Brief description
A supervised classification was applied to a Landsat TM5 image. This image was acquired 9:40 am, on the 27th July 2011 (5.14 am low tide at Brisbane Bar). 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 4797 survey sites by UQ. 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: irregular
Statement: Polygon boundaries and attributes derived from field and satellite image data. Field data Polygon boundaries digitised using information from 661 EHMP survey sites, Google Earth Downloaded Image and bathymetry data at scales ranging from 1:5000 depending on the size of the polygon.
Satellite image polygon boundaries and attributes
A supervised classification was applied to a Landsat TM5 image. This image was acquired 9:40 am, on the 27th July 2011(5.14 am low tide at Brisbane Bar). 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 4797 survey sites by UQ. 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.
Satellite image polygon boundaries and attributes
A supervised classification was applied to a Landsat TM5 image. This image was acquired 9:40 am, on the 27th July 2011(5.14 am low tide at Brisbane Bar). 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 4797 survey sites by UQ. 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.
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 field,'species’, refer to 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).
• 0-25% cover (sparse)
• 25-50% cover (low)
• 50-75% cover (medium)
• 75-100% cover (dense)
The field,'species’, refer to 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).
text: westlimit=153; southlimit=-27.78333; eastlimit=153.5; northlimit=-27.08333
Subjects
ANGIOSPERMS (FLOWERING PLANTS) |
AQUATIC ECOSYSTEMS |
BIOLOGICAL CLASSIFICATION |
Biological Sciences |
BIOSPHERE |
Benthic habitat |
Biotic taxonomic identification |
EARTH SCIENCE |
Ecology |
Environmental Science and Management |
Environmental Sciences |
Environmental Management |
Environmental Sciences Not Elsewhere Classified |
MARINE HABITAT |
MONOCOTS |
Marine and Estuarine Ecology (Incl. Marine Ichthyology) |
Moreton Bay |
Moreton Bay Marine Park |
Other Environmental Sciences |
PLANTS |
SEAGRASS |
biota |
cameras |
ecology |
estuarine |
orbiting satellite |
vegetation |
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Other Information
(Original metadata record [PANGAEA catalogue])
doi :
https://doi.pangaea.de/10.1594/PANGAEA.846271
global : 4739e4b0-4dba-4ec5-b658-02c09f27ab9a
Identifiers
- global : d02b6f4e-c8b3-4983-b3c1-0b0d514b4a3d
