Two vegetation maps (sold separately) - Natural Vegetation (1788) and Post-European Vegetation (1988) reconstruct Australia`s vegetation in the 1780s and the mid-1980s. Areas over 30 000 hectares are shown, plus small areas of significant vegetation such as rainforest. Attribute information includes: growth form of tallest and lower stratum, foliage cover of tallest stratum and dominant floristic types. Data was captured from 1:5 million source material. These maps are also available as free vector GIS data. Product Specifications Coverage: Australia Currency: Compiled mid-1980s Coordinates: Geographical Datum: AGD66 Projection: Simple Conic on two standard parallels 18S and 36S Medium: Printed map (flat and folded); Data - Free online and CD-ROM (fee applies) Forward Program: Under review

One of the components of the FIRE-DST project is investigating fire modelling in the urban and peri-urban interface at the local neighbourhood scale. Each building in the interface will be examined to assess its vulnerability to the approach of a fire for each of ember attack, radiant heat and flame contact. The vulnerability will be dependant on a multitude of factors in the environment including the building construction, roof type, fences and other barriers. The vulnerability will then be used to calculate the expected impact of a fire on the urban area. To be able to model the fire movement and the affect on the built environment there has to be an accurate categorisation of the interface vegetation fuels. In this presentation we will focus on the creation of a 3D model of the neighbourhood scale vegetation and buildings. The neighbourhood scale environment will be created by including individual building information (like building age, wall construction type, roof type and occupancy) from the Geoscience Australia NEXIS database. There also has to be an accurate categorisation of the interface fuels and so specific details of other information such as individual trees, fences and forest will be obtained from high resolution LiDAR. LiDAR will also used to provide both the height and vertical profile of the vegetation in the urban interface. Other geographical information such as roads and a digital elevation model are also required. All this neighbourhood information is then processed to generate a 3D Model of the local environment.

Coastal lagoons are a type of estuary, which has highly variable assemblages of primary producer groups. A classification is derived distinguishing microphytobenthos-dominated, perennial and ephemeral submerged aquatic vegetation-dominated, and nutrient- and light-limited phytoplankton-dominated lagoons. The principle variables required for the classification are bathymetry, light attenuation and initial solar radiation, dissolved inorganic nitrogen concentration and the area covered by ephemeral and perennial submerged aquatic vegetation. Biogeochemical processes and system-wide nutrient dynamics are inherently coupled to the distribution of primary producer groups, so that the classification provides inferences on water quality and ecosystem functioning for different lagoon types and supports the development of management plans and ecological status assessments. Four case studies representing different lagoon types from the temperate south-eastern and south-western coast of Australia are presented. It is demonstrated that the distribution of primary producer groups, and consequently the lagoon type, can be temporarily variable, e.g. as a function of seasonal solar radiation and light attenuation, the water level in a closed lagoon or the degree of eutrophication.

No abstract available

Four data formats are available for download, three vector (e00, mif, shp) and one raster (ecw).

Inland sulfidic soils have recently formed throughout wetlands of the Murray River floodplain associated with increased salinity and river regulation (Lamontagne et al., 2006). Sulfides have the potential to cause widespread environmental degradation both within sulfidic soils and down stream depending on the amount of carbonate available to neutralise acidity (Dent, 1986). Sulfate reduction is facilitated by organic carbon decomposition, however, little is known about the sources of sedimentary organic carbon and carbonate or the process of sulfide accumulation within inland sulfidic wetlands. This investigation uses stable isotopes from organic carbon (13C and 15N), inorganic sulfur (34S) and carbonate (13C and 18O) to elucidate the sources and cycling of sulfur and carbon within sulfidic soils of the Loveday Disposal Basin.

Extended abstract detailing the use of MODIS Enhanced Vegetation Index time series data to map and monitor Groundwater Dependent Ecosystems in the Hat Head National Park.

The White Elephant 1:7,500 regolith-landform map illustrates the distribution of regolith materials and the landforms on which they occur, described using the RTMAP scheme developed by Geoscience Australia

Identification of groundwater-dependent (terrestrial) vegetation, and assessment of the relative importance of different water sources to vegetation dynamics commonly involves detailed ecophysiological studies over a number of seasons or years. However, even when groundwater dependence can be quantified, results are often difficult to upscale beyond the plot scale. Consequently, quicker, more regional mapping approaches have been developed. These new approaches utilise advances in computation geoscience, and remote sensing and airborne geophysical technologies. The Darling River Floodplain, western New South Wales, Australia, was selected as the case study area. This semi-arid landscape is subject to long periods of drought followed by extensive flooding. Despite the episodic availability of surface water resources, two native Eucalyptus species, E. camaldulensis (River Red Gum) and E. largiflorens (Black Box) continue to survive in these conditions. Both species have recognised adaptations, include the ability to utilise groundwater resources at depth. A remote sensing methodology was developed to identify those communities potentially dependent on groundwater resources during the recent millennium drought in Australia.

National vegetation cover derived from: - Values 1, 7, and 8 from the 2007 forests dataset (BRS) - Values 2 and 3 from the NVIS 3.1 dataset (ERIN) - Values 1-6 and 9-11 from the catchment scale land use dataset (as at April 2009, BRS) - Any remaining no data areas filled from the Integrated Vegetation 2008 dataset (BRS) The datasets were resampled to 100 metre grids and projected to Albers equal area if required. The integrated vegetation grid was derived using a conditional statement weighing each input grid in the order listed above. Bureau of Rural Sciences, Canberra are custodians of the dataset.