Geoscience Australia has been updating its collection of navigation for marine surveys in Australia. These include original navigation files, the 2003 SNIP navigation files and survey track maps along with survey acquisition reports. The result will be an updated cleansed navigation collection. The collection is based on the standard P190 extended header navigation file which follows the UKOOA standard. Industry standard metadata associated with a seismic survey is preserved. To assist industry, Geoscience Australia is making available its updated version of cleansed navigation. Although the process of updating the navigation data is ongoing and there is still legacy data to check, the navigation data is at point where a significant improvement has been achieved and it is now usable. Users should be aware that this navigation is not final and there may be errors. The KML file can be viewed using a range of applications including Google Earth, NASA WorldWind, ESRI ArcGIS Explorer, Adobe PhotoShop, AutoCAD3D or any other earth browser (geobrowser) that accepts KML formatted data. Alternatively the Shapefiles can be downloaded and viewed using any application that supports shape files.

In early 2014 the RVIB Nathaniel B. Palmer conducted the first ever multidisciplinary study of the Sabrina Coast continental shelf. This area is remote and generally inaccessible, but biological significance is recognised by its initial inclusion within the proposed East Antarctic representative system of Marine Protected Areas. The datasets collected during this voyage allow analysis of the physical habitat parameters and benthic biota through interpretation of bottom camera images, high resolution multibeam bathymetry, sediment properties and oceanographic measurements, with satellite observations of sea ice also providing important environmental context. The suite of environmental and biological datasets provides evidence for a diverse, relatively high biomass continental shelf community that is strongly structured by the physical environment. The distribution of benthic taxa is most closely related ( = 0.592) to seafloor bathymetry, substrate type, latitude and the occurrence of phytodetritus. Phytodetritus accumulation is associated with muddy/sandy substrates, indicating long term sediment focussing in these areas, consistent with evidence of bottom recirculation features. These softer substrates contain relatively high abundances of mobile holothurians and amphipods. Scattered occurrence of dropstones creates habitat heterogeneity at fine-scales. Harder substrates have high abundances of brachiopods, bryozoans, polychaete tubeworms, a range of massive and encrusting sponges and sea whips. Several taxa are found only on areas of hard substrate, yet have a broad distribution across the sites, indicating that the density of dropstones is sufficient for most sessile invertebrates to disperse across the region. The occurrence of dropstones is associated with significant increases in taxa diversity, abundance and percent biological cover, enhancing the overall diversity and biomass of this ecosystem. This study illustrates how multidisciplinary studies can inform understanding of the drivers of benthic ecosystems, providing important constraints for generating realistic ecosystem models and contributing to our understanding of the sensitivity of this community to environmental change.

Acoustic remote sensing is the only effective technique to investigate deep sea bottom. Modern high-frequency multibeam echosounders transmit and receive backscatter signals from hundreds of narrow-angle beams which enlighten small footprints on the seabed. They can produce bathymetry and backscatter data with a spatial resolution around 2% of water depth, which enables us to map the seabed with great detail and accuracy. After calibration, the backscatter intensity is largely controlled by three seabed physical properties: the acoustic impedance contrast (often called hardness), apparent interface roughness (relative to acoustic frequency) and volume inhomogeneity [3, 4, 7]. These seabed physical properties are directly related to sediment grain size characteristics at the sedimentary areas. Studies showed that backscatter intensity had a moderate and positive correlation with sediment mean grain size [1, 3, 6]. Also, backscatter intensity was found to be positively correlated with coarse fractions and inversely correlated with finer fractions [2, 5, 6]. Other sediment grain size properties, especially sorting may also play important roles in the backscatter-sediment relationship [3, 5, 6]. The backscatter-sediment relationship, however, is complex in nature. Research is needed to better understand how acoustic sound interacts with sediment. This study aims to explore this relationship using a set of high quality sediment and multibeam backscatter data, and a robust spatial modelling technique. The co-located sediment and multibeam data were collected from four different areas of Australian margin which represent different sedimentary environments. Five hundred sixty-four sediment grab samples were taken from these survey areas. They were analysed in laboratory using the same procedure to generate grain size properties of %gravel, %sand, %mud, mean grain size, sorting, skewness and kurtosis. The multibeam data were collected using Kongsberg's 300 kHz EM3002 system. The raw multibeam backscatter was processed using the CMST-GA MB Process v8.11.02.1 software developed by Geoscience Australia and the Centre for Marine Science and Technology at Curtin University of Technology. As a result, the backscatter mosaics from incidence angles of 1o to 60o, at an interval of 1o, were generated. The backscatter intensity values from these 60 incidence angles were extracted for all of the sediment samples. The machine learning model Random Forest Decision Tree (RFDT) was used to investigate the backscatter-sediment relationship. The seven sediment grain size properties were the explanatory variables. The response variable was the backscatter intensity from each incidence angle. The model performance was evaluated using 10-fold cross-validation. For incidence angles between 1o and 42o, the RFDT models achieved fairly good performance, with a percentage of variance explained around 70% (Figure 1). The model performance gradually decreased for the outer beam range (incidence angle > 42o). Mud content was consistently identified as the most important explanatory variable to the backscatter strength. The second most important explanatory was usually sediment mean grain size. The RFDT models were also able to generate predicted response curves to quantitatively investigate the relationships between the important explanatory variables and individual response variables. The predicted relationship between %mud and the acoustic backscatter intensity is shown in Figure 2. This indicates a negative but non-linear relationship, with the increase of mud content in the sediment, the backscatter intensity decreases. This finding is consistent with that of previous studies [2, 5, 6]. Fine sediment with high mud content not only is soft (e.g., low impedence contrast) but also has high acoustic penetration (e.g., high attenudation in sediment), which naturally incurs low backcatter return

Australia marine surveys base map

ArcGIS shapefile detailing GA's multibeam bathymetry holdings and coverage.

ArcGIS shapefile detailing GA's multibeam bathymetry holdings and coverage.

ArcGIS shapefile detailing GA's multibeam bathymetry holdings and coverage.

The local Moran I grid calculates local autocorrelation of the bathymetry grid. It indicates local heterogeneity. The large and positive values represent positive autocorrelation or clumped pattern; the large negative values represent negative autocorrelation or checkerboard pattern; the values close to zero represent random local pattern. The grid was created from the bathymetry grid of Darwin Harbour. Please see the metadata of the bathymetry grid for details (GeoCat no: 74915).

Population connectivity research involves investigating the presence, strength and characteristics of spatial and temporal relationships between populations. These data can be used in many different ways: to identify source-sink relationships between populations; to detect critical pathways or keystone habitats; to find natural clusters or biogeographic regions; or to investigate the processes underlying population genetic structure, among others. This information can be of significant value for managers and decision-makers when designing reserve networks, evaluating the potential spread of invasive species. This database represents the first publicly-available collection of national/continental-scale marine connectivity data.

This dataset contains the Sediment sample data collected on Geoscience Australia Survey 273. The survey took place in central Torres Strait during October 2004 on the RV James Kirby. sample collected on this survey include Vibro Cores, Push Cores, Van Veen Grabs and suspended soilds from water samples. This dataset has been processed and archived within Geoscience Australia's Seabed Mapping and Characteristion Project in Canberra. Data can been accessed via the Geoscience Australia Marine Samples (MARS) database. Additional information regarding this dataset is contained in the Survey report. Biophysical Processes in theTorres Strait Marine Esosystem II. Survey Results and review of activites in responce to CRC objectives. Geoscience Australia Record 2006/10.