Digital Earth Australia (DEA) is a key piece of public data infrastructure that uses images and information recorded by satellites orbiting our planet to detect physical changes across Australia in unprecedented detail. Landsat 5, 7 and 8 ‘analysis-ready’ data are currently available within DEA, where the raw satellite data have been corrected and orthorectified to enable easy interrogation of data across sensors. Geoscience Australia is developing techniques for analysing the data within DEA to identify wetlands and groundwater dependent ecosystems across northern Australia. These techniques include summarising observations of ‘wetness’ acquired over 30 years and linking these observations to gridded rainfall measurements to identity waterbodies and wetlands that persist during periods of low rainfall. These wetness summaries have been shown to correspond with known spring complexes in the Carmichael River catchment in Queensland, and have been used to improve the understanding of groundwater discharge processes within basalt provinces in the Upper Burdekin region in Queensland. This poster was submitted/presented to the 2018 Australian Geoscience Council Convention (AGCC) 14-18 October (https://www.agcc.org.au/)

The Tasselled Cap Wetness (TCW) percentage exceedance composite represents the behaviour of water in the landscape, as defined by the presence of water, moist soil or wet vegetation at each pixel through time. The summary shows the percentage of observed scenes where the Wetness layer of the Tasselled Cap transform is above the threshold, i.e. where each pixel has been observed as ‘wet’. Areas that retain surface water or wetness in the landscape during the dry season are potential areas of groundwater discharge and associated GDEs. The TCW exceedance composite was classified into percentage intervals to distinguish areas that were wet for different proportions of time during the 2013 dry season. Areas depicted in the dataset have been exaggerated to enable visibility.

The Tasselled Cap Wetness (TCW) percentage exceedance composite represents the behaviour of water in the landscape, as defined by the presence of water, moist soil or wet vegetation at each pixel through time. The summary shows the percentage of observed scenes where the Wetness layer of the Tasselled Cap transform is above the threshold, i.e. where each pixel has been observed as ‘wet’. Areas that retain surface water or wetness in the landscape during the dry season are potential areas of groundwater discharge and associated GDEs. The TCW exceedance composite was classified into percentage intervals to distinguish areas that were wet for different proportions of time during the 2013 dry season. Areas depicted in the dataset have been exaggerated to enable visibility.

This web service provides access to gridded data produced by Geoscience Australia from studies of Australian groundwater and hydrogeological systems.

This web service provides access to gridded data produced by Geoscience Australia from studies of Australian groundwater and hydrogeological systems.

<div>Groundwater dependent ecosystems (GDEs) rely on access to groundwater on a permanent or intermittent basis to meet some or all of their water requirements (Richardson et al., 2011). The <a href="https://explorer-aws.dea.ga.gov.au/products/ga_ls_tc_pc_cyear_3">Tasselled Cap percentile products</a> created by Digital Earth Australia (2023) were used to identify potential GDEs for the upper Darling River floodplain study area. These percentile products provide statistical summaries (10th, 50th, 90th percentiles) of landscape brightness, greenness and wetness in imagery acquired between 1987 and present day. The 10th percentile greenness and wetness represent the lowest 10% of values for the time period evaluated, e.g. 10th greenness represents the least green period. In arid regions, areas that are depicted as persistently green and/or wet at the 10th percentile have the greatest potential to be GDEs. For this reason, and due to accessibility of the data, the 10th percentile Tasselled Cap greenness (TCG) and Tasselled Cap wetness (TCW) products were used as the basis for the assessment of GDEs for the upper Darling River floodplain study area. </div><div><br></div><div>This data release is an ESRI geodatabase, with layer files, including:</div><div><br></div><div>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;original greenness and wetness datasets extracted; </div><div><br></div><div>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;classified 10th percentile greenness and wetness datasets (used as input for the combined dataset); </div><div><br></div><div>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;combined scaled 10th percentile greenness and wetness dataset (useful for a quick glance to identify potential groundwater dependent vegetation (GDV) that have high greenness and wetness e.g. river red gums)</div><div><br></div><div>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;combined classified 10th percentile greenness and wetness dataset (useful to identify potential GDV/GDE and differentiate between vegetation types)</div><div><br></div><div>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;coefficient of variation of 50th percentile greenness dataset (useful when used in conjunction with the scaled/combined products to help identify GDEs)</div><div><br></div><div>For more information and detail on these products, refer to <a href="https://dx.doi.org/10.26186/148545">https://dx.doi.org/10.26186/148545</a>.</div><div><br></div><div><strong>References</strong></div><div>Digital Earth Australia (2023). <em><a href="https://docs.dea.ga.gov.au">Digital Earth Australia User Guide</a></em>. </div><div>Richardson, S., E. Irvine, R. Froend, P. Boon, S. Barber, and B. Bonneville. 2011a. <em>Australian groundwater-dependent ecosystem toolbox part 1: Assessment framework.</em> Waterlines Report 69. Canberra, Australia: Waterlines.</div>

<div>Groundwater is critical to the survival of a range of ecosystems in Australia through provision of a direct source of water to plants with suitable root systems, and through discharge into surface water systems. Effectively managing groundwater dependent ecosystems (GDEs) alongside other water demands requires the ability to identify, characterise, and monitor vegetation condition.&nbsp;<em>&nbsp;</em><br> As part of the <a href="https://www.eftf.ga.gov.au/upper-darling-river-floodplain-groundwater-study">Exploring for the Future Upper Darling Floodplain</a> (UDF) groundwater project in western New South Wales, we present results from a study testing the suitability of two novel methods (a) recently available tasselled cap percentile products with national coverage through Digital Earth Australia, and (b) dry-conditions interferometric radar (InSAR) coherence images for mapping vegetation that is potentially groundwater dependent. <em>&nbsp;</em></div><div><em>&nbsp;</em></div><div>A combination of greenness and wetness 10th percentile tasselled cap products delineated terrestrial and aquatic GDEs with greater accuracy than existing regional ecosystem mapping, demonstrating the utility of these products for GDE identification. These results suggest the tasselled cap products can be used to support and refine the existing GDE mapping for this region, and further testing of their suitability and application for other regions is warranted.&nbsp;<em>&nbsp;</em></div><div><em>&nbsp;</em></div><div>The InSAR coherence images produced good agreement with the Bureau of Meteorology national GDE Atlas for areas of high probability of groundwater dependence. Although data availability and technical expertise currently lags behind optical imagery products, if research continues to show good performance in mapping potential GDEs and other applications, InSAR could become an important line of evidence within multi-dataset investigations.&nbsp;<em>&nbsp;</em></div><div><em>&nbsp;</em></div><div>Key next steps for improving the utility of these techniques &nbsp;are (a) comparison with vegetation condition data, and (b) further assessment of the likelihood of groundwater dependence through assessing relationships between vegetation condition and groundwater, surface water, and soil moisture availability.<em>&nbsp;</em></div><div>&nbsp;</div><div>This abstract was submitted/presented to the 2023 Australasian Groundwater / New Zealand Hydrological Society (AGC NZHS) Joint Conference (https://www.hydrologynz.org.nz/events-1/australasian-groundwater-nzhs-joint-conference)</div>

<div>Groundwater dependent ecosystems (GDEs) rely on access to groundwater on a permanent or intermittent basis to meet some or all of their water requirements (Richardson et al., 2011). The <a href="https://explorer-aws.dea.ga.gov.au/products/ga_ls_tc_pc_cyear_3">Tasseled Cap percentile products</a> created by Digital Earth Australia (2023) were used to identify potential GDEs for the South Nicholson-Georgina basins study area. These percentile products provide statistical summaries (10th, 50th, 90th percentiles) of landscape brightness, greenness and wetness in imagery acquired between 1987 and present day. The 10th percentile greenness and wetness represent the lowest 10% of values for the time period evaluated, e.g. 10th percentile greenness represents the least green period. In arid regions, areas that are depicted as persistently green and/or wet at the 10th percentile have the greatest potential to be GDEs. For this reason, and due to accessibility of the data, the 10th percentile Tasseled Cap greenness (TCG) and Tasseled Cap wetness (TCW) products were used as the basis for the assessment of GDEs for the South Nicholson-Georgina region. The 50th percentile greenness was utilised to create the coefficient of variance (CV) dataset. This data release is an ESRI geodatabase, with layer files, including: - combined classified 10th percentile greenness and wetness dataset (useful to identify potential groundwater dependent vegetation/other GDEs and differentiate between vegetation types) - CV of 50th percentile greenness dataset (useful when used in conjunction with the combined product to help identify groundwater dependent vegetation) For more information and detail on these products, refer to associated <a href="https://dx.doi.org/10.26186/149377">report</a>. </div><div><br></div><div><strong>References</strong></div><div>Digital Earth Australia (2023).&nbsp;<em><a href="https://docs.dea.ga.gov.au/">Digital Earth Australia User Guide.</a></em></div><div>Richardson, S., E. Irvine, R. Froend, P. Boon, S. Barber, and B. Bonneville. 2011a.&nbsp;<em>Australian groundwater-dependent ecosystem toolbox part 1: Assessment framework.</em>&nbsp;Waterlines Report 69. Canberra, Australia: Waterlines.</div><div><br></div>

