Data

Seagrass meadow extents derived from field to spaceborne earth observation at Green Island (Wunyami), a reef habitat in the Cairns section of the Great Barrier Reef, November 2020

Australian Ocean Data Network
Langlois, Lucas ; McKenzie, Len
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/d3288865-c9d0-4f78-becc-e6bc2b204ef8&rft.title=Seagrass meadow extents derived from field to spaceborne earth observation at Green Island (Wunyami), a reef habitat in the Cairns section of the Great Barrier Reef, November 2020&rft.identifier=https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/d3288865-c9d0-4f78-becc-e6bc2b204ef8&rft.description=Seagrass meadow extent and meadow-scape was mapped using two alternative approaches at Green Island, a reef clear water habitat, in the Cairns section of the Great Barrier Reef, in November 2020. Approach 1 included mapping seagrass meadow-scape using imagery captured during low spring tides with a DJI Mavic 2 Pro UAV at an altitude of 100 m, with a resolution of 2.45cm/pixel. Approach 2 used PlanetScope Dove imagery captured on 05 November 2020 coinciding as close as possible to the field-surveys from 25 to 27 November 2020, with 3.7 m x 3.7 m pixels (nadir viewing) acquired from the PlanetScope archive. This record describes meadow extent data collected using Approach 2 (PlanetScope imagery). View the original metadata record at https://doi.pangaea.de/10.1594/PANGAEA.946605 for the full data collection.Statement: Spatially explicit seagrass maps were created from PlanetScope Dove imagery, and classified using a machine-learning model (Random Forest) coupled with a Boot-strapping process (100 iterations). The final model predictions were then gathered into separate rasters, based on Bootstrap Probability thresholds of 60% and 100%. The final rasters were cleaned using a majority filter algorithm, to eliminate stray pixel predictions using a moving window between 3 and 9 pixels depending on the size of the imagery. All meadows captured in November 2020 are represented. Seagrass distribution and abundance can change seasonally and between years, and users should ensure that they make appropriate enquires to determine whether new information is available on the particular subject matter. Model accuracy is 94.7±0.0004%.&rft.creator=Langlois, Lucas &rft.creator=McKenzie, Len &rft.date=2020&rft.coverage=westlimit=145.965; southlimit=-16.77; eastlimit=145.99; northlimit=-16.754&rft.coverage=westlimit=145.965; southlimit=-16.77; eastlimit=145.99; northlimit=-16.754&rft_rights=Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0/&rft_rights=Langlois, Lucas; McKenzie, Len J (2022): Seagrass meadows derived from field to spaceborne earth observation at Green Island (Wunyami), a reef habitat in the Cairns section of the Great Barrier Reef, November 2020. PANGAEA, https://doi.org/10.1594/PANGAEA.946605&rft_rights=This dataset is a reduced version of the full dataset, available at https://doi.pangaea.de/10.1594/PANGAEA.946605, and is hosted by the Institute for Marine and Antarctic Studies (IMAS), University of Tasmania, on behalf of James Cook University (JCU) for the purposes of the Seamap Australia collaborative project.&rft_subject=biota&rft_subject=MARINE HABITAT&rft_subject=EARTH SCIENCE&rft_subject=BIOSPHERE&rft_subject=AQUATIC ECOSYSTEMS&rft_subject=SEAGRASS&rft_subject=BIOLOGICAL CLASSIFICATION&rft_subject=PLANTS&rft_subject=ANGIOSPERMS (FLOWERING PLANTS)&rft_subject=MONOCOTS&rft_subject=Great Barrier Reef&rft_subject=Environmental Sciences not elsewhere classified&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=OTHER ENVIRONMENTAL SCIENCES&rft_subject=Environmental Management&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=Marine and Estuarine Ecology (incl. Marine Ichthyology)&rft_subject=BIOLOGICAL SCIENCES&rft_subject=ECOLOGY&rft_subject=human&rft_subject=orbiting satellite&rft_subject=Abundance of biota&rft_subject=benthic habitat&rft_subject=deep learning&rft_subject=machine learning&rft_subject=reef&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution 4.0 International License
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Langlois, Lucas; McKenzie, Len J (2022): Seagrass meadows derived from field to spaceborne earth observation at Green Island (Wunyami), a reef habitat in the Cairns section of the Great Barrier Reef, November 2020. PANGAEA, https://doi.org/10.1594/PANGAEA.946605

This dataset is a reduced version of the full dataset, available at https://doi.pangaea.de/10.1594/PANGAEA.946605, and is hosted by the Institute for Marine and Antarctic Studies (IMAS), University of Tasmania, on behalf of James Cook University (JCU) for the purposes of the Seamap Australia collaborative project.

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Brief description

Seagrass meadow extent and meadow-scape was mapped using two alternative approaches at Green Island, a reef clear water habitat, in the Cairns section of the Great Barrier Reef, in November 2020. Approach 1 included mapping seagrass meadow-scape using imagery captured during low spring tides with a DJI Mavic 2 Pro UAV at an altitude of 100 m, with a resolution of 2.45cm/pixel. Approach 2 used PlanetScope Dove imagery captured on 05 November 2020 coinciding as close as possible to the field-surveys from 25 to 27 November 2020, with 3.7 m x 3.7 m pixels (nadir viewing) acquired from the PlanetScope archive. This record describes meadow extent data collected using Approach 2 (PlanetScope imagery). View the original metadata record at https://doi.pangaea.de/10.1594/PANGAEA.946605 for the full data collection.

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Statement: Spatially explicit seagrass maps were created from PlanetScope Dove imagery, and classified using a machine-learning model (Random Forest) coupled with a Boot-strapping process (100 iterations). The final model predictions were then gathered into separate rasters, based on Bootstrap Probability thresholds of 60% and 100%. The final rasters were cleaned using a majority filter algorithm, to eliminate stray pixel predictions using a moving window between 3 and 9 pixels depending on the size of the imagery. All meadows captured in November 2020 are represented. Seagrass distribution and abundance can change seasonally and between years, and users should ensure that they make appropriate enquires to determine whether new information is available on the particular subject matter. Model accuracy is 94.7±0.0004%.

Data time period: 2020-11-05 to 2020-11-27

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145.99,-16.754 145.99,-16.77 145.965,-16.77 145.965,-16.754 145.99,-16.754

145.9775,-16.762

text: westlimit=145.965; southlimit=-16.77; eastlimit=145.99; northlimit=-16.754

Subjects
ANGIOSPERMS (FLOWERING PLANTS) | AQUATIC ECOSYSTEMS | Abundance of biota | BIOLOGICAL CLASSIFICATION | Biological Sciences | BIOSPHERE | EARTH SCIENCE | Ecology | Environmental Science and Management | Environmental Sciences | Environmental Management | Environmental Sciences Not Elsewhere Classified | Great Barrier Reef | MARINE HABITAT | MONOCOTS | Marine and Estuarine Ecology (Incl. Marine Ichthyology) | Other Environmental Sciences | PLANTS | SEAGRASS | benthic habitat | biota | deep learning | human | machine learning | orbiting satellite | reef |

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Other Information
(Original metadata record [PANGAEA catalogue])

doi : https://doi.pangaea.de/10.1594/PANGAEA.946605

global : 4739e4b0-4dba-4ec5-b658-02c09f27ab9a

Identifiers
  • global : d3288865-c9d0-4f78-becc-e6bc2b204ef8