances in volcano surveillance and
eruption monitoring. This quickly evolving discipline has benefited from
significant advances in computing power, instrumentation technology,
communications and observatory practices. We invite presentations of
innovations on any aspect of this critical chain, from sensor to alarm,
and all the steps between. Data collection and management, advanced signal
processing methods, event identification and classification, machine
learning, automatic decision-making, computer-aided review, and especially
cross-disciplinary implementations are sought to build a comprehensive
look at the state of the art and new methods just around the corner.
Please be advised that the AGU abstract deadline has been moved up
significantly, and submissions will close on ****4 AUGUST****. Thanks,
and we hope to see you there!
Seth Moran (smoran@xxxxxxxx), U.S.G.S. Cascades Volcano Observatory
Description: This session details advances in volcano surveillance and
eruption monitoring. This quickly evolving discipline has benefited from
significant advances in computing power, instrumentation technology,
communications and observatory practices. We invite presentations of
innovations on any aspect of this critical chain, from sensor to alarm,
and all the steps between. Data collection and management, advanced signal
processing methods, event identification and classification, machine
learning, automatic decision-making, computer-aided review, and especially
cross-disciplinary implementations are sought to build a comprehensive
look at the state of the art and new methods just around the corner.
Please be advised that the AGU abstract deadline has been moved up
significantly, and submissions will close on ****4 AUGUST****. Thanks,
and we hope to see you there!
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