This collection contains processing environments for use by external users of the Australian Geoscience Data Cube (AGDC).

This collection contains processing environments and code repositories created by Geoscience Australia used to generate National Earth and Marine Observations products.

This collection is used to provide an environment for external access to the Australian Geoscience Data Cube Virtual Desktop Interface (VDI).

<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)

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>

<b>This record was retired 29/03/2022 with approval from S.Oliver as it has been superseded by eCat 130853 GA Landsat 5 TM 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.

<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.

<b>This record was retired 29/03/2022 with approval from S.Oliver as it has been superseded by eCat 145498 Geoscience Australia Landsat Fractional Cover Collection 3</b> The Fractional Cover (FC) algorithm was developed by the Joint Remote Sensing Research Program and is described in described in Scarth et al. (2010). It has been implemented by Geoscience Australia for every observation from Landsat Thematic Mapper (Landsat 5), Enhanced Thematic Mapper (Landsat 7) and Operational Land Imager (Landsat 8) acquired since 1987. It is calculated from surface reflectance (SR-N_25_2.0.0). FC_25 provides a 25m scale fractional cover representation of the proportions of green or photosynthetic vegetation, non-photosynthetic vegetation, and bare surface cover across the Australian continent. The fractions are retrieved by inverting multiple linear regression estimates and using synthetic endmembers in a constrained non-negative least squares unmixing model. For further information please see the articles below describing the method implemented which are free to read: - Scarth, P, Roder, A and Schmidt, M 2010, 'Tracking grazing pressure and climate interaction - the role of Landsat fractional cover in time series analysis', Proceedings of the 15th Australasian Remote Sensing and Photogrammetry Conference, Schmidt, M, Denham, R and Scarth, P 2010, 'Fractional ground cover monitoring of pastures and agricultural areas in Queensland', Proceedings of the 15th Australasian Remote Sensing and Photogrammetry Conference A summary of the algorithm developed by the Joint Remote Sensing Centre is also available from the AusCover website: http://data.auscover.org.au/xwiki/bin/view/Product+pages/Landsat+Fractional+Cover Fractional cover data can be used to identify large scale patterns and trends and inform evidence based decision making and policy on topics including wind and water erosion risk, soil carbon dynamics, land management practices and rangeland condition. This information could enable policy agencies, natural and agricultural land resource managers, and scientists to monitor land conditions over large areas over long time frames.

The Australian Government is investing in a world first analysis platform for satellite imagery and other Earth observations. From sustainably managing the environment to developing resources and optimising our agricultural potential, Australia must overcome a number of challenges to meet the needs of our growing population. Digital Earth Australia (DEA) will deliver a unique capability to process, interrogate, and present Earth observation satellite data in response to these issues. It will track changes across Australia in unprecedented detail, identifying soil and coastal erosion, crop growth, water quality, and changes to cities and regions. DEA will build on the globally recognised innovation, the Australian Geoscience Data Cube1; which was the winner of the 2016 Content Platform of the Year at the Geospatial World Leadership Awards and was developed as a partnership between GA, CSIRO and the National Collaborative Research Infrastructure Strategy (NCRIS) supported National Computational Infrastructure (NCI).

Earth Observations over Antarctica and the Southern Ocean are critical for understanding changes in the cryosphere, ecosystems and oceans through time. Our ability to observe Antarctica systematically at a continental scale is constrained by difficulties accessing, storing and pre-processing satellite imagery prior to analysis. Some of these challenges are unique to the Antarctic environment, where factors such as cloud masking, reflectivity, prolonged periods of darkness and atmospheric differences in water vapour, aerosol and signal scattering mean that corrections applied to satellite data in other regions of the world aren’t representative of Antarctic conditions. A new collaboration between Geoscience Australia and the Australian Antarctic Division, Digital Earth Antarctica, aims to improve access to corrected continental scale satellite data through use of Open Data Cube technology. This initiative builds on work in the international community in developing Open Data Cube platforms, which have been applied in the development of Digital Earth Australia and Digital Earth Africa. The Digital Earth Antarctica platform will provide open access to analysis ready time-series data that has been corrected and validated for Antarctic conditions. It will focus primarily on data from Landsat (optical), Sentinel-1 (synthetic aperture radar) and Sentinel-2 (optical), with other sensors to be added as the capability expands. Digital Earth Antarctica is an ambitious project that will work alongside other international efforts to enhance the accessibility of quality Antarctic Earth Observations. Abstract/Poster presented at the 2023 New Zealand - Australia Antarctic Science Conference (NZAASC)