Data

Habitat map of seagrass cover derived from a supervised moderate-spatial-resolution multi-spectral satellite image, integrated with manual delineation and coincident field data, Moreton Bay, 2004

University of Tasmania, Australia
Data Coordinator
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=5b06aeef-979b-4d09-8e78-0170cbdb8869&rft.title=Habitat map of seagrass cover derived from a supervised moderate-spatial-resolution multi-spectral satellite image, integrated with manual delineation and coincident field data, Moreton Bay, 2004&rft.identifier=http://metadata.imas.utas.edu.au/geonetwork/srv/eng/search?uuid=5b06aeef-979b-4d09-8e78-0170cbdb8869&rft.description=A supervised classification was applied to a Landsat TM5 image. This image was acquired on the 8th August 2004, 15 minutes after low tide. The image classification was applied on areas of clear waters up to three metres depth and for exposed regions of Moreton Bay. Field validation data was collected at 2800 survey sites by UQ, 18 Seagrass-Watch sites and 60 Port of Brisbane Corporation survey sites. GPS referenced field data were used as training areas for the image classification process. For this training the substrate DN signatures were extracted from the Landsat 5 TM image for field survey locations of known substrate cover, enabling a characteristic spectral reflectance signature to be defined for each target. The Landsat TM image, containing only those pixels in water < 3.0m deep, was then subject to minimum distance to means algorithm to group pixels with similar DN signatures (assumed to correspond to the different substrata). This process enabled each pixel to be assigned a label of either seagrass cover (0, 1-25 %, 25-50 %, 50-75 % and 75-100 %). The resulting raster data was then converted into a vector polygon file. Species information was added based on the field data and expert knowledge. Both polygon files were joined by overlaying features of remote sensing files with the EHMP field data to produce an output theme that contains the attributes and full extent of both themes. If polygons of remote sensing were within polygons of field data the assumption was made that the remote sensing polygon was showing more detail and the underlying field polygon was deleted.Maintenance and Update Frequency: notPlannedStatement: Polygon boundaries and attributes derived from field and satellite image data. Field data Polygon boundaries digitised using information from 4900 EHMP survey sites and bathymetry data at scales ranging from 1:300 to 1:5000 depending on the size of the polygon.Statement: The field,'seagrass', provides a description of the visually estimated ground cover of the seagrass and is generally classed as either: • 0-25% cover (sparse) • 25-50% cover (low) • 50-75% cover (medium) • 75-100% cover (dense) The fields,'H_ovalis’, ‘Z_muelleri’, ‘H_spinulosa’, ‘H_uninervis’, ‘C_serrulata’, and ‘S_isoetifolium’ refer to the relative proportion of the seagrass species occurring within each polygon. The field, ‘Source_type’ refers to how the attribute and spatial information was acquired and includes satellite image, snorkel, drop camera held over the side of a stationary vessel and expert knowledge. The field, ‘Source_data’ refers to the organisation / program responsible for data collection and analysis. The field, ‘Polygon’ refers to how the polygon was created. The field, ‘Rs_domain’ refers to the domain for which the image data is analysed (exposed regions or shallow clear waters).&rft.creator=Data Coordinator &rft.date=2021&rft.coverage=westlimit=153; southlimit=-27.78333; eastlimit=153.5; northlimit=-27.08333&rft.coverage=westlimit=153; southlimit=-27.78333; eastlimit=153.5; northlimit=-27.08333&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: Roelfsema, Christiaan M; Phinn, Stuart R; Maxwell, Paul; Udy, Nicola (2015): Habitat map of seagrass cover derived from a supervised moderate-spatial-resolution multi-spectral satellite image, integrated with manual delineation and coincident field data, Moreton Bay, 2004, with link to shapefile. PANGAEA, https://doi.org/10.1594/PANGAEA.846270&rft_rights=This dataset is hosted by the Institute for Marine and Antarctic Studies (IMAS), University of Tasmania, on behalf of the University of Queensland 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=Moreton Bay Marine Park&rft_subject=vegetation&rft_subject=ecology&rft_subject=estuarine&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=Moreton Bay&rft_subject=Environmental Management&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=ENVIRONMENTAL SCIENCE AND MANAGEMENT&rft_subject=Environmental Sciences not elsewhere classified&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=Biotic taxonomic identification&rft_subject=Benthic habitat&rft_subject=cameras&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Open Licence view details
CC-BY

