Geoscience Australia carried out marine surveys in Jervis Bay (NSW) in 2007, 2008 and 2009 (GA303, GA305, GA309, GA312) to map seabed bathymetry and characterise benthic environments through colocated sampling of surface sediments (for textural and biogeochemical analysis) and infauna, observation of benthic habitats using underwater towed video and stills photography, and measurement of ocean tides and wavegenerated currents. Data and samples were acquired using the Defence Science and Technology Organisation (DSTO) Research Vessel Kimbla. Bathymetric mapping, sampling and tide/wave measurement were concentrated in a 3x5 km survey grid (named Darling Road Grid, DRG) within the southern part of the Jervis Bay, incorporating the bay entrance. Additional sampling and stills photography plus bathymetric mapping along transits was undertaken at representative habitat types outside the DRG. jb_s2 is an ArcINFO grid of southern part of Jervis Bay survey area (south2 is part of Darling RD grid) produced from the processed EM3002 bathymetry data using the CARIS HIPS and SIPS software

In May 2013, Geoscience Australia (GA) and the Australian Institute of Marine Science (AIMS) undertook a collaborative seabed mapping survey (GA0340/ SOL5754) on the Leveque Shelf, a distinct geological province within the Browse Basin, offshore Western Australia. The purpose of the survey was to acquire geophysical and biophysical data on seabed environments over a previously identified potential CO2 injection site to better understand the overlying seabed habitats and to assess potential for fluid migration to the seabed. Mapping and sampling was undertaken across six areas using multibeam and single beam echosounders, sub-bottom profilers, sidescan sonar, underwater towed-video, gas sensors, water column profiler, grab samplers, and vibrocorer. Over 1070 km2 of seabed and water column was mapped using the multibeam and single beam echosounder, in water depths ranging between 40 and 120 m. The sub-surface was investigated using the multichannel and the parametric sub-bottom profilers along lines totalling 730 km and 1547 km in length respectively. Specific seabed features were investigated over 44 line km using the sidescan sonar and physically and sampled at 58 stations. Integration of this newly acquired data with existing seismic data will provide new insights into the geology of the Leveque Shelf. This work will contribute to the Australian Government's National CO2 Infrastructure Plan (NCIP) by providing key seabed environmental and geological data to better inform the assessment of the CO2 storage potential in this area of the Browse Basin. This catalogue entry refers to an interpreted geomorphic map, mapped at 1:10 000 scale. Geomorphic mapping was completed using a combination of semi-automated feature extraction and hand digitisation from bathymetry and backscatter grids collected during the survey along with their derivatives and reference to broader scale geomorphic maps (Heap and Harris, 2008).

This resource contains geochemistry data for the Oceanic Shoals Commonwealth Marine Reserve (CMR) in the Timor Sea collected by Geoscience Australia during September and October 2012 on RV Solander (survey GA0339/SOL5650). This datset comprises chlorophyll a, b and c and phaeophytin a concentrations from the upper 2 cm of seabed sediments. The Oceanic Shoals Commonwealth Marine Reserve survey was undertaken as an activity within the Australian Government's National Environmental Research Program Marine Biodiversity Hub and was the key component of Research Theme 4 - Regional Biodiversity Discovery to Support Marine Bioregional Plans. Hub partners involved in the survey included the Australian Institute of Marine Science, Geoscience Australia, the University of Western Australia, Museum Victoria and the Museum and Art Gallery of the Northern Territory. Data acquired during the survey included: multibeam sonar bathymetry and acoustic backscatter; sub-bottom acoustic profiles; physical samples of seabed sediments, infauna and epibenthic biota; towed underwater video and still camera observations of seabed habitats; baited video observations of demersal and pelagic fish, and; oceanographic measurements of the water column from CTD (conductivity, temperature, depth) casts and from deployment of sea surface drifters. Further information on the survey is available in the post-survey report published as Geoscience Australia Record 2013/38: Nichol, S.L., Howard, F.J.F., Kool, J., Stowar, M., Bouchet, P., Radke, L., Siwabessy, J., Przeslawski, R., Picard, K., Alvarez de Glasby, B., Colquhoun, J., Letessier, T. & Heyward, A. 2013. Oceanic Shoals Commonwealth Marine Reserve (Timor Sea) Biodiversity Survey: GA0339/SOL5650 - Post Survey Report. Record 2013/38. Geoscience Australia: Canberra. (GEOCAT #76658).

Imagery collected by still and video cameras is an increasingly important tool for minimal impact, repeatable observations in the marine environment. Data collection from imagery is based on identification, annotation and enumeration of biological subjects and environmental features within an image. For such annotation data to be long-lived and useful beyond their project specific initial purpose, they need to be widely understood. A standardized annotation vocabulary is needed in order to generate regional, national or even global data sets from multiple sources to address broad-scale conservation and ecosystem-based management questions, and also for the development of computer algorithms to automate annotation. This need was addressed, within the Australian context, through the Collaborative and Automated Tools for Analysis of Marine Imagery (CATAMI) project (www.catami.org). The CATAMI classification scheme (CCS) is designed to annotate benthic substrates and biota in marine imagery. It is the first nationally standardised classification based on combinations of coarse-level taxonomy and morphology. The CCS is a flexible, hierarchical classification that bridges the gap between habitat or biotope classifications and taxonomic classifications, allowing for limitations in identifying biological taxa specific to imagery. The CCS is well described, documented, and maintained through web-based data-bases (www.catami.org and http://www.cmar.csiro.au/caab/), and it can be applied across benthic image collection methods, annotation platforms and scoring methods. The CCS was released in 2013 and has already been taken up by on-going Australian marine monitoring programs and by industry environmental consultants. Its incorporation into newly developed on-line image annotation tools further strengthens its continued use and development.

