<p>This mangrove canopy cover product provides valuable information about the extent and canopy density of mangroves for each year between 1987 and 2018 for the entire Australian coastline. </p> <p>The canopy cover classes are 20-50% (pale green), 50-80% (mid green), 80-100% (dark green). The product consists of a sequence (one per year) of 25-metre resolution maps that are generated by analysing the Landsat fractional cover developed by the Joint Remote Sensing Research Program (https://doi.org/10.6084/m9.figshare.94250.v1) and the Global Mangrove Watch layers developed by the Japanese Aerospace Exploration Agency (https://doi.org/10.1071/MF13177). </p> <p>This product can be cited as Lymburner, L., Bunting, P., Lucas, R., Scarth, P., Alam, I., Phillips, C., Ticehurst, C. and Held, A. (2018). Mapping the multi-decadal mangrove dynamics of the Australian coastline. See https://www.sciencedirect.com/science/article/pii/S0034425719301890. </p>

1. Band ratio: B5/B7 Blue is well ordered kaolinite, Al-rich muscovite/illite, paragonite, pyrophyllite Red is Al-poor (Si-rich) muscovite (phengite) useful for mapping: (1) exposed saprolite/saprock is often white mica or Al-smectite (warmer colours) whereas transported materials are often kaolin-rich (cooler colours); (2) clays developed over carbonates, especially Al-smectite (montmorillonite, beidellite) will produce middle to warmers colours. (2) stratigraphic mapping based on different clay-types; and (3) lithology-overprinting hydrothermal alteration, e.g. Si-rich and K-rich phengitic mica (warmer colours). Combine with Ferrous iron in MgOH and FeOH content products to look for evidence of overlapping/juxtaposed potassic metasomatism in ferromagnesian parents rocks (e.g. Archaean greenstone associated Au mineralisation) +/- associated distal propyllitic alteration (e.g. chlorite, amphibole).

1. Band ratio: (B5+B7)/B6 Blue is low abundance, Red is high abundance potentially includes: phengite, muscovite, paragonite, lepidolite, illite, brammalite, montmorillonite, beidellite, kaolinite, dickite Useful for mapping: (1) exposed saprolite/saprock (2) clay-rich stratigraphic horizons; (3) lithology-overprinting hydrothermal phyllic (e.g. white mica) alteration; and (4) clay-rich diluents in ore systems (e.g. clay in iron ore). Also combine with AlOH composition to help map: (1) exposed in situ parent material persisting through "cover" which can be expressed as: (a) more abundant AlOH content + (b) long-wavelength (warmer colour) AlOH composition (e.g. muscovite/phengite).

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.

<div>The recent federal funding of the <em>National Space Mission for Observation</em> is in no small part a recognition of the capability of the Australian EO community and central to this is the ability to mount effective national-scale field validation programs.</div><div><br></div><div>After many delays, Landsat 9 was launched on the 27th September 2021. Before being handed to the USGS for operational use, NASA had oversight of configuring and testing the new platform and navigating it into its final operational orbit.&nbsp;For a brief few days and a handful of overpasses globally, Landsat 9 was scheduled to fly ‘under’ its predecessor Landsat 8. &nbsp;This provided the global EO community a ‘once in a mission lifetime’ opportunity to collect field validation data from both sensors.</div><div><br></div><div>At short notice the USGS were advised on the timing and location of these orbital overpasses. &nbsp;For Australia, this meant that between the 11th and 17th&nbsp;of November we would see a single overpass with 100% sensor overlap and three others that featured only 10% overlap. Geoscience Australia (who have a longstanding partnership with the USGS on satellite Earth observation) put out a call to the Australian EO community for collaborators.</div><div><br></div><div>Despite this compressed timeline, COVID travel restrictions and widespread La Niña induced rain and flooding, teams from CSIRO, Queensland DES, Environment NSW, University of WA, Frontier SI and GA were able to capture high value ground and water validation data in each of the overpasses.</div><div><br></div><div>Going forward, the Australian EO community need to maintain and build on these skills and capabilities such that the community can meet the future demands of not only our existing international EO collaborations but the imminent arrival of Australian orbiting EO sensors. Abstract presented at Advancing Earth Observation Forum 2022 (https://www.eoa.org.au/event-calendar/2021/12/1/advancing-earth-observation-aeo-2021-22-forum)

<b>This record was retired 29/03/2022 with approval from S.Oliver as it has been superseded by eCat 132310 GA Landsat 7 ETM+ Analysis Ready Data Collection 3</b> Surface Reflectance (SR) is a suite of Earth Observation (EO) products from GA. The SR product suite provides standardised optical surface reflectance datasets using robust physical models to correct for variations in image radiance values due to atmospheric properties, and sun and sensor geometry. The resulting stack of surface reflectance grids are consistent over space and time which is instrumental in identifying and quantifying environmental change. SR is based on radiance data from the Landsat TM/ETM+ and OLI sensors.