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

WWW:LINK-1.0-http--related

License Text

Cite data as: Roelfsema, Christiaan M; Phinn, Stuart R; Maxwell, Paul; Udy, Nicola (2015): Habitat map of seagrass cover derived from a supervised moderate-spatial-resolution multi-spectral satellite image, integrated with manual delineation and coincident field data, Moreton Bay, 2004, with link to shapefile. PANGAEA, https://doi.org/10.1594/PANGAEA.846270

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

Access:

Open

Brief description

A supervised classification was applied to a Landsat TM5 image. This image was acquired on the 8th August 2004, 15 minutes after low tide. The image classification was applied on areas of clear waters up to three metres depth and for exposed regions of Moreton Bay. Field validation data was collected at 2800 survey sites by UQ, 18 Seagrass-Watch sites and 60 Port of Brisbane Corporation survey sites. GPS referenced field data were used as training areas for the image classification process. For this training the substrate DN signatures were extracted from the Landsat 5 TM image for field survey locations of known substrate cover, enabling a characteristic "spectral reflectance signature" to be defined for each target. The Landsat TM image, containing only those pixels in water < 3.0m deep, was then subject to minimum distance to means algorithm to group pixels with similar DN signatures (assumed to correspond to the different substrata). This process enabled each pixel to be assigned a label of either seagrass cover (0, 1-25 %, 25-50 %, 50-75 % and 75-100 %). The resulting raster data was then converted into a vector polygon file. Species information was added based on the field data and expert knowledge.

Both polygon files were joined by overlaying features of remote sensing files with the EHMP field data to produce an output theme that contains the attributes and full extent of both themes. If polygons of remote sensing were within polygons of field data the assumption was made that the remote sensing polygon was showing more detail and the underlying field polygon was deleted.

Lineage

Maintenance and Update Frequency: notPlanned
Statement: Polygon boundaries and attributes derived from field and satellite image data. Field data Polygon boundaries digitised using information from 4900 EHMP survey sites and bathymetry data at scales ranging from 1:300 to 1:5000 depending on the size of the polygon.
Statement: The field,'seagrass', provides a description of the visually estimated ground cover of the seagrass and is generally classed as either:
• 0-25% cover (sparse)
• 25-50% cover (low)
• 50-75% cover (medium)
• 75-100% cover (dense)

The fields,'H_ovalis’, ‘Z_muelleri’, ‘H_spinulosa’, ‘H_uninervis’, ‘C_serrulata’, and ‘S_isoetifolium’ refer to the relative proportion of the seagrass species occurring within each polygon.
The field, ‘Source_type’ refers to how the attribute and spatial information was acquired and includes satellite image, snorkel, drop camera held over the side of a stationary vessel and expert knowledge.
The field, ‘Source_data’ refers to the organisation / program responsible for data collection and analysis.
The field, ‘Polygon’ refers to how the polygon was created.
The field, ‘Rs_domain’ refers to the domain for which the image data is analysed (exposed regions or shallow clear waters).

This dataset is part of a larger collection

153.5,-27.08333 153.5,-27.78333 153,-27.78333 153,-27.08333 153.5,-27.08333

153.25,-27.43333

text: westlimit=153; southlimit=-27.78333; eastlimit=153.5; northlimit=-27.08333

Other Information
(Original metadata record [PANGAEA catalogue])

doi : https://doi.pangaea.de/10.1594/PANGAEA.846270

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

Identifiers
  • global : 5b06aeef-979b-4d09-8e78-0170cbdb8869