In many areas of the world, vegetation dynamics in semi-arid floodplain environments have been seriously impacted by increased river regulation and groundwater use. With increases in regulation along many rivers in the Murray-Darling Basin, flood volume, seasonality and frequency have changed which has in turn affected the condition and distribution of vegetation. Floodplain vegetation can be degraded from both too much and too little water due to regulation. Over-regulation and increased use of groundwater in these landscapes can exacerbate the effects related to natural climate variability. Prolonged flooding of woody plants has been found to induce a number of physiological disturbances such as early stomatal closure and inhibition of photosynthesis. However, drought conditions can also result in leaf biomass reduction and sapwood area decline. Depending on the species, different inundation and drought tolerances are observed. Identification of groundwater-dependent terrestrial vegetation, and assessment of the relative importance of different water sources to vegetation dynamics, typically requires detailed ecophysiological studies over a number of seasons or years as shown in Chowilla, New South Wales [] and Swan Coastal Plain, Western Australia []. However, even when groundwater dependence can be quantified, results are often difficult to upscale beyond the plot scale. Quicker, more regional approaches to mapping groundwater-dependent vegetation have consequently evolved with technological advancements in remote sensing techniques. Such an approach was used in this study. LiDAR canopy digital elevation model (CDEM) and foliage projected cover (FPC) data were combined with Landsat imagery in order to characterise the spatial and temporal behaviour of woody vegetation in the Lower Darling Floodplain, New South Wales. The multi-temporal dynamics of the woody vegetation were then compared to the estimated availability of different water sources in order to better understand water requirements.

New ASTER GIS products in the Gawler-Curnamona Geoscience Australia, in collaboration with CSIRO and PIRSA are releasing a suite of 14 new ASTER mosaiced products for a significant part of the Gawler-Curnamona region. About 110 ASTER scenes have been mosaiced and processed into geoscience products that can be quickly and easily integrated with other datasets in a GIS. The products have been pre-processed and calibrated with available HyMap data and provide basic mineral group information such as Ferric Oxide abundance, AlOH group distribution as well as mosaiced and levelled false colour and regolith ratio images. These images, along with accompany notes are available for free ftp download online at: ftp://ftp.arrc.csiro.au/NGMM/Gawler-Curnamona ASTER Project/

Soil mapping at the local- (paddock), to continental-scale, may be improved through remote hyperspectral imaging of surface mineralogy. This opportunity is demonstrated for the semiarid Tick Hill test site (20 km2) near Mount Isa in western Queensland. The study of this test site is part of a larger Queensland government initiative involving the public delivery of 25,000 km2 of processed airborne hyperspectral mineral maps at 4.5 m pixel resolution to the mineral exploration industry. Some of the mineral maps derived from hyperspectral imagery for the Tick Hill area include the abundances and/or physicochemistries (chemical composition and crystal disorder) of dioctahedral clays (kaolin, illite-muscovite and Al smectite, both montmorillonite and beidellite), ferric/ferrous minerals (hematite/goethite, Fe2+-bearing silicates/carbonates) and hydrated silica (opal) as well as soil water (bound and unbound) and green and dry (cellulose/lignin) vegetation. Validation of these hyperspectral mineral products is based on field soil sampling and laboratory analyses (spectral reflectance, X-ray diffraction, scanning electron microscope and electron backscatter). The mineral maps show more detailed information regarding the surface composition compared with the published soil and geology (1:100,000 scale) maps and airborne radiometric imagery (collected at 200 m line spacing). This mineral information can be used to improve the published soil mapping but also has the potential to provide quantitative information suitable for soil and water catchment modeling and monitoring.

Extensive benefits and tools can be gained for mineral explorers, land-users and government and university researchers using new spectral data and processing techniques. Improved methods were produced as part of a large multi-agency project focusing on the world-class Mt Isa mineral province in Australia. New approaches for ASTER calibration using high-resolution HyMap imagery through to testing for compensation for atmospheric residuals, lichen and other vegetation cover effects have been included in this study. . Specialised data processing software capable of calibrating and processing terabytes of multi-scene imagery and a new approach to delivery of products, were developed to improve non-specialist user interpretation and comparison with other datasets within a GIS. Developments in processing and detailed reporting of methodology, accuracies and applications can make spectral data a more functional and valuable tool for users of remote sensing data. A highly-calibrated approach to data processing, using PIMA ground samples to validate the HyMap, and then calibrating the ASTER data with the HyMap, allows products to have more detailed reliable accuracies and integration with other data, such as geophysical and regolith information in a GIS package, means new assessments and interpretations can be made in mapping and characterising materials at the surface. Previously undiscovered or masked surface expression of underlying materials, such as ore-deposits, can also be identified using these methods. Maps and products made for this project, covering some ~150 ASTER scenes and over 200 HyMap flight-lines, provide a ready-to-use tool that aids explorers in identifying and mapping unconsolidated regolith material and underlying bedrock and alteration mineralogy.

