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Open AccessArticle

High-Silica Lava Morphology at Ocean Spreading Ridges: Machine-Learning Seafloor Classification at Alarcon Rise

1
School of the Earth, Ocean and Environment, University of South Carolina, Columbia, SC 29208, USA
2
Institute of Marine Sciences, University of California, Santa Cruz, CA 95064, USA
3
Monterey Bay Aquarium Research Institute, Moss Landing, CA 95039, USA
*
Author to whom correspondence should be addressed.
Present address: Fugro USA Marine, Inc. Geoconsulting Exploration, 6100 Hillcroft Ave, Houston, TX 77081, USA.
Geosciences 2019, 9(6), 245; https://doi.org/10.3390/geosciences9060245
Received: 31 March 2019 / Revised: 26 May 2019 / Accepted: 28 May 2019 / Published: 1 June 2019
(This article belongs to the Special Issue Geological Seafloor Mapping)
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Abstract

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. View Full-Text
Keywords: seafloor classification; lava morphology; remote sensing; machine learning; fuzzy logic; oceanic spreading ridge seafloor classification; lava morphology; remote sensing; machine learning; fuzzy logic; oceanic spreading ridge
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Maschmeyer, C.H.; White, S.M.; Dreyer, B.M.; Clague, D.A. High-Silica Lava Morphology at Ocean Spreading Ridges: Machine-Learning Seafloor Classification at Alarcon Rise. Geosciences 2019, 9, 245.

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