Data

Mangroves of North-western Australia mapped with multi-dimensional space–time remote sensing (ICoAST)

University of Tasmania, Australia

Hickey, Sharyn

Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]

ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://metadata.imas.utas.edu.au/geonetwork/srv/eng/search?uuid=3b33e731-58e1-4041-9411-cc269cd1cfa3&rft.title=Mangroves of North-western Australia mapped with multi-dimensional space–time remote sensing (ICoAST)&rft.identifier=http://metadata.imas.utas.edu.au/geonetwork/srv/eng/search?uuid=3b33e731-58e1-4041-9411-cc269cd1cfa3&rft.description=Mangroves are a globally important ecosystem subject to significant anthropogenic and climate impacts. Tidally submerged forests and those that occur in arid and semi-arid regions are particularly susceptible to sea level rise or are growing at the margins of their their ecophysiological limits. The spatial extent of these types of mangroves over broad scales are typically poorly documented as their structural and environmental characteristics make them difficult to detect using remote sensing models. This study utilised the entire Landsat 8 satellite collection between January 2014 and June 2021. A new cloud-based time-series method was used that accounts for tidal variance in detecting mangrove areas that are periodically inundated and have historically been difficult to detect with traditional remote sensing methods. A habitat area model was derived for remote North-western Australia and detected an additional 32% (76,048 hectares) of mangroves that were previously undocumented. The accuracy of the model was assessed within the distinct geomorphic zones of the region through visual validation from high-resolution imagery. See accompanying report for full methodology: Hickey, S.M.; Radford, B. Turning the Tide on Mapping Marginal Mangroves with Multi-Dimensional Space–Time Remote Sensing. Remote Sens. 2022, 14, x. https://doi.org/10.3390/rs14143365Statement: See accompanying report for full methodology: Hickey, S.M.; Radford, B. Turning the Tide on Mapping Marginal Mangroves with Multi-Dimensional Space–Time Remote Sensing. Remote Sens. 2022, 14, x. https://doi.org/10.3390/rs14143365&rft.creator=Hickey, Sharyn &rft.date=2023&rft.coverage=westlimit=112.7; southlimit=-27.40; eastlimit=129.2; northlimit=-13.60&rft.coverage=westlimit=112.7; southlimit=-27.40; eastlimit=129.2; northlimit=-13.60&rft_rights= http://creativecommons.org/licenses/by/4.0/&rft_rights=http://i.creativecommons.org/l/by/4.0/88x31.png&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Graphic&rft_rights=Creative Commons Attribution 4.0 International License&rft_rights=http://creativecommons.org/international/&rft_rights=WWW:LINK-1.0-http--related&rft_rights=WWW:LINK-1.0-http--related&rft_rights=License Text&rft_rights=Cite data as:Hickey, S & Radford, B (2022). Mangroves of North-western Australia mapped with multi-dimensional space–time remote sensing (ICoAST). University of Western Australia. Data accessed at https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/3b33e731-58e1-4041-9411-cc269cd1cfa3 on [access date].&rft_rights=This dataset is a is hosted by the Institute for Marine and Antarctic Studies (IMAS), University of Tasmania, on behalf of the University of Western Australia (UWA) for the purposes of the Seamap Australia collaborative project.&rft_rights=Creative Commons Attribution 4.0 International License http://creativecommons.org/licenses/by/4.0&rft_subject=biota&rft_subject=MARINE HABITAT&rft_subject=EARTH SCIENCE&rft_subject=BIOSPHERE&rft_subject=AQUATIC ECOSYSTEMS&rft_subject=EARTH SCIENCE | BIOSPHERE | ECOSYSTEMS | MARINE ECOSYSTEMS | COASTAL | MANGROVE SWAMP&rft_subject=EARTH SCIENCE | BIOSPHERE | ECOSYSTEMS | MARINE ECOSYSTEMS | ESTUARY | MANGROVE SWAMP&rft_subject=Great Barrier Reef&rft_subject=Environmental Sciences not elsewhere classified&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=OTHER ENVIRONMENTAL SCIENCES&rft_subject=Marine and Estuarine Ecology (incl. Marine Ichthyology)&rft_subject=BIOLOGICAL SCIENCES&rft_subject=ECOLOGY&rft_subject=orbiting satellite&rft_subject=Abundance of biota&rft_subject=benthic habitat&rft_subject=mangrove habitat&rft_subject=remote sensing&rft_subject=Landsat&rft.type=dataset&rft.language=English Access the data