Removing the topographic effect from satellite images is a very important step in order to obtain comparable surface reflectance in mountainous areas and to use the images for different purposes on the same spectral base. The most common method of normalising for the topographic effect is by using a Digital Surface Model (DSM) and / or a Digital Elevation Model (DEM). However, the accuracy of the correction depends on the accuracy, scale and spatial resolution of DSM data as well as the co-registration between the DSM and satellite images. A physics based BRDF and atmospheric correction model in conjunction with a 1-second SRTM (Shuttle Radar Topographic Mission) derived DSM product released by Geoscience Australia in 2010 were used to conduct the analysis reported in this paper. The results show that artefacts in the DSM data can cause significant local errors in the correction. For some areas, false shadow and over corrected surface reflectance factors have been observed. In other areas, the algorithm is unable to detect shadow or retrieve an accurate surface reflectance factor in the slopes away from the sun. The accuracy of co-registration between satellite images and DSM data is crucial for effective topographic correction. A mis-registration error of one or two pixels can lead to large error of retrieved surface reflectance factors in the gully and ridge areas (retrieved reflectance factors can change from 0.3 to 0.5 or more). Therefore, accurate registrations for both satellite images and DSM data are necessary to ensure the accuracy of the correction. Using low resolution DSM data in conjunction with high resolution satellite images can fail to correct some significant terrain effects. A DSM resolution appropriate to the scale of the resolution of satellite image is needed for the best results.

Large areas of prospective North and North-East Queensland have been surveyed by airborne hyperspectral sensor, HyMap, and airborne geophysics as part of the 'Smart' exploration initiative by the Geological Survey of Queensland. In particular, 25000 km2 of hyperspectral mineral and compositional map products, at 4.5 m spatial resolution, have been generated and made available via the internet. In addition, more than 130 ASTER scenes were processed and merged to produce broad scale mapping of mineral groups (Thomas et al, 2008). Province-scale, accurate maps of mineral abundances and minerals chemistries were generated for North Queensland as a result of a 2 year project starting in July 2006 which involved CSIRO Exploration and Mining, the Geological Survey of Queensland (GSQ), Geoscience Australia, James Cook University, and Curtin University. Airborne radiometric data acquired over the same North Queensland Mt Isa - Cloncurry areas as the hyperspectral surveys, had been acquired at flight line spacing of 200 metre. Such geophysical radiometric data provides a useful opportunity to compare the mineral mapping potential of both techniques, for a wide range of geological and vegetated environments. In this study, examples are described of soil mapping within the Tick Hill area, and geological / exploration mapping within the Mt Henry and Suicide Ridge prospects of North Queensland.

Continent-scale digital maps of mineral information of the Earth's land surface are now achievable using geoscience-tuned remote sensing systems. Multispectral ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) data and the derived mineral information provide the opportunity for characterization of geological and soil processes including the nature of the regolith (weathered) cover and alteration footprints of hydrothermal ore deposits [1,2]. This paper describes work from the Western Australian (WA) Centre of Excellence for 3D Mineral Mapping, which is part of CSIRO's Minerals Down Under Flagship and supported by Geoscience Australia and other Australian geosurveys, to generate a series of ASTER mineral group maps (both content and composition) for the whole Australian continent at a 30 m pixel resolution.. The input ASTER L1B radiance-at-sensor data were provided by ERSDAC (Japan), NASA and the USGS. These data were corrected for instrument, illumination, atmospheric and geometric effects. About 4000 ASTER scenes from an archive of >30,000 scenes were selected to generate the continent-scale ASTER map and Hyperion scenes were used for reduction and validation of the cross-calibrated ASTER mosaic to reflectance. Band ratios [2] were applied as base algorithms and masked to remove complicating effects, such as green vegetation, clouds and deep shadow. Types of generated geoscience products include (1) mineral group content maps based on continuum-band depths (e.g. Al-OH group content mapping Al-OH clays like muscovite, kaolinite and montmorillonite) and (2) mineral group composition maps (e.g. Al-OH group composition ranging from Si-rich white mica through to well ordered kaolinite) based on ratios but masked using the relevant content products.

Includes copy of AGSO Record 1997/20

Legacy product - no abstract available

No abstract available