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.

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.

This project commenced in November 2012 and is intended to provide satellite data and related scientific services to support the Murray-Darling Basin Authority's monitoring of how the condition of riparian vegetation responds to changing river run-off and wetland inundation levels. Under this project, Geoscience Australia started to build a satellite data processing infrastructure; named the 'datacube', as a proof of concept for expected on-going time series analysis applications including historical flood and bathymetry mapping. The work incorporates an automated processing chain for Landsat satellite images from Geoscience Australia's extensive archive, into customised high level intermediate products, including automated ortho-rectification, atmospheric correction, cloud-removal, and mosaicking, and finally into statistics on the spectral and derivative indices (that is, vegetation condition indices or various types) for the summer periods of December-March, each year for the period 2000-2013. These vegetation indices and associate statistics are then used, by the Murray-Darling Basin Authority and its collaborators, as inputs to a mathematical model of vegetation types and their respective conditions within the Murray-Darling Basin.

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.

The combination of anthropogenic activity and climate variability has resulted in changes to hydrologic regimes across the globe. Changes in water availability impact on vegetation structure and function, particularly in semi-arid landscapes. Riparian and floodplain vegetation communities are sensitive to changes to surface-water and groundwater availability in these water-limited landscapes. Remote-sensing multi-temporal methods can be used to detect changes in vegetation at a regional to local scale. In this study, a `best-available pixel' approach was used to represent dry-season, woody-vegetation-canopy characteristics inferred from Normalised Difference Vegetation Index (NDVI). This paper describes a method in which Landsat 5 TM and Landsat 7 ETM+ data from 1987 to 2011 were processed using object-based image-analysis techniques to generate annual minimum NDVI values for vegetation communities in the Lower-Darling floodplain The changes detected in riparian and floodplain canopies over time can then be integrated with other spatial data to identify water-source dependence and infer a relationship between changes to the hydrologic characteristics of specific water sources and vegetation dynamics.

The Integrated Vegetation Cover (2003), hereafter referred to as the IVC03 dataset represents vegetation cover across Australia and was compiled by integrating a number of recent vegetation-related datasets.This dataset was developed to assess and report on the type and extent of native, non-native and non-vegetated cover types across the whole landscape. This dataset has been used to describe vegetation types found in each National Action Plan and Natural Heritage Trust regions across Australia. Data are stored as a raster of 100m resolution and are projected in Albers conic equal-area coordinates.Version 1 incorporates a selection of the latest available vegetation data as at July 2003.Vegetation cover in the IVC03 dataset is described using a 12-class attribute schema that was developed to meet vegetation-related information needs of the Commonwealth Government natural resource management arena.The IVC03 dataset has 12 attribute classes:1Native forests and woodlands 2Native shrublands and heathlands 3Native grasslands and minimally modified pastures4Horticultural trees and shrubs5Perennial crops6Annual crops and highly modified pastures7Plantation (hardwood)8Plantation (softwood/mixed)9Bare10Ephemeral and Permanent Water Features11Built-up99Unknown/not reportable. Five datasets were used as inputs to create the IVC03 dataset.A national ruleset was developed to assign orders of precedence to each attribute value from each input dataset.The ruleset was used to integrate the inputs into a single vegetation cover dataset. The five input datasets were:-Agricultural Land Cover Change (ALCC95);-Forests of Australia 2003 (FOA03);-1996/97 Land Use of Australia, Version 2 (LUA97);-Land Use Mapping at the Catchment Scale (LUMCS03); and-National Vegetation Information System 2000 (NVIS00).

Geoscience Australia (GA) was invited by Murray-Darling Basin Authority (MDBA) in 2010 to participate in an evaluation of the Intermap IFSAR (Interferometric Synthetic Aperture RADAR) data that was acquired as part of the Murray-Darling Basin Information Infrastructure Project Stage 1 (MDBIIP1) in 2009. This evaluation will feed into the business case for Stage 2 of the project. As part of the evaluation GA undertook the following: 1. A comparison of the IFSAR Digital Surface Model (DSM) and Digital Terrain Model (DTM) with a recent LiDAR acquisition, covering approximately 9000Km2 of the Lower Darling Region. It focused on assessment of the data over various land cover and terrain types and identified opportunities and issues with integrating IFSAR with LiDAR. 2. A comparison of the IFSAR Vegetation Canopy Surface (DSM minus DTM) with the Lower Darling LiDAR Canopy Elevation Model (CEM). 3. A comparison between currently mapped man-made and natural water bodies over the Murray-Darling Basin with the IFSAR derived products (water mask). 4. Application of the National Catchment Boundaries (NCBs) methodology to the IFSAR data and comparison with the delineated watersheds from PBS&J (Intermap's sub-contractor). This report outlines the findings of this evaluation based on the 4 items above MDBA requested.

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.

No abstract available

Shows the vegetation of Australia in the mid-1980s. Areas over 30,000 hectares are shown, plus small areas of significant vegetation such as rainforests and croplands. Attribute information includes: growth form of tallest and lower stratum, foliage cover of tallest stratum and dominant floristic types. Data are captured from 1:5 million source material, suitable for GIS applications. The source map is also available for purchase. Product Specifications: Coverage: Australia Currency: Compiled mid-1980s Coordinates: Geographical Datum: AGD66 Projection: Simple Conic on two standard parallels 18S and 36S (printed map only) Format: ArcInfo Export, ArcView Shapefile and MapInfo mid/mif (data only) Medium: Printed map - Paper (flat and folded); Free online and CD-ROM (fee applies) Forward Program: Under review.