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>

This report provides a preliminary assessment of the utility of a satellite remote sensing approach for the identification and characterisation of coastal habitats that are critical for threatened and migratory species in northern Australia. This work is part of the Habitats research theme in the A12 Northern Seascapes Scoping Project. The Australian Landsat archive in the Digital Earth Australia (DEA) analysis platform for satellite imagery was utilised to demonstrate its potential for mapping intertidal areas and mangrove extent, and changes over time in the extent of coastal landforms and habitats. Seven estuaries were examined, Darwin Harbour and the Keep, Daly, Roper, Macarthur, Flinders and Gilbert River estuaries. The estuaries were selected by the A12 Project team because they are known to provide important areas for the species of interest. Features of importance to shorebird populations were a focus. The focus of this scoping work was to utilise the DEA Landsat archive to build understanding of the effects of tidal dynamics on intertidal habitats across this region of large and complex tides, examine approaches to mapping the extent of key coastal habitats, and test the potential of the archive to detect coastal habitat change, in particular mangrove. In northern Australia, cloud interference can make it difficult to obtain clear satellite imagery. To avoid this issue, the geometric median of surface reflectance values was used to produce crisp, cloud-free composite images that depict the maximum observed tidal extent in the seven estuaries. Tide-tagging of satellite imagery was also successfully employed to allow any tide induced change to be removed from change-detection analyses and clearly depict the intertidal extent. Application of the Intertidal Extent Model in the DEA enabled the extent and morphology of estuarine intertidal environments to be mapped. The DEA also enabled habitat change change detection using the fully processed, high density, three decade long Landsat time series. The results clearly depict the dynamic nature of some areas, including large-scale rapid island growth and mangrove expansion (e.g. Keep River and Gilbert River estuaries), gradual long-term expansion of mangrove (Flinders River and McArthur River estuaries), and estuaries with areas of rapid recent die back of mangrove (Roper River and Flinders estuaries). This information is important for the management of key species as well decisions around coastal developments. With Landsat and new satellite data streams (e.g. Sentinal 2) continually being added to the DEA, this time-series analysis approach could be developed into an effective habitat extent and condition monitoring tool for northern Australia. The image products and analysis tools employed in this study demonstrate the potential utility of DEA for mapping the extent and dynamics of key coastal and estuarine habitats utilised by threatened and migratory species. To better inform the management of these species, a key next step in this approach is to utilise ground-validation data to enable these habitats to be robustly classified and quantified using the Landsat archive. This analysis should provide important baseline information and enable the extent and condition of key habitats to be monitored. <b>Preferred Citation:</b> <i>Phillips, C., Lymburner, L. & Brooke, B. (2018). Characterising northern estuaries using Digital Earth Australia.</i> Report to the National Environmental Science Programme, Marine Biodiversity Hub. <i>Geoscience Australia.</i>

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

Factsheet for DEA with information relevant to stakeholders from the earth observation iand other related industries.

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 greater than 25m by 25m 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. Areas depicted in the dataset have been exaggerated to enable visibility.

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.

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).

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.

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.