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Title: High-Silica Lava Morphology at Ocean Spreading Ridges: Machine-Learning Seafloor Classification at Alarcon Rise
The oceanic crust consists mostly of basalt, but more evolved compositions may be far more common than previously thought. To aid in distinguishing rhyolite from basaltic lava and help guide sampling and understand spatial distribution, we constructed a classifier using neural networks and fuzzy inference to recognize rhyolite from its lava morphology in sonar data. The Alarcon Rise is ideal to study the relationship between lava flow morphology and composition, because it exhibits a full range of lava compositions in a well-mapped ocean ridge segment. This study shows that the most dramatic geomorphic threshold in submarine lava separates rhyolitic lava from lower-silica compositions. Extremely viscous rhyolite erupts as jagged lobes and lava branches in submarine environments. An automated classification of sonar data is a useful first-order tool to differentiate submarine rhyolite flows from widespread basalts, yielding insights into eruption, emplacement, and architecture of the ocean crust.  more » « less
Award ID(s):
1633936
PAR ID:
10123201
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Geosciences
Volume:
9
Issue:
6
ISSN:
2076-3263
Page Range / eLocation ID:
245
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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