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.

The developed method of long-strip adjustment for orientation and georeferencing of PRISM imagery is based on the merging of successive images within a single satellite pass into what amounts to a single image covering the entire orbit segment. Metadata for each separate scene is merged to produce a single, continuous set of orbit and attitude parameters, such that the entire strip of tens of images can be treated as a single image, even though the separate scenes are not actually merged. Within the strip adjustment, the orbit parameters are refined based on the provision of GCPs at each end of the strip. A minimum of four GCPs is required to achieve 1-pixel georeferencing accuracy, even for strip lengths of 1000 km or more. The merging of orbit data results in a very considerable reduction in both the number of unknown orientation parameters and the number of required GCPs in the sensor orientation adjustment. Indeed the number of required GCPs can drop from well over 100 to only 4-6 for a 50-image orbit segment. Moreover, unlike in traditional photogrammetric strip adjustment, there is no need for tie-point measurements between images. Once the adjusted orbit parameters are obtained, the georeferencing and orthorectification process can revert to a fully automatic image-by-image computation. Following orthorectification, a final mosaicking is undertaken to produce the reference image, namely the AGRI. AGRI was needed because imagery from emerging new satellites can be automatically registered to it, consistently and accurately. AGRI was made possible by the developed long-strip adjustment approach to satellite image georeferencing. This technique, implemented in Barista, rendered the project feasible in time, logistics and cost. It reduced the image registration problem from correction of almost 10,000 scenes to correction of just 105 orbit segments. Moreover, the number of required GCPs was reduced from more than 30,000 to less than 1000.

This class set of 10 Discovering Remote Sensing student manuals is designed to be used in conjunction with the Discovering Remote Sensing kit, catalogue item 30832. Each student manual contains; - background text covering concepts of resolution, scale, radiation, spectral bands, reflectance, false colour and much more. Images used in the kit use platforms such as NOAA, Landsat TM and SPOT. The manuals also include an activity based around Geoscience Australia's web-based satellite image processor. - twelve reproducible student activities - one set of five A4 image cards used with the student activities. Please note - the student examination and answers to the student activities are not included in the student manuals. These are available in item 30832. Ten sets of 5 images cards are also available in a bulk set for purchase separately (catalogue item 30842). Suitable for secondary levels Years 8-12

Legacy product - no abstract available

The Pine Creek GIS package has been prepared jointly by AGSO and the Northern Territory Survey for release in both digital and hard copy (atlas) formats. Based on the 1:500 000 geological map of the Pine Creek Geosyncline (2nd edition) published by BMR in 1984, the GIS has been supplemented where possible by recently acquired data from mapping in the Litchfield, Katherine, and South Alligator areas. The aim of this project was to bring together almost 45 years of regional mapping projects by both organisations by integrating existing hard copy geological maps and other relevant geoscientific data into a digital Metallogenic Geographic Information System (GIS).

This product includes the remote sensing information booklet + student activities + one set of five A4 image cards. Discovering Remote Sensing - an introduction does not contain any overhead projection images. Suitable for secondary Years 8-12.

This two year collaborative project was established in July 2006 with the overall aim of developing, validating, evaluating and delivering a suite of publicly available, pre-competitive mineral mapping products from airborne HyMap hyperspectral imagery and satellite multispectral ASTER imagery. Moreover, it was important to establish whether these mineral maps would complement other precompetitive geological and geophysical data and provide valuable new information regards enhanced mineral exploration for industry. A mineral systems approach was used to appreciate the value of these mineral maps for exploration. That is, unlocking the value from these mineral maps is not simply by looking for the red bulls-eyes. Instead, mineral products need to be selected on the basis of critical parameters, such as what minerals are expected to develop as fluids migrate from source rocks to depositional sites and then into outflow zones with each associated with different physicochemical conditions (e.g. metasomatic metal budget, nature of the fluids, water-rock ratios, lithostatic pressure, pore fluid pressure, REDOX, pH, and temperature). One of the other key messages is to be able to recognise mineral chemical gradients as well as anomalous cross-cutting effects. These principles were tested using a number of case histories including, (1) the Starra iron oxide Cu-Au deposit; (2) the Mount Isa Pb-Zn-Ag and Cu deposits; and (3) Century Zn, all within the Mount Isa Block. These showed that the interpreted mineral alteration footprints of these mineral systems can be traced 10-15 km away from the metal deposition sites. In summary this project has shown that it is possible to generate accurate, large area mineral maps that provide new information about mineral system footprints not seen in other precompetitive geoscience data and that the vision of a mineral map of Australia is achievable and valuable.

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.

ASTER Geoscience GIS products now available for the Gawler-Curnamona region in South Australia (AUSGEOnews title) 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/

Londonderry - Drysdale Potassium (red), Thorium (green), Uranium (blue) colour composite