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: (B6+B8)/B7 Blue is low content, Red is high content (potentially includes: chlorite, epidote, jarosite, nontronite, gibbsite, gypsum, opal-chalcedony) Useful for mapping: (1) jarosite (acid conditions) - in combination with ferric oxide content (high); (2) gypsum/gibbsite - in combination with ferric oxide content (low); (3) magnesite - in combination with ferric oxide content (low) and MgOH content (moderate-high) (4) chlorite (e.g. propyllitic alteration) - in combination with Ferrous in MgOH (high); and (5) epidote (calc-silicate alteration) - in combination with Ferrous in MgOH (low).

The National Spectral Database (NSD) houses data taken by Australian remote sensing scientists. The database includes spectra covering targets as diverse as mineralogy, soils, plants, water bodies and various land surfaces.<br /> Currently the database holds spectral information from multiple locations across the country and as the collection grows in spatial / temporal coverage, the NSD will service continental scale validation requirements of the Earth observation community for satellite-based measurements of surface reflectance. The NSD is accessed with information provided at the NSD Geoscience Australia Content Management Interface (CMI) web page: https://cmi.ga.gov.au/data-products/dea/643/australian-national-spectral-database <b>Value:</b> Curated spectral data provides a wealth of knowledge to remote sensing scientists. For other parties interested in calibration and validation (Cal/Val) of surface reflectance products, the Geoscience Australia (GA) Cal/Val dataset provides a useful resource of ground-truth data to compare to reflectance captured by Landsat 8 and Sentinel 2 satellites. The Aquatic Library is a robust collection of Australian datasets from 1994 to present time, primarily of end-member and substratum measurements. The University of Wollongong collection represents immense value in end-member studies, both terrestrial and aquatic. <b>Scope:</b> The NSD covers Australian data including historical datasets as old as 1994. Physical study sites encompass locations around Australia, with spectra captured in every state. <b>Data types:</b> - Spectral data: raw digital numbers (DN), radiance and reflectance.  - From spectral bands VIS-NIR, SWIR1 & SWIR2: wavelengths 350nm - 2500nm collected with instruments in the field or lab setting. Contact for further information: NSDB_manager@ga.gov.au <b>To view the entire collection click on the keyword "HVC 144490" in the below Keyword listing <b>

Up to date information about the extent and location of surface water provides all Australians with a common understanding of this valuable and increasingly scarce resource. Digital Earth Australia (DEA) Waterbodies shows the wet surface area of waterbodies as estimated from satellites. It does not show depth, volume, purpose of the waterbody, nor the source of the water. DEA Waterbodies uses Geoscience Australia’s archive of over 30 years of Landsat satellite imagery to identify where over 300,000 waterbodies are in the Australian landscape and tells us the wet surface area within those waterbodies. It supports users to understand and manage water across Australia. For example, users can gain insights into the severity and spatial distribution of drought or identify potential water sources for aerial firefighting. The tool uses a water classification for every available Landsat satellite image and maps the locations of waterbodies across Australia. It provides a timeseries of wet surface area for waterbodies that are present more than 10% of the time and are larger than 2700m2 (3 Landsat pixels). The tool indicates changes in the wet surface area of waterbodies. This can be used to identify when waterbodies are increasing or decreasing in wet surface area. More information on using this dataset can be accessed on the DEA Knowledge Hub at <a href="https://docs.dea.ga.gov.au/data/product/dea-waterbodies-landsat/?tab=overview">https://docs.dea.ga.gov.au/data/product/dea-waterbodies-landsat/?tab=overview</a>. Refer to the research paper Krause et al. 2021 for additional details: <a href="https://doi.org/10.3390/rs13081437">https://doi.org/10.3390/rs13081437</a> The update from version 2 to version 3.0 of the DEA Waterbodies product and service was created through a collaboration between Geoscience Australia, the National Aerial Firefighting Centre, Natural Hazards Research Australia, and FrontierSI to make the product more useful in hazard applications. Geoscience Australia, the National Aerial Firefighting Centre, Natural Hazards Research Australia, and FrontierSI advise that the information published by this service comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, FrontierSI, Geoscience Australia, the National Aerial Firefighting Centre and Natural Hazards Research Australia (including its employees and consultants) are excluded from all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it.