The spatial extent of seabed habitat data collected & collated for New South Wales Coastal waters. The HABMAP program has provided fine scale benthic habitat information for NSW State Waters. Targeted areas use surveyed bathymetric and backscatter layers for Habitat classification. Data is collected using a pole mounted Geoswath 125KHZ Interferometric sidescan sonar system. Data are tide, sound velocity and motion corrected and are accurate to the sub-metre level (DGPS). The shape file presented here is a collation of the spatial extent of the area of mapped sea floor habitat data from a variety of sources including; the OEH HABMAP program, digitised from aerial photographs and plotted external high resolution bathymetric data as well as historical habitat data.

Inshore benthic habitat mapping of the Adelaide Mount Lofty Ranges (AMLR), Yorke Peninsula, Eyre Peninsula, Upper Spencer Gulf, Upper Gulf St Vincent, South East and Kangaroo Island as part of a wider DEWNR project to map specific areas of the South Australian inshore environments Habitat boundaries were interpreted from underwater features discernable on ortho-rectified aerial photographs. The data for the Upper Gulf St Vincent and Upper Spencer Gulf were captured between 2005 and 2007. AMLR data was captured between 2008 and 2009. South East data was captured between 2009 and 2010. Field observations and underwater video footage was used to capture the Upper Spencer Gulf and Upper Gulf St Vincent data. The AMLR data was captured from field observations, underwater video footage, acoustic mapping and sidescan sonar. The data sets were combined as part of a DENR Statewide project. Additional data was captured on Kangaroo Island during 2013 which included field observations and Underwater video footage. This data was added by regional staff using an adapted data schema that now includes species specific information.

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.

The Seamap Australia spatial data layer is a nationally synthesised data product of seafloor marine habitat data. Australian continental shelf benthic habitat layers in GIS format were collected from various stakeholders around the country. Through compiling all of these data sets, we established a controlled vocabulary, reviewed by ANDS and external independent assessors, to produce a national classification of marine habitats. This national marine habitat classification scheme complements work undertaken by the National Environmental Science Program (NESP) Marine Biodiversity Hub (Theme D). The Seamap Australia product is of national importance and highlights the diversity of benthic habitats around our marine estate. This is the first edition of a seafloor marine habitat data layer that seamlessly brings together data from each of Australia’s state and territory marine habitat databases. Seamap Australia is a constantly evolving product as we continuously improve our skills in standardising, collating and sharing marine spatial data. This record describes a static version of the Seamap Australia national data layer as of 28/11/2018. The most current version of the data is available from the Seamap Australia website [http://seamapaustralia.org/map]. We envisage that the 'live' product will be constantly developed and updated as future surveys continue to improve our knowledge of our vast marine estate.

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.

The SeaMap Tasmania project undertook mapping of seafloor habitats across the nearshore Tasmanian coastline (0-40 m) - the first state to compile a statewide asssimilated benthic habitat dataset. This initiative comprised of collating aerial photography (from archives), acoustic mapping, and conducting underwater video surveys and field-based visual observations. From this, 1:25,0000 scale habitat maps were created for shallow coastal water to within 1.5 km of the coastline (or 40m depth, which ever was arrived at first). Depth information was collected via acoustic methods and used to discriminate seafloor habitat type, in combination with scanned aerial photographs and towed video transects providing ground-truthing information. See 'Lineage' section of this record for full methodology and data dictionary. This data is also available via the Seamap Australia National Benthic Habitat Layer - a nationally consolidated benthic habitat map. https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/4739e4b0-4dba-4ec5-b658-02c09f27ab9a

This dataset summarises subtidal benthic surveys in Yanyuwa Sea Country into 3 GIS shapefiles. (1) A point (site) shapefile describes seagrass presence/absence at 849 subtidal sites surveyed by vessel. (2) The meadow shapefile describes attributes of 46 subtidal seagrass meadows. (3) The interpolation shapefile describes variation in subtidal seagrass biomass across the seagrass meadows. This project is a partnership between the li-Anthawirriyarra rangers, Charles Darwin University, James Cook University, and Mabunji Aboriginal Resource Indigenous Corporation to map the subtidal habitats of the Yanyuwa Indigenous Protected Area (IPA), an area of profound importance to the Marra and Yanyuwa people and to the marine ecosystem of the Gulf of Carpentaria. Benthic habitat maps of Yanyuwa Country were produced, with a focus on seagrass. This project was funded by the NT Government Aboriginal Ranger Grant Program. The sampling methods used to study, describe and monitor seagrass meadows were developed by TropWATER and tailored to the location and habitat surveyed; these are described in detail in the relevant publications (https://research.jcu.edu.au/tropwater). Geographic Information System (GIS) All survey data were entered into a Geographic Information System (GIS) using ArcGIS 10.8. Rectified colour satellite imagery of Yanyuwa Sea Country (Source: Allen Coral Atlas and ESRI), field notes and aerial photographs taken from the helicopter during surveys were used to identify geographical features, such as reef tops, channels and deep-water drop-offs, to assist in determining seagrass meadow boundaries. Three GIS layers were created to describe spatial features of the region: a site layer, seagrass meadow layer, and a seagrass biomass interpolation layer. Site layer This layer contains information on data collected at assessment sites. This layer includes: 1. Temporal survey details – Survey date; 2. Spatial position - Latitude/longitude; 3. Survey location; 4. Seagrass information including presence/absence of seagrass, above-ground biomass (total and for each species), percent cover of seagrass at each site; 5. Benthic macro-invertebrate information including the percent cover of hard coral, soft coral, sponges and other benthic macro invertebrates (e.g. ascidian, clam) at a site; 6. Algae information including percent cover of algae at a site and percent contribution of algae functional groups to algae cover at a site; 7. Open substrate – the percent cover of the site that had no flora or habitat forming benthic invertebrates present; 8. Dominant sediment type - Sediment type based on grain size visual assessment or deck descriptions. 9. Survey method and vessel; 10. Relevant comments and presence/absence of megafauna and animals of interest (dugong, turtle, dolphin); and 11. Data custodians. Seagrass meadow layer Seagrass presence/absence site data, mapping sites, field notes, and satellite imagery were used to construct meadow boundaries in ArcGIS®. The meadow (polygon) layer provides summary information for all sites within each seagrass meadow, including: 1. Temporal survey details – Survey month and year as individual columns and the survey date (the date range the survey took place); 2. Spatial survey details – Survey location, meadow identification number that identifies the reef name and the meadow number. This allows individual meadows to be compared among years; 3. Survey method; 4. Meadow depth for subtidal meadows; 5. Species presence – a list of the seagrass species in the meadow; 6. Meadow density – Seagrass meadows were classified as light, moderate, dense based on the mean biomass of the dominant species within the meadow. For example, a Thalassia hemprichii dominated meadow would be classed as “light” if the mean meadow biomass was <5 grams dry weight m-2 (g DW m-2), and “dense” if mean meadow biomass was >25 g DW m-2. 7. Meadow community type – Seagrass meadows were classified into community types according to

The Victorian seabed habitat map documents the distribution of broad benthic habitat types in Victorian Coastal Waters to the State’s 3 nautical mile jurisdictional limit. The map was created using a top-down modelling process whereby habitat descriptors were assigned using seafloor structure and biological information derived from multibeam sonar (Victorian Marine Habitat Mapping Project), bathymetric LiDAR (Future Coasts program) and observations from underwater video. Identification of benthic biota, to the lowest discernible taxonomic level, and substrate characteristics were recorded according to the Victorian Towed Video Classification scheme (Ierodiaconou et al. 2007).