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

Point data collected from video drops identifying benthic habitats such as seagrass, macroalgae and reef, collected during field work in 2007 to 2011. Used to support the Benthic Habitat Mapping project undertaken by DENR to map the nearshore benthic habitats of South Australia.

This dataset consists of polygons delineating the broad-scale regional marine habitats of selected areas in Western Australia, mostly in existing and proposed marine conservation reserve areas. Habitat mapping was carried out by various organisations, including DPAW, using a range of methodologies over many years. Diverse classifications and habitat descriptions were standardised to the DPaW broad-scale Shallow-water Marine Habitat Classification scheme (SMHC) (Bancroft, 2003) after initial habitat mapping and classification work had been done. Habitat polygons are classified to the broad-scale ecological Community level and where more detailed data exist, local-scale Functional Group level (Bancroft, 2003). Polygons were attributed with habitat class names only, textual descriptions of these classes are provided in this metadata statement and further in Bancroft (2003).

Inshore benthic habitat mapping of the Adelaide Dolphin Sanctuary, 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.

The Seamap Australia National Benthic Habitat Layer (NBHL) is a nationally synthesised database of seafloor habitat data, classified according to the Seamap Australia National Benthic Habitat Classification Scheme (https://vocabs.ardc.edu.au/viewById/129). In generating the Seamap Australia NBHL, datasets from data providers around Australia are collated and centrally hosted by IMAS (UTAS). Through time, some datasets become superseded by newer, more accurate data for the same region (improved data collection or processing methodology). This record aggregates all habitat datasets that have been collated as part of the Seamap Australia project, but are no longer considered the most accurate/up to date habitat for a particular region and have been superseded by another product. The parent record for the Seamap Australia NBHL provides an aggregation point for all "current" habitat datasets: https://metadata.imas.utas.edu.au/geonetwork/srv/eng/catalog.search#/metadata/4739e4b0-4dba-4ec5-b658-02c09f27ab9a

This record describes the benthic assemblage survey data collected as part of the Tasmanian Seamounts Study undertaken by CSIRO Division of Fisheries in January 1997. 34 benthic dredge tows were made on the top, slope and base of 14 seamounts in the survey area, approx. 100 km to the south of Tasmania, using a specially constructed dredge, in water depths ranging from 600m to approx. 2000m. Numerous (>200) invertebrate taxa were recovered representing hydroids, octocorals, polychaetes, bryozoa, bivalve molluscs, cephalopods, barnacles, isopods, decapod crustaceans, crinoids, asteroids, echiuroids, holothurians, hydrozoans, brachiopods, chitons, gastropods, sponges, and other minor groups. The data have been analysed with respect to depth, fishing history (lightly or heavily fished areas), and position on the seamount, and two main community types documented, one dominated by living colonial coral (Solenosmilia variabilis) and one by echinoids (sea urchins). Many of the species found are new records for Australia and a number are new to science. The specimens of select taxa from this survey were re-examined to enable comparison of this survey to two surveys conducted in in the same area in 2006/7 (SS11/2006 & SS02/2007). Identification were upgraded and specimens compared to the new collections by museum experts and integrated into the data. To date (Sept. 2014) we are aware of 20 taxonomic revisions or descriptions that have been published using material from this collection.

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.

This record contains a subset of benthic habitat data from https://doi.org/10.25959/E4S6-GE74 (NESP MaC Project 3.6) rehosted for the purposes of the Seamap Australia collaborative project. Seagrass beds are a dominant marine ecosystem of Tayaritja (the Furneaux Group of Islands) in the north-eastern waters off Tasmania. Historical coarse mapping has indicated extensive beds of Posidonia, Amphibolis, Heterozostera, and Zostera species, potentially comprising some of the largest and deepest seagrass extents found in temperate Australian waters. However, limited data on the distribution and ecological value of these seagrass habitats represents a significant knowledge gap in understanding Australia's wetland natural assets. This project mapped the extent, ecological composition, population structure, and blue carbon value of seagrass beds around Tayaritja, in partnership with the Tasmanian Aboriginal Centre, as part of NESP Marine and Coastal Hub Project 3.6. The study area focused on the coastal waters surrounding Flinders Island in the western Furneaux Group, with mapping extending from the high tide line to the depth limit of reliable optical detection (approximately 30 m), based on analysis of field data and satellite imagery capabilities in the region. This metadata record specifically describes the benthic mapping component of the study. A combination of close-range remote sensing methods was used to map the extent and ecological values of seagrass beds. High-resolution satellite imagery from Sentinel-2 (10 m) sensors, combined with bathymetric LiDAR data and oceanographic variables, was used to map baseline seagrass extent and composition. A field campaign deployed a Benthic Observation Survey System (BOSS) and unBaited Remote Underwater stereo-Video system (stereo-uBRUV) at approximately 400 locations to validate remote sensing outputs, collecting field photo quadrats and rhizome cores. From these data, maps were produced showing the extent and coverage of seagrass, sand, and macroalgae, and where possible, seagrass species composition, subject to water depth and clarity constraints. See the "Lineage" section of this record for full methodology.

