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)

Record for source data - Calibration & Validation Surface Reflectance Measurements for the National Spectral Database (NSD). This is a collection of Phase 1 & Phase 2 datasets from Geoscience Australia Analysis Ready Data (ARD) Calibration & Validation's field program. The data is intended to serve the GA ARD surface reflectance validation pipeline. Phase 1 field campaigns are summarised in the technical report: Byrne, G., Walsh, A., Thankappan, M., Broomhall, M., Hay, E. 2021. DEA Analysis Ready Data Phase 1 Validation Project : Data Summary. Geoscience Australia, Canberra. doi.org/10.26186/145101

The National Spectral Database (NSD) houses data from Australian remote sensing scientists. The database includes spectra covering targets as diverse as mineralogy, soils, plants, water bodies and various land surfaces. 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. <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

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>

<div>A package of deliverables for the Australian Research Data Commons (ARDC), Bushfire History Data Project, Work Package 5. If you require further information or access, please contact earth.observation@ga.gov.au</div><div><br></div><div>Outputs generated for this Project are interim and represent a snapshot of work to date, as of September 2023. Deliverables are developmental in nature and are under further advancement. Datasets or visualisations should not be treated as endorsed, authoritative, or quality assured; and should not be used for anything other than a minimal viable product, especially not for safety of life decisions. The eventual purpose of this information is for strategic decisions, rather than tactical decisions. For local data, updates and alerts, please refer to your State or Territory emergency or fire service.</div><div><br></div><div>The purpose of this Project (WP5) was to generate fire history products from Earth observation (EO) data available from the Landsat and Sentinel-2 satellites. WP5 aimed to implement a suite of automated EO-based algorithms currently in use by State and Territory agencies, to produce National-scale data products describing the timing, location, and extent of bushfires across Australia. WP5 outputs are published here as a “deliverable package”, listed as documents, datasets and Jupyter notebooks.&nbsp;</div><div><br></div><div>Burnt area data demonstrators were produced to a Minimum Viable Product level. Four burnt area detection methods were investigated: </div><div>* BurnCube (Geoscience Australia, ANU, (Renzullo et al. 2019)),</div><div>* Burnt Area Characteristics (Geoscience Australia, unpublished methodology),</div><div>* A version of the Victoria’s Random Forest (Victorian, Tasmanian and New South Wales Governments). Based on method as described in Collins et al. (2018), and</div><div>* Queensland’s RapidFire (Queensland Government, (Van den Berg et al. 2021). Please note that demonstrator burnt area data from the Queensland method was only investigated for the Queensland location. Data were sourced from Terrestrial Ecosystem Research Network (TERN) infrastructure, which is enabled by the Australian Government National Collaborative Research Infrastructure Strategy (NCRIS). </div><div><br></div><div>In addition demonstrator products that examine the use of Near Real Time satellite data to map burnt area, data quality and data uncertainty were delivered. </div><div><br></div><div>The algorithms were tested on several study sites:</div><div>* Eastern Victoria,</div><div>* Cooktown QLD,</div><div>* Kangaroo Island SA,</div><div>* Port Hedland WA, and</div><div>* Esperance WA.</div><div><br></div><div>The BurnCube (Renzullo et al. 2019) method was implemented at a national-scale using the Historic Burnt Area Processing Pipeline documented below “GA-ARDC-DataProcessingPipeline.pdf”. Continental-scale interim summary results were generated for both 2020 Calendar Year and 2020 Financial Year. Results were based upon both Landsat 8 and Sentinel-2 (combined 2a and 2b) satellite outputs, producing four separate interim products:&nbsp;</div><div>* Landsat 8, 2020 Calendar Year, BurnCube Summary (ga_ls8c_nbart_bc_cyear_3),</div><div>* Landsat 8, 2020 Financial Year, BurnCube Summary (ga_ls8c_nbart_bc_fyear_3),</div><div>* Sentinel 2a and 2b, 2020 Calendar Year, BurnCube Summary (ga_s2_ard_bc_cyear_3),</div><div>* Sentinel 2a and 2b, 2020 Financial Year, BurnCube Summary (ga_s2_ard_bc_fyear_3).</div><div>&nbsp;</div><div>The other methods have sample products for the study sites, as discussed in the "lineage" section. </div><div><br></div><div>The Earth observation approach has several limitations, leading to errors of omission and commission (ie under estimation and over estimation of the burnt area). Omission errors can result from: lack of visibility due to clouds; small or patchy fires; rapid vegetation regrowth between fire and satellite observation; cool understorey burns being hidden by the vegetation canopy. Commission errors can result from: incorrect cloud or cloud-shadow masking; high-intensity land-use changes (such as cropping); areas of inundation. In addition cloud and shadow masking lead to differences in elapsed time between reference imagery and observations of change resulting in differences in burn area detection. For more information on data caveats please see Section 7.6 of DRAFT-ARDC-WP5-HistoricBurntArea.</div><div><br></div><div>The official Project title is: The Australian Research Data Commons (ARDC), Bushfire Data Challenges Program; Project Stream 1: the ARDC Bushfire History Data Project; Work Package 5 (WP5): National burnt area products analysed from Landsat and Sentinel 2 satellite imagery.</div><div><br></div><div>We thank the Mindaroo Foundation and ARDC for their support in this work.</div>