On the Australian margin, submarine canyons have formed along all sides of the continent and are exposed to the potential influence of large-scale ocean currents, including the Leeuwin Current and the East Australian Current. Recognised in marine bioregional plans as potential biodiversity hotspots, many of these canyons sit within the new national network of Commonwealth Marine Reserves. This GIS polygon layer contains 753 submarine canyons along the Australian continental margin and external territorie, mapped from a range of bathymetry datasets. The layer has attributes describing the canyon's geophysical characteristics. The definitions are as follows. SHAPE_Leng: Perimeter (km) SHAPE_Area: Planar area (km2) centreli_L: Centreline length (km); total length of canyon/sub-canyons centreline(s) MBG_Width: Minimum bounding rectangle width (km) MBG_Length: Minimum bounding rectangle length (km) MBG_Orient: Minimum bounding rectangle orientation len_wid_ra: Length to width ratio; a measure of elongation; larger the value the more elongate the canyon border_ind: Border index; a measure of geometric complexity; larger he value the more fractal the canyon compactnes: a measure of compactness; larger the value the more compact the canyon (or the smaller its border) no_branch: Number of sub-canyons head_incis: Head incision (m); incision deph of canyon head head_depth: Head depth (m); water depth of canyon head foot_depth: Foot depth (m); water depth of canyon foot depth_rang: Depth range (m); depth range between canyon head and foot slope_mean: Slope mean; average slope gradients within canyon polygon slope_std: Slope standard deviation; standard deviation of the slope gradients within canyon polygon slope_rang: Slope range; range between maximum and minimum slope gradients within canyon polygon surArea1: Surface area (km2); 3-D surface area of canyon rugosity: Rugosity; roughness of canyon surface volume: Volume (km3); 3-D volume enclosed by the canyon bottom and walls head_x: X coordinate of canyon head; in Asia south Equidistant Conic projection head_y: Y coordinate of canyon head; in Asia south Equidistant Conic projection foot_x: X coordinate of canyon foot; in Asia south Equidistant Conic projection foot_y: Y coordinate of canyon foot; in Asia south Equidistant Conic projection h_f_dist: Head to foot distance (km); euclidian distance between canyon head and foot h_f_slope: head to foot slope; slope gradient between canyon head and foot dist_shelf: Distance to shelf (km); euclidian distance of canyon to shelf break; a distance of zero indicates that canyon touchs or intersects the shelf break or within the continental shelf near_canyo: Nearest canyon (km); euclidian distance to the nearest canyon dist_coast: Distance to coast (km); euclidian distance of canyon to Australian coast focal_var: Focal variety; number of neighbouring canyons within a nominated proximity inci_depth: Incision depth (m); averged depth of canyon area that incises into shelf break; slope-confined canyons have values of zero inci_area: Incision area (km2) ; area of canyon area that incises into shelf break; slope-confined canyons have values of zero slope15: Percentage of slope gradient greater than 15 degree; percentage of canyon area with slope gradients greater than 15 degree sinuosity: a measure of sinuosity; larger the value the more sinuous the canyon shelf_inci: Shelf incision; shlef-incising canyons have value of 1; slope-confined canyons have value of zero dist_river: Distance to revier (km); euclidian distance to the mouth of the nearest permanent river uncertain: Uncertainty; mapping uncertainty assigned to canyon; larger the value the more uncertain the mapping is marine_reg: Marine region; the location of the canyon in one of the marine regions canyon_nam: The name of canyon if known map_region: Map region; the location of canyon in one of the map regions Please refer to Marine Geology 357, 362-383 for details of mapping methods.

The grid was created from the Australian bathymetry and topography grid (2009, version 4). The data represents the degree of aspect of a slope surface (a rectangle of 3 by 3 cells).

The grid was created from the Australian bathymetry and topography grid (2009, version 4). The data represents the degree of slope of an area of seabed (a rectangle of 3 by 3 cells).

The grid was created from the Australian bathymetry and topography grid (2009, version 4). The data represents the difference in elevation between the highest and lowest point within a specified area (a rectangle of 3 by 3 cells). The units are metres.

This dataset provides the spatially continuous data of predicted seabed mud content (sediment fraction finer than 63 µm) expressed as a weight percentage ranging from 0 to 100%, presented in 0.0025 decimal degree (dd) resolution raster grids format and an ascii text file. The dataset covers the north-northwest region of the Australian continental EEZ. This dataset supersedes previous predictions of seabed mud content for the region with demonstrated improvements in accuracy. Accuracy of predictions varies based on density of underlying data and level of seabed complexity. Artefacts occur in this dataset as a result of insufficient samples in relevant areas. This dataset is intended for use at regional scale. The dataset may not be appropriate for use at local scales in areas where sample density is insufficient to detect local variation in sediment properties. To obtain the most accurate interpretation of sediment distribution in these areas, it is recommended that additional samples be collected and interpolations updated.

Geoscience Australia's GEOMACS model was utilised to produce hindcast hourly time series of continental shelf (~20 - 300 m depth) bed shear stress (unit of measure: Pascal, Pa) on a 0.1 degree grid covering the period March 1997 to February 2008 (inclusive). The hindcast data represents the combined contribution to the bed shear stress by waves, tides, wind and densitydriven circulation. Ecological data collected from Torres Strait suggests that bed shear stresses exceeding 0.4 Pa are important in determining the species present (Long, Bode, & Pitcher 1997). Although this data may not be representative of other regions or benthic communities, it has been utilised to calculate two parameters for determining the relationship between shear bed stress and the benthic community. One of the parameters is the total percentage of time the bed shear stress exceeds 0.4 Pa, and this is denoted (Hughes & Harris 2008).