Mangroves of North-western Australia mapped with multi-dimensional space–time remote sensing (ICoAST)
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
Simple
Identification info
- Alternate title
- ICoAST mangrove
- Date (Publication)
- 2023-03-01
Principal investigator
Co-author
- Status
- Completed
Point of contact
- Spatial representation type
- Vector
- Topic category
-
- Biota
Extent
Temporal extent
- Time period
- 2014-01-01 2021-06-30
Resource format
- Title
- ESRI Shapefile
- Date
- Edition
- -
- Global Change Master Directory (GCMD) Earth Science Keywords Version 8.0
- Keywords (Place)
-
- Great Barrier Reef
- Keywords (Theme)
-
- benthic habitat
- mangrove habitat
- remote sensing
- Landsat
Resource specific usage
- Specific usage
- Data supplied for use by the Seamap Australia Project.
Resource constraints
- Classification
- Unclassified
Resource constraints
- Linkage
-
http://i.creativecommons.org/l/by/4.0/88x31.png
License Graphic
- Title
- Creative Commons Attribution 4.0 International License
- Website
-
http://creativecommons.org/licenses/by/4.0/
License Text
- Other constraints
- 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].
- Other constraints
- 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.
- Language
- English
- Character encoding
- UTF8
- Supplemental Information
- 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
Content Information
- Content type
- Physical measurement
- Description
- Appended to original data for styling purposes for the Seamap Australia Project
- Name
-
Benthic habitat
- Name
-
SM_HAB_CLS
Identifier
- Code
- Abundance of biota
Distribution Information
- Distribution format
-
-
ESRI Shapefile
-
ESRI Shapefile
- OnLine resource
-
DATA ACCESS - Geotiff direct download
- OnLine resource
-
seamap:SeamapAus_WA_ICoAST_mangroves_2022
MAP - WA ICoAST Mangroves
- OnLine resource
-
PUBLICATION - Turning the Tide on Mapping Marginal Mangroves with Multi-Dimensional Space–Time Remote Sensing
- OnLine resource
-
ArcGIS online mapping layer for data
Resource 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
- Hierarchy level
- Dataset
- Hierarchy level
- Dataset
Platform
Identifier
- Code
- orbiting satellite
Metadata
- Metadata identifier
-
3b33e731-58e1-4041-9411-cc269cd1cfa3
- Language
- English
- Character encoding
- UTF8
Point of contact
- Parent metadata
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/3b33e731-58e1-4041-9411-cc269cd1cfa3
Point of truth URL of this metadata record
- Date info (Creation)
- 2023-03-01T12:00:00
Metadata standard
- Title
- ISO 19115-3:2018