This collection contains Earth Observations from space created by Geoscience Australia. This collection specifically is focused on RADAR and Synthetic Aperture Radar (SAR) data. Example products include: ALOS SLC, ENVISAT raw etc.

This collection contains satellite imagery or Earth Observations from space created by Geoscience Australia. Among others, the collection includes data from various satellite sensors including Landsat Thematic Mapper and Multi-Spectral Scanner, Terra and Aqua MODIS.

1. Band ratio: B1/B4 Blue is low abundance, Red is high abundance (potentially includes carbon black (e.g. ash), magnetite, Mn oxides, and sulphides in unoxidised envornments Useful for mapping: (1) magnetite-bearing rocks (e.g. BIF); (2) maghemite gravels; (3) manganese oxides; (4) graphitic shales. Note 1: (1) and (4) above can be evidence for "reduced" rocks when interpreting REDOX gradients. Combine with AlOH group Content (high values) and Composition (high values) products, to find evidence for any invading "oxidised" hydrothermal fluids which may have interacted with reduced rocks evident in the Opaques index product.

Geoscience Australia (GA) has acquired Landsat satellite image data over Australia since 1979, from instruments including the Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS). This data represents raw telemetry which has either been received directly at Geoscience Australia's (GAs) receiving stations (Alice Springs or - formerly - Hobart), or downloaded from the United States Geological Survey Organisation. The data is maintained in raw telemetry format as a baseline to downstream processes. While this data has been used extensively for numerous land and coastal mapping studies, its utility for accurate monitoring of environmental resources has been limited by the processing methods that have been traditionally used to correct for inherent geometric and radiometric distortions in EO imagery. To improve access to Australia's archive of Landsat TM/ETM+/OLI data, several collaborative projects have been undertaken in conjunction with industry, government and academic partners. These projects have enabled implementation of a more integrated approach to image data correction that incorporates normalising models to account for atmospheric effects, BRDF (Bi-directional Reflectance Distribution Function) and topographic shading (Li et al., 2012). The approach has been applied to Landsat TM/ETM+ and OLI imagery to create the surface reflectance products. <b>Value: </b>The Landsat Raw Data Archive is processed and further calibrated to input to development of information products toward an improved understanding of the distribution and status of environmental phenomena. <b>Scope: </b>Data is provided via the US Geological Survey's (USGS) Landsat program, following downlink and recording of the data at Alice Springs Antenna (operated by Geoscience Australia) or downloaded directly from USGS EROS

1. Band ratio: B4/B3 Blue is low abundance, Red is high abundance (1) Exposed iron ore (hematite-goethite). Use in combination with the "Opaques index" to help separate/map dark (a) surface lags (e.g. maghemite gravels) which can be misidentified in visible and false colour imagery; and (b) magnetite in BIF and/or bedded iron ore; and (3) Acid conditions: combine with FeOH Group content to help map jarosite which will have high values in both products. Mapping hematite versus goethite mapping is NOT easily achieved as ASTER's spectral bands were not designed to capture diagnostic iron oxide spectral behaviour. However, some information on visible colour relating in part to differences in hematite and/or goethite content can be obtained using a ratio of B2/B1 especially when this is masked using a B4/B3 to locate those pixels with sufficient iro oxide content.

1. Band ratio: (B10+B12)/B11 Blue is low gypsum content. Red is high gypsum content. Accuracy: Very Low: Strongly complicated by dry vegetation and often inversely correlated with quartz-rich materials. Affected by discontinuous line-striping. Use in combination with FeOH product which is also sensitive to gypsum. Geoscience Applications: Useful for mapping: (1) evaporative environments (e.g. salt lakes) and associated arid aeolian systems (e.g. dunes); (2) acid waters (e.g. from oxidising sulphides) invading carbonate rich materials including around mine environments; and (3) hydrothermal (e.g. volcanic) systems.

1. Band ratio: B11/(B10+B12) Blue is low quartz content Red is high quartz content Geoscience Applications: Use in combination with Silica index to more accurately map "crystalline" quartz rather than poorly ordered silica (e.g. opal), feldspars and compacted clays.

Band ratio: B3/B2 Blue is low content Red is high content Use this image to help interpret the amount of "obscuring/complicating" green vegetation cover.

This is the parent datafile of a dataset that comprises a set of 14+ geoscience products made up of mosaiced ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) scenes across Australia. The individual geoscience products are a combination of bands and band ratios to highlight different mineral groups and parameters including: False colour composite CSIRO Landsat TM Regolith Ratios Green vegetation content Ferric oxide content Ferric oxide composition Ferrous iron index Opaque index AlOH group content AlOH group composition Kaolin group index FeOH group content MgOH group content MgOH group composition Ferrous iron content in MgOH/carbonate Surface mineral group distribution (relative abundance and composition)

1. Band ratio: B2/B1 Blue-cyan is goethite rich, Green is hematite-goethite, Red-yellow is hematite-rich (1) Mapping transported materials (including palaeochannels) characterised by hematite (relative to geothite). Combine with AlOH composition to find co-located areas of hematite and poorly ordered kaolin to map transported materials; and (2) hematite-rish areas in drier conditions (eg above the water table) whereas goethite-rich in wetter conditions (eg at/below the water or areas recently exposed). May also be climate driven.