Access data online via tools
(ArcGIS online mapping layer for da... Access data via landing page
https://metadata.imas....

Cite Saved to MyRDA Save to MyRDA

Licence & Rights:

Open Licence view details

http://creativecommons.org/licenses/by/4.0/

Creative Commons Attribution 4.0 International License
http://creativecommons.org/licenses/by/4.0

http://i.creativecommons.org/l/by/4.0/88x31.png

WWW:LINK-1.0-http--related

License Graphic

Creative Commons Attribution 4.0 International License

http://creativecommons.org/international/

WWW:LINK-1.0-http--related

License Text

Cite data as:Hickey, S & Radford, B (2022). Mangroves of North-western Australia mapped with multi-dimensional space–time remote sensing (ICoAST). University of Western Australia. Data accessed at https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/3b33e731-58e1-4041-9411-cc269cd1cfa3 on [access date].

This dataset is a is hosted by the Institute for Marine and Antarctic Studies (IMAS), University of Tasmania, on behalf of the University of Western Australia (UWA) for the purposes of the Seamap Australia collaborative project.

Access:

Open

Brief description

Mangroves are a globally important ecosystem subject to significant anthropogenic and climate impacts. Tidally submerged forests and those that occur in arid and semi-arid regions are particularly susceptible to sea level rise or are growing at the margins of their their ecophysiological limits. The spatial extent of these types of mangroves over broad scales are typically poorly documented as their structural and environmental characteristics make them difficult to detect using remote sensing models.

This study utilised the entire Landsat 8 satellite collection between January 2014 and June 2021. A new cloud-based time-series method was used that accounts for tidal variance in detecting mangrove areas that are periodically inundated and have historically been difficult to detect with traditional remote sensing methods. A habitat area model was derived for remote North-western Australia and detected an additional 32% (76,048 hectares) of mangroves that were previously undocumented. The accuracy of the model was assessed within the distinct geomorphic zones of the region through visual validation from high-resolution imagery.

See accompanying report for full methodology:
Hickey, S.M.; Radford, B. Turning the Tide on Mapping Marginal Mangroves with Multi-Dimensional Space–Time Remote Sensing. Remote Sens. 2022, 14, x. https://doi.org/10.3390/rs14143365

Lineage

Statement: See accompanying report for full methodology:
Hickey, S.M.; Radford, B. Turning the Tide on Mapping Marginal Mangroves with Multi-Dimensional Space–Time Remote Sensing. Remote Sens. 2022, 14, x. https://doi.org/10.3390/rs14143365

Data time period: 2014-01-01 to 2021-06-30

This dataset is part of a larger collection

Click to explore relationships graph

text: westlimit=112.7; southlimit=-27.40; eastlimit=129.2; northlimit=-13.60

Subjects

User Contributed Tags

Other Information

(DATA ACCESS - Geotiff direct download)

uri : https://data.imas.utas.edu.au/attachments/3b33e731-58e1-4041-9411-cc269cd1cfa3/WA_Mangroves.tif External Link

PUBLICATION - Turning the Tide on Mapping Marginal Mangroves with Multi-Dimensional Space–Time Remote Sensing

doi : https://doi.org/10.3390/rs14143365 DOI Link

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

Identifiers

global : 3b33e731-58e1-4041-9411-cc269cd1cfa3

Similar data you may be interested in: