Analysis Ready Data (ARD) are satellite data that have been pre-processed for immediate analysis with minimal user effort. The generation of Surface Reflectance (SR) from optical satellite data, involves a series of corrections to standardise the data and enable meaningful comparison of data from multiple sensors and across time. Surface reflectance data are foundational for time-series analyses and rapid generation of other information products. Field based validation of surface reflectance data is therefore critical to determine its fitness for purpose, and applicability for downstream product development. In this paper, an approach for continental scale validation of the surface reflectance data from Landsat-8 and Sentinel-2 satellites, using field-based measurements that are near-synchronous to the satellite observations over multiple sites across Australia is presented. Good practice measurement protocols governing the acquisition of field data, including field instrument calibration, sampling strategy and approach for post-collection processing and management of field spectral data are outlined. This study has been a nationally coordinated, collaborative field data collection campaign across Australia. Permanent field sites, to support validation efforts within the broader Earth Observation (EO) community for continental scale products were also identified. The approach is expected to serve as a model for coordinated ongoing validation of ARD products at continental to global scales. Presented at the 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

<b>This record has been superseded by eCat 148920 DEA Waterbodies v3.0 (Landsat) with approval from N.Mueller on 01/02/2024 This record was retired 15/09/2022 with approval from S.Oliver as it has been superseded by eCat 146197 DEA Waterbodies (Landsat) </b> <p>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. <p>Digital Earth Australia 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. <p>Digital Earth Australia Waterbodies uses Geoscience Australia’s archive of over 30 years of Landsat satellite imagery to identify where almost 300,000 waterbodies are in the Australian landscape and tells us the wet surface area within those waterbodies. <p>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 during bushfires. <p>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 3125m2 (5 Landsat pixels). <p>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.

Factsheet for DEA with information relevant to stakeholders from the Australian Government

<div>These two videos provide tutorials on how to use the Digital Earth Australia (DEA) portal in the classroom. They include guides for basic navigation, how to load a data set (DEA Landcover) and how to compare different dates within a data set. Additionally, they also show how to share your data via either a share link, image or as an interactive ‘Story’ of saved scenes.</div><div>Videos included:</div><div>-&nbsp;Introduction to using the Digital Earth Australia (DEA) portal</div><div>- Exploring land cover data using the Digital Earth Australia (DEA) portal</div>

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/)

Groundwater-dependent ecosystems (GDEs) rely on access to groundwater on a permanent or intermittent basis for some or all of their water requirements (Queensland Government, 2018). Remotely sensed data from Digital Earth Australia (DEA) (Geoscience Australia, 2018) were used to map potential aquatic and other GDEs and enhance understanding of surface water – groundwater interactions in the Upper Burdekin region. Two Landsat TM satellite products (Water Observations from Space (WOfS; Mueller et al. 2016) summary statistic and Tasselled Cap Index (TCI) wetness summary)) were used to investigate the persistence of surface water and soil moisture in the landscape to identify perennial streams, springs and other parts of the landscape that may rely on groundwater discharge. The WOfS summary statistic represents, for each pixel, the percentage of time that water is detected at the surface relative to the total number of clear observations. Due to the 25-m by 25-m pixel size of Landsat data, only features at least 25 m wide are detected and only features covering multiple pixels are consistently detected. The WOfS summary statistic was produced over the McBride and Nulla Basalt provinces for the entire period of available data (1987 to 2018). Pixels were polygonised and classified in order to visually enhance key data in the imagery, such as the identification of standing water for at least 80% of the time. The TCI is a method of reducing six surface reflectance bands of satellite data to three bands (Brightness, Greenness, Wetness) using a Principal Components Analysis (PCA) and Procrustes' Rotation (Roberts et al., 2018). The published coefficients of Crist (1985) are applied to DEA's Landsat data to generate a TCI composite. The resulting Tasselled Cap bands are a linear combination of the original surface reflectance bands that correlate with the Brightness (bare earth), Greenness and Wetness of the landscape. The TCI wetness summary (or Tasselled Cap Wetness (TCW) percentage exceedance composite), derived from the Wetness band, 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’ according to the TCI. 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 threshold is set at -600 to calculate the percentage exceedance. This threshold is based on scientific judgment and is currently in the research/testing phase. It is based on Australian conditions and conservative in nature. The dry season, when surface runoff to streams and rainfall are minimal, is particularly useful for identifying and mapping groundwater-fed streams, springs and other ecosystems that rely on access to groundwater during periods of limited rainfall. The Upper Burdekin region was especially dry between May and October 2013, with low rainfall totals in the months preceding this dry season and overall below-average rainfall conditions (i.e. decline in rainfall residual mass). 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. Field validation of the remote sensing data products would be required to confirm the preliminary identification of parts of the landscape where groundwater discharges to the surface and potentially supports GDEs. This release includes the classified WOfS summary statistic and classified TCW percentage exceedance composite (May-October 2013) data products for the McBride and Nulla basalt provinces in the Upper Burdekin region, North Queensland. <b>References: </b> Crist EP (1985) A TM Tasseled Cap equivalent transformation for reflectance factor data. Remote Sensing of Environment 17(3), 301–306. Doi: 10.1016/0034-4257(85)90102-6. Geoscience Australia (2018) Digital Earth Australia. Geoscience Australia, http://www.ga.gov.au/dea. 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. Remote Sensing of Environment 174, 341-352, ISSN 0034-4257. Queensland Government (2018) Groundwater dependent ecosystems, WetlandInfo 2014. Queensland Government, Brisbane, https://wetlandinfo.des.qld.gov.au/wetlands/ecology/aquatic-ecosystems-natural/groundwater-dependent/. Roberts D, Dunn B and Mueller N (2018) Open Data Cube Products Using High-Dimensional Statistics of Time Series. International Geoscience and Remote Sensing Symposium. Valencia, Spain: IEEE Geoscience and Remote Sensing Society.

Combining observations of open water, wet vegetation, and vegetation fractional cover allows us to observe the spatiotemporal behaviour of wetlands. We developed a Wetlands Insight Tool (WIT) using Analysis-Ready Data available through Digital Earth Australia that combines Water Observations from Space (WOfS), the Tasseled Cap Wetness Transform (TCW) and Fractional Cover into an asset drill. We demonstrate the tool on three Australian wetlands, showing changes in water and vegetation from bush fires, sand mining and planned recovery. This paper was submitted to/presented at the 2019 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2019) - https://igarss2019.org/

<div>Tasseled Cap percentiles provide an annual summary of how the environment has varied through a year. The Tasseled Cap percentiles provide the upper, lower and middle conditions as described by the 90th, 10th and 50th percentiles respectively, of greenness, wetness and brightness across the landscape.</div><div><br></div><div>These percentiles are intended for use as inputs into classification algorithms to identify such environmental features as wetlands and groundwater dependent ecosystems, and characterise salt flats, clay pans, salt lakes and coastal land forms.</div><div><br></div>

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.

60 second video announcing Digital Earth Australia - a world first analysis platform for satellite imagery and other Earth observations.