Reef Cover, a coral reef classification for global habitat mapping from remote sensing
Kennedy, Emma V., Roelfsema, Chris M., Lyons, Mitchell B., Kovacs, Eva M., Borrego-Acevedo, Rodney, Roe, Meredith, Phinn, Stuart R., Larsen, Kirk, Murray, Nicholas J., Yuwono, Doddy, Wolff, Jeremy, and Tudman, Paul (2021) Reef Cover, a coral reef classification for global habitat mapping from remote sensing. Scientific Data, 8. 196.
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Abstract
Coral reef management and conservation stand to benefit from improved high-resolution global mapping. Yet classifications underpinning large-scale reef mapping to date are typically poorly defined, not shared or region-specific, limiting end-users’ ability to interpret outputs. Here we present Reef Cover, a coral reef geomorphic zone classification, developed to support both producers and end-users of global-scale coral reef habitat maps, in a transparent and version-based framework. Scalable classes were created by focusing on attributes that can be observed remotely, but whose membership rules also reflect deep knowledge of reef form 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. Two case studies demonstrate application of the Reef Cover classification scheme and its scientific and conservation benefits: 1) detailed mapping of the Cairns Management Region of the Great Barrier Reef to support management and 2) mapping of the Caroline and Mariana Island chains in the Pacific for conservation purposes.
| Item ID: | 73275 |
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| Item Type: | Article (Research - C1) |
| ISSN: | 2052-4463 |
| Copyright Information: | Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. © The Author(s) 2021, corrected publication 2021. |
| Funders: | Australian Research Council (ARC) |
| Projects and Grants: | ARC Australian Discovery Early Career Award (DE190100101) |
| Date Deposited: | 10 May 2022 22:47 |
| FoR Codes: | 37 EARTH SCIENCES > 3704 Geoinformatics > 370499 Geoinformatics not elsewhere classified @ 75% 37 EARTH SCIENCES > 3709 Physical geography and environmental geoscience > 370901 Geomorphology and earth surface processes @ 25% |
| SEO Codes: | 22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220499 Information systems, technologies and services not elsewhere classified @ 50% 18 ENVIRONMENTAL MANAGEMENT > 1805 Marine systems and management > 180599 Marine systems and management not elsewhere classified @ 50% |
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