Analysis Ready Data (ARD) takes medium resolution satellite imagery captured over the Australian continent and corrects for inconsistencies across land and coastal fringes. The result is accurate and standardised surface reflectance data, which is instrumental in identifying and quantifying environmental change. This product is a single, cohesive ARD package, which allows you to analyse surface reflectance data as is, without the need to apply additional corrections. ARD consists of sub products, including : 1) NBAR Surface Reflectance which produces standardised optical surface reflectance data using robust physical models which correct for variations and inconsistencies in image radiance values. Corrections are performed using Nadir corrected Bi-directional reflectance distribution function Adjusted Reflectance (NBAR). 2) NBART Surface Reflectance which performs the same function as NBAR Surface Reflectance, but also applies terrain illumination correction. 3) OA Observation Attributes product which provides accurate and reliable contextual information about the data. This 'data provenance' provides a chain of information which allows the data to be replicated or utilised by derivative applications. It takes a number of different forms, including satellite, solar and surface geometry and classification attribution labels. ARD enables generation of Derivative Data and information products that represent biophysical parameters, either summarised as statistics, or as observations, which underpin an understanding of environmental dynamics. The development of derivative products to monitor land, inland waterways and coastal features, such as: - urban growth - coastal habitats - mining activities - agricultural activity (e.g. pastoral, irrigated cropping, rain-fed cropping) - water extent Derivative products include: - Water Observations from Space (WOfS) - National Intertidal Digital Elevation Model (NIDEM) - Fractional Cover (FC) - Geomedian ARD and Derivative products are reproduced through a period collection upgrade process for each sensor platform. This process applied improvements to the algorithms and techniques and benefits from improvements applied to the baseline data that feeds into the ARD production processes. <b>Value: </b>These data are used to understand distributions of and changes in surface character, environmental systems, land use. <b>Scope: </b>Australian mainland and some part of adjacent nations. Access data via the DEA web page - <a href="https://www.dea.ga.gov.au/products/baseline-data">https://www.dea.ga.gov.au/products/baseline-data</a>

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/

<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.

Digital Earth Australia (DEA) is a world-class digital infrastructure that uses satellite data, in the form of images and information, to detect physical changes across Australia in unprecedented detail. It identifies soil and coastal erosion, crop growth, water quality and changes to cities and regions. DEA provides government, industry, and individuals with the high-quality data and tools required for policy and investment decision-making. DEA will support industry productivity and innovation and the development of new digital products and services. These capabilities will improve decision-making, increase business efficiency, bolster profits and create jobs. For more information visit www.ga.gov.au/dea

<div>This document steps teachers and students through accessing and using satellite data on the Digital Earth Australia (DEA) Portal, with a particular focus on bushfires and flood events. The document is intended to be followed with the DEA portal open so teachers and students can explore the data using the links provided in the guide. The document also provides brief background information on how spectral satellites operate and how various bands of the electromagnetic spectrum can deliver useful data.</div>