This GIS layer is the product of interpreted multibeam acoustic data charaterising the distribution pattern of seafloor habitats at forty sampling sites within the Flinders Commonwealth Marine Reserve. The three classes that were mapped include hard, mixed and soft substrate. Mappin the Flinders CMR is a prerequisite to understanding the relationships between inshore (shelf) and offshore (slope) habitats and therefore representing a key element in developing effective management for the depth strata across the entire CMR. Habitat characterisation provides the underlying spatial framework for developing models of habitat dynamics, trophic interactions and spatial distribution of marine biodiversity.

This dataset corresponds to high resolution (10 m) raster shallow benthic and geomorphic habitat maps for Northern and Western Australia estimated from Sentinel 2 composite imagery from 2018 – 2023. Benthic classes include sand, rubble, rock, seagrass, coral/algae, microalgal mats and light seagrass. Geomorphic classes include deep, sediment slope, shallow lagoon, deep lagoon, inner reef flat, outer reef flat, reef crest, terrestrial reef flat, sheltered reef slope, plateau, back reef slope, small reef and rocky reef. This dataset covers the area from Houtman Abrolhos Islands in Western Australia through to the northwestern side of Cape York, including both offshore and inshore reef systems. Classifications are limited to shallow regions, just below lowest astronomical tide in turbid areas, and to 10 - 15 m in clear water areas. These maps were developed by extending the methods used in the Allen Coral Atlas (https://allencoralatlas.org/methods/) and the development of habitat maps for the Great Barrier Reef (GBR10 GBRMP Geomorphic, https://arcg.is/1jfWaa1, GBR10 GBRMP Benthic, https://arcg.is/1GOD4T1). The maps were produced using a semi-automated classification workflow implemented in Google Earth Engine, combining improved low-tide Sentinel-2 satellite imagery composites created by the Australian Institute of Marine Science (AIMS) (https://doi.org/10.26274/2bfv-e921), with Random Forest machine learning classifiers. The classification approach was regionally tailored across five subregions (Shark Bay, West, Northwest, Gulf, and Offshore) to account for differences in water column optical properties and habitat types. Classifications are aligned with updated reef and shallow sediment outlines produced by AIMS as part of this project, and follow conventions from the Allen Coral Atlas and Great Barrier Reef mapping projects, incorporating additional classes to better represent seagrass environments characteristic of this region. The workflow integrated expert visual interpretation of reference imagery, Object-Based Image Analysis (OBIA) for training data development, and iterative refinement through object-based cleanup rules and regional expert review. These maps are intended to support regional-scale habitat assessment, marine spatial planning, ecosystem modelling, environmental impact assessment, and prioritisation of monitoring efforts. The dataset provides a consistent and scalable baseline for future reef monitoring and contributes directly to the national reef mapping framework. This dataset is delivered in three parts: 1. Geomorphic Map (geomorphic/NW_NESP-MaC-3-17_UQ_Shallow-habitat_Geomorphic_2025.tif) High-resolution spatial classification of coral reef, rocky reef, and shallow sediment geomorphic zones across five subregions. The map features 14 classes: Deep Water, Sediment Slope, Shallow Lagoon, Deep Lagoon, Inner Reef Flat, Outer Reef Flat, Reef Crest, Terrestrial Reef Flat, Sheltered Reef Slope, Reef Slope, Plateau, Back Reef Slope, Small Reef, and Rocky Reef. Classifications were produced at 10 m spatial resolution and refined through three stages of cleanup, including object-based rules and expert-guided manual corrections. Geomorphic maps underwent accuracy assessment using validation points generated from expert-interpreted reference segments.,