<div>The Groundwater Dependent Ecosystem (GDE) Atlas (Bureau of Meteorology, 2019) is a well-known national product that has been utilised for a wide range of applications including environmental impact statements, water planning and research. A complementary GDE dataset, Groundwater Dependent Waterbodies (GDW), has been produced from Digital Earth Australia (DEA) national data products. This new GDW ArcGIS dataset is spatially aligned with Landsat satellite-derived products, enabling ready integration with other spatial data to map and characterise GDEs across the continent.</div><div><br></div><div>The DEA Water Observations Multi Year Statistics (Mueller et al. 2016; DEA 2019) and the DEA Waterbodies (version 2) data product (Kraus et al., 2021; DEA Waterbodies, 2022) have been combined with the national GDE Atlas to produce the GDW dataset which delineates surface waterbodies that are known and/or high potential aquatic GDEs. The potential of a GDE relates to the confidence that the mapped feature is a GDE, where known GDEs have been mapped from regional studies and high potential GDEs identified from regional or national studies (Nation et al., 2017). The GDW dataset are aquatic GDE waterbodies, including springs, rivers, lakes and wetlands, which rely on a surface expression of groundwater to meet some or all of their water requirements. </div><div><br></div><div>The DEA Water Observation Multi Year Statistics, based on Collection 3 Landsat satellite imagery, shows the percentage of wet observations in the landscape relative to the total number of clear observations since 1986. DEA Waterbodies identifies the locations of waterbodies across Australia that are present for greater than 10% of the time and are larger than 2700m2 (3 Landsat pixels) in size. These waterbodies include GDEs and non-GDEs (e.g. surface water features not reliant on groundwater, such as dams). Where known/high potential GDEs in the GDE Atlas intersected a DEA waterbody, the entire waterbody polygon was assigned as a potential GDW, resulting in 55,799 waterbodies in the GDW dataset. Conversely, any GDEs not classified as known/high potential GDEs in the Atlas, due to a lack of data, are not included in the GDW product. Even though this method should remove dams from the GDW dataset (assuming they have been assigned appropriately in the GDE Atlas), due to spatial misalignment some may still be included that are not potential GDEs. Furthermore, surface water features that are too small to be detected by Landsat satellite data will be excluded from the GDW dataset.</div><div><br></div><div>The GDW polygons were attributed with the spatial summary of maximum, median, mean and minimum percentages for pixels within each GDW, derived from the DEA Water Observation Multi Year Statistics i.e. maximum/minimum pixel value or median/mean across all pixels in the GDW. This attribute enables comparison between GDWs of the proportion of time they have surface water observed. An additional attribute was added to the GDW dataset to indicate amount of overlap between waterbodies and aquatic GDEs in the GDE Atlas.&nbsp;</div><div><br></div><div>An ESRI dataset, AquaticGDW.gdb, and a variety of national ArcGIS layer files have been produced using the spatial summary statistics in the GDW dataset.</div><div>These provide a first-pass representation of known/high potential aquatic GDEs and their surface water persistence, derived consistently from Landsat satellite imagery across Australia.</div><div><br></div><div><strong>References:</strong></div><div> </div><div>Bureau of Meteorology, 2019. <em>Groundwater Dependent Ecosystems Atlas</em>. http://www.bom.gov.au/water/groundwater/gde/index.shtml </div><div>&nbsp;</div><div>DEA Water Observations Statistics, 2019. https://cmi.ga.gov.au/data-products/dea/686/dea-water-observations-statistics-landsat</div><div><br></div><div>DEA Waterbodies, 2022. https://www.dea.ga.gov.au/products/dea-waterbodies</div><div><br></div><div>Krause, C.E., Newey, V., Alger, M.J., and Lymburner, L., 2021. Mapping and Monitoring the Multi-Decadal Dynamics of Australia’s Open Waterbodies Using Landsat, <em>Remote Sensing</em>, 13(8), 1437. https://doi.org/10.3390/rs13081437</div><div><br></div><div>Mueller, N., Lewis, A., Roberts, D., Ring, S., Melrose, R., Sixsmith, J., Lymburner, L., McIntyre, A., Tan, P., Curnow, S. and Ip, A., 2016. Water observations from space: Mapping surface water from 25 years of Landsat imagery across Australia. <em>Remote Sensing of Environment</em>, 174, 341-352, ISSN 0034-4257.</div><div><br></div><div>Nation, E.R., Elsum, L., Glanville, K., Carrara, E. and Elmahdi, A., 2017. Updating the Atlas of Groundwater Dependent Ecosystems in response to user demand, 22nd International Congress on Modelling and Simulation, Hobart, Tasmania, mssanz.org.au/modsim2017</div>

<div>This study investigates the feasibility of mapping potential groundwater dependent vegetation (GDV) at a regional scale using remote sensing data. Specifically, the Digital Earth Australia (DEA) Tasseled Cap Percentiles products, integrated with the coefficient of greenness and/or wetness, are applied in three case study regions in Australia to identify and characterise potential terrestrial and aquatic groundwater dependent ecosystems (GDE). The identified high potential GDE are consistent with existing GDE mapping, providing confidence in the methodology developed. The approach provides a consistent and rapid first-pass approach for identifying and assessing GDEs, especially in remote areas of Australia lacking detailed GDE and vegetation information.</div>