The GBR10 benthic habitat type map is the output of a modelling process that combines satellite imagery and other environmental attributes like water depth, slope and wave climate, along with known occurrences of benthic habitat type. The occurrences of benthic habitat type were derived through machine learning applied to geolocated photos of the benthos (>100,000 photos) that were collected along reef flats and reef slopes at various offshore shallow reefs (~100 reefs). The modelling process involves taking those occurrences of benthic habitat at known locations (training data) and using a machine learning model to build a relationship between benthic habitat type and the underlying data layers (imagery, depth, slope, waves). Because the data layers cover the whole Great Barrier Reef, a prediction is then able to be made for benthic habitat across the whole Great Barrier Reef as well. Contextual editing was then used to make changes to the map, based on a set of geomorphology- and ecology-based rules, such as what environment a class can occur in and what classes are able to neighbour each other (object-based rulesets). This map covers the “offshore” or “mid and outer-shelf” reefs of the Great Barrier Reef Marine Park. Some of the occurrences of benthic habitat type are withheld from the process, and used to check how well the mapping performed at the end (validation). The mapping was carried out by the Remote Sensing Research Centre at the University of Queensland. The scientific method for generating the benthic habitat map can be briefly described as: 1. Ingestion of Sentinel-2 satellite image data, bathymetry and wave climate data derived from Sentinel-2 image data, and various additional derived environmental covariates into Google Earth Engine 2. Stacking of the input data sources into a model-ready environment 3. Running a segmentation routine to create image objects 4. Fitting a supervised machine learning model (e.g. random forest) to known occurrences in order to classify segments into benthic classes 5. Application of object based rules using a range of colour, shape texture and relationship rules to modify the class attribution 6. Validation of mapping accuracy and performance This is an snapshot of the GBR10 benthic dataset taken on Jan 2023 for the Seamap Australia project from the GBRMP Reef Knowledge System (https://reefiq.gbrmpa.gov.au/ReefKnowledgeSystem), see also https://gbrmpa.maps.arcgis.com/home/item.html?id=492a87d95e8243728486718e7aed02a8. An updated version of the data may be available from the source provider.

The Marine Futures Project was designed to benchmark the current status of key Western Australian marine ecosystems, based on an improved understanding of the relationship between marine habitats, biodiversity and our use of these values. Approximately 1,500 km2 of seafloor were mapped using hydroacoustics (Reson 8101 Multibeam), and expected benthic habitats "ground-truthed" using towed video transects and baited remote underwater video systems. Both sources of information were then combined in a spatial predictive modelling framework to produce fine-scale habitat maps showing the extent of substrate types, biotic formations, etc. Surveys took place across 9 study areas, including Middle Island, the project's easternmost site located within the Recherche Archipelago. The Recherche Archipelago provides habitats for a diverse range of both terrestrial and marine species, and can be accessed either by vessel from the town of Esperance, or by four wheel drive along the coastal roads adjoining the Cape Arid National Park.

The Marine Futures Project was designed to benchmark the current status of key Western Australian marine ecosystems, based on an improved understanding of the relationship between marine habitats, biodiversity and our use of these values. Approximately 1,500 km2 of seafloor were mapped using hydroacoustics (Reson 8101 Multibeam), and expected benthic habitats "ground-truthed" using towed video transects and baited remote underwater video systems. Both sources of information were then combined in a spatial predictive modelling framework to produce fine-scale habitat maps showing the extent of substrate types, biotic formations, etc. Surveys took place across 9 study areas, including Mount Gardner, a site located just off Two People’s Bay, 30km east of the town of Albany. The area is host to a number of human uses, including recreational and commercial fishing, diving, surfing, recreational boat use and shipping and mining. The marine environment at this location is different to the other three study locations on the south coast, in that it encompasses the protected Two Peoples Bay with seagrass and invertebrate communities and the more exposed rocky and macroalgal reefs around the Mt Gardner peninsula itself.

This data is part of the 2013 report "Synthesis of seagrass mapping studies" conducted by the Water Science Branch of the Department of Water. Surveys were conducted by the WA Department of Water together with Geoscience Australia. The objective of these surveys was to collect baseline data on seagrass composition and distribution in key estuaries of southern and south-western WA. This data was acquired by the ACEAS Seagrass Group as part of the 2013 Australia-wide risk assessment of Seagrass. The datasets making up the Wellstead Estuary seagrass survey data are: WA_Wellstead_SAV_sites - point dataset of species presence/absence and survey methodology at each site. WA_Wellstead_SAV_polygons - polygon dataset showing interpolated percentage cover in polygons derived from site points.

This data is part of the 2013 report "Synthesis of seagrass mapping studies" conducted by the Water Science Branch of the Department of Water. Surveys were conducted by the WA Department of Water together with Geoscience Australia. The objective of these surveys was to collect baseline data on seagrass composition and distribution in key estuaries of southern and south-western WA. This data was acquired by the ACEAS Seagrass Group as part of the 2013 Australia-wide risk assessment of Seagrass. The datasets making up the Beaufort Inlet seagrass survey data are: WA_Beaufort_SAV_sites - point dataset of species presence/absence and survey methodology at each site. WA_Beaufort_SAV_polygons - polygon dataset showing interpolated percentage cover in polygons derived from site points.

This data is part of the 2013 report "Synthesis of seagrass mapping studies" conducted by the Water Science Branch of the Department of Water. Surveys were conducted by the WA Department of Water together with Geoscience Australia. The objective of these surveys was to collect baseline data on seagrass composition and distribution in key estuaries of southern and south-western WA. This data was acquired by the ACEAS Seagrass Group as part of the 2013 Australia-wide risk assessment of Seagrass. The datasets making up the Irwin Inlet seagrass survey data are: WA_Irwin_SAV_polygons - polygon dataset showing interpolated percentage cover of Ruppia spp.