<div>The A1 poster incorporates 4 images of Australia taken from space by Earth observing satellites. The accompanying text briefly introduces sensors and the bands within the electromagnetic spectrum. The images include examples of both true and false colour and the diverse range of applications of satellite images such as tracking visible changes to the Earth’s surface like crop growth, bushfires, coastal changes and floods. Scientists, land and emergency managers use satellite images to analyse vegetation, surface water or human activities as well as evaluate natural&nbsp;hazards.</div>

<div>The DEA Geometric Median and Median Absolute Deviation products use statistical analyses to provide information on variance in the landscape over a given year. They provide insight into the “average” conditions observed over Australia in a given year, as well as the amount of variability experienced around that average. These products are useful for monitoring change detection, such as from cropping, urban expansion or burnt area mapping.&nbsp;</div><div><br></div><div>Satellite imagery allows us to observe the Earth with significant accuracy and detail. However, missing data — such as gaps caused by cloud cover — can make it difficult to create a complete image. In order to produce a single, complete view of a certain area, satellite data must be consolidated by stacking measurements from different points in time to create a composite image.&nbsp;</div><div><br></div><div>The Digital Earth Australia GeoMAD (Geometric Median and Median Absolute Deviation) data product is a cloud-free composite of satellite data compiled annually over each calendar year.&nbsp;</div><div><br></div><div>Large-scale image composites are increasingly important for a variety of applications such as land cover mapping, change detection, and the generation of high-quality data to parameterise and validate bio-physical and geophysical models. A number of compositing methodologies are being used in remote sensing in general, however, challenges still exist. These challenges include mitigating against boundary artifacts due to mosaicking scenes from different epochs ensuring spatial regularity across the mosaic image and maintaining the spectral relationship between bands.&nbsp;</div><div><br></div><div>The creation of good composite images is especially important due to the opening of the United States Geological Survey’s Landsat archive. The greater availability of satellite imagery has resulted in demand to provide large regional mosaics that are representative of conditions over specific time periods while also being free of clouds and other unwanted visual noise. One approach is to ‘stitch together’ multiple selected high-quality images. Another is to create mosaics in which pixels from a time series of observations are combined (using an algorithm). This ‘pixel composite’ approach to mosaic generation provides more consistent results than with stitching high-quality images due to the improved colour balance created by combining one-by-one pixel-representative images. Another strength of pixel-based composites is their ability to be automated, hence enabling their use in large data collections and time series datasets.&nbsp;</div><div><br></div><div>The DEA GeoMAD product can be used for seeing how an area of land usually looks rather than only viewing it at a single point in time. Hence you can assess the land cover and land use on a general basis rather than at a specific date. It can also be used to assess how much an area changes over time. You will notice areas like bare rock that are very stable versus those like cropping areas that change dramatically.&nbsp;</div><div><br></div><div>The DEA GeoMAD product combines the Geometric Median and the Median Absolute Deviation algorithms in a single package. The Geometric Median output provides information on the general conditions of the landscape for a given year. Meanwhile the Median Absolute Deviation output provides information on how the landscape is changing in the same year.&nbsp;</div><div><br></div>

<div>In recent years Geoscience Australia has undertaken a successful continental scale validation program, targeting Landsat and Sentinel analysis ready data surface reflectance products. The field validation model used for this program successfully built on earlier studies and the measurement uncertainties associated with these protocols have been quantified and published. As a consequence, the Australian earth observation community was well-placed to respond to the United States Geological Survey (USGS) call for collaborators with the 2021 Landsat 8 (L8) and Landsat 9 (L9) 6 underfly. Despite a number of challenges, seven validation datasets were captured across five sites. As there was only a single 100% overlap transit across Australia and with the country in the midst of a strong La Niña climate cycle, it was decided to deploy teams to the two available overpasses with only 15% side lap. The validation sites encompassed rangelands, chenopod scrublands and a large inland lake. Apart from instrument problems at one site, good weather enabled the capture of high quality field data allowing for meaningful comparisons between the radiometric performance of L8 and L9, as well as the USGS and Australian Landsat analysis ready data processing models. Duplicate (cross calibration) spectral sampling at different sites provides evidence of the field protocol reliability, while the off-nadir view of L9 over the water site has been used to better compare the performance of different water and atmospheric correction (ATCOR) processing models.&nbsp;</div> <b>Citation: </b>Byrne, G.; Broomhall, M.; Walsh, A.J.; Thankappan, M.; Hay, E.; Li, F.; McAtee, B.; Garcia, R.; Anstee, J.; Kerrisk, G.; et al. Validating Digital Earth Australia NBART for the Landsat 9 Underfly of Landsat 8. <i>Remote Sens.</i> <b>2024</b>, 16, 1233. https://doi.org/10.3390/rs16071233

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.

