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Reef Cover: a coral reef classification to guide global habitat mapping from remote sensing

View ORCID ProfileEmma Kennedy, Chris Roelfsema, Mitchell Lyons, Eva Kovacs, Rodney Borrego-Acevedo, Meredith Roe, Stuart Phinn, Kirk Larsen, Nicholas Murray, Doddy Yuwono, Jeremy Wolff, Paul Tudman
doi: https://doi.org/10.1101/2020.09.10.292243
Emma Kennedy
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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  • For correspondence: e.kennedy1@uq.edu.au
Chris Roelfsema
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Mitchell Lyons
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Eva Kovacs
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Rodney Borrego-Acevedo
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Meredith Roe
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Stuart Phinn
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Kirk Larsen
3Vulcan Inc, Washington 98104, USA
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Nicholas Murray
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
2College of Science and Engineering, James Cook University, Townsville, Queensland, Australia
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Doddy Yuwono
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Jeremy Wolff
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Paul Tudman
1Remote Sensing Research Centre, School of Earth and Environmental Sciences, University of Queensland, Australia
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Abstract

Coral reef management and conservation stand to benefit from improved high-resolution global mapping. Yet classifications employed in large-scale reef mapping to date are typically poorly defined, not shared or region-specific. Here we present Reef Cover, a new coral reef geomorphic zone classification, developed to support global-scale coral reef habitat mapping in a transparent and version-based framework. We developed scalable classes by focusing on attributes that can be observed remotely, but whose membership rules also reflect knowledge of reef formation, growth and functioning. Bridging the divide between earth observation data and geo-ecological knowledge of reefs, Reef Cover maximises the trade-off between applicability at global scales, and relevance and accuracy at local scales. We use the Caroline and Mariana Island chains in the Pacific as a case study to demonstrate use of the classification scheme and its scientific and conservation applications. The primary application of Reef Cover is the Allen Coral Atlas global coral reef mapping project, but the system will support bespoke reef mapping conducted at a variety of spatial scales.

Competing Interest Statement

All coauthors are funded by Vulcan Inc, a US-based philanthropic organisation who funded the research.

Footnotes

  • E-mail: c.roelfsema{at}uq.edu.au

  • https://zenodo.org/record/3833246#.XwRa9G5uKmS

  • https://zenodo.org/record/3953053#.Xxofk4gzZPZ

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted September 11, 2020.
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Reef Cover: a coral reef classification to guide global habitat mapping from remote sensing
Emma Kennedy, Chris Roelfsema, Mitchell Lyons, Eva Kovacs, Rodney Borrego-Acevedo, Meredith Roe, Stuart Phinn, Kirk Larsen, Nicholas Murray, Doddy Yuwono, Jeremy Wolff, Paul Tudman
bioRxiv 2020.09.10.292243; doi: https://doi.org/10.1101/2020.09.10.292243
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Reef Cover: a coral reef classification to guide global habitat mapping from remote sensing
Emma Kennedy, Chris Roelfsema, Mitchell Lyons, Eva Kovacs, Rodney Borrego-Acevedo, Meredith Roe, Stuart Phinn, Kirk Larsen, Nicholas Murray, Doddy Yuwono, Jeremy Wolff, Paul Tudman
bioRxiv 2020.09.10.292243; doi: https://doi.org/10.1101/2020.09.10.292243

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