<div>The United States Geological Survey's (USGS) Landsat satellite program has been capturing images of the Australian continent for more than 30 years. This data is highly useful for land and coastal mapping studies.</div><div><br></div><div>In particular, the light reflected from the Earth’s surface (surface reflectance) is important for monitoring environmental resources – such as agricultural production and mining activities – over time.</div><div><br></div><div>We make accurate comparisons of imagery acquired at different times, seasons and geographic locations. However, inconsistencies can arise due to variations in atmospheric conditions, sun position, sensor view angle, surface slope and surface aspect. These are reduced or removed to ensure the data is consistent and can be compared over time.</div><div><br></div><div>The Geoscience Australia Landsat 9 OLI TIRS Analysis Ready Data Collection 3 contains three sub-products that provide corrections or attribution information:</div><div>- DEA Surface Reflectance NBAR* (Landsat 9)</div><div>- DEA Surface Reflectance NBART** (Landsat 9)</div><div>- DEA Surface Reflectance OA*** (Landsat 9)</div><div><br></div><div>Note: DEA produces NBAR as part of the Landsat ARD, this is available in the National Computing Infrastructure environment only and is not available in the DEA cloud environments.</div><div><br></div><div>The resolution is a 30 m grid based on the USGS Landsat Collection 2 archive, or 15 m for the panchromatic band. This data forms part of the DEA Collection 3 archive. </div><div><br></div><div>* Nadir corrected Bi-directional reflectance distribution function Adjusted Reflectance (NBAR)</div><div>** Nadir corrected Bi-directional reflectance distribution function Adjusted Reflectance with terrain illumination correction (NBART)</div><div>*** Observation Attributes (OA)</div>

<div>Intertidal environments contain many important ecological habitats such as sandy beaches, tidal flats, rocky shores, and reefs. These environments also provide many valuable benefits such as storm surge protection, carbon storage, and natural resources.&nbsp;</div><div>&nbsp;</div><div>Intertidal zones are being increasingly faced with threats including coastal erosion, land reclamation (e.g. port construction), and sea level rise. These regions are often highly dynamic, and accurate, up-to-date elevation data describing the changing topography and extent of these environments is needed. However, this data is expensive and challenging to map across the entire intertidal zone of a continent the size of Australia. &nbsp;</div><div>&nbsp;</div><div>The intertidal zone also forms a critical habitat and foraging ground for migratory shore birds and other species. An improved characterisation of the exposure patterns of these dynamic environments is important to support conservation efforts and to gain a better understanding of migratory species pathways. &nbsp;</div><div>&nbsp;</div><div>The <strong>DEA Intertidal </strong>product suite (https://knowledge.dea.ga.gov.au/data/product/dea-intertidal) provides annual continental -scale elevation and exposure products for Australia’s intertidal zone, mapped at a 10m resolution, from Digital Earth Australia’s archive of open-source Landsat and Sentinel-2 satellite data. These intertidal products enable users to better monitor and understand some of the most dynamic regions of Australia’s coastlines.</div><div><br></div><div><strong>Applications</strong></div><div><br></div><div> - Integration with existing topographic and bathymetric data to seamlessly map the elevation of the coastal zone.&nbsp;</div><div>&nbsp;</div><div> - Providing baseline elevation data for predicting the impact of coastal hazards such as storm surges, tsunami inundation, or future sea-level rise.&nbsp;</div><div>&nbsp;</div><div> - Investigating coastal erosion and sediment transport processes.&nbsp;</div><div>&nbsp;</div><div> - Supporting habitat mapping and modelling for coastal ecosystems extending across the terrestrial to marine boundary.&nbsp;</div><div>&nbsp;</div><div> - Characterisation of the spatio-temporal exposure patterns of the intertidal zone to support migratory species studies and applications.&nbsp;</div><div><br></div><div><br></div><div><br></div>