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

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)

<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>

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

<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.

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.

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.

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

<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>

The Digital Earth Australia (DEA) Program Roadmap describes the high level work plan to be undertaken by the DEA Program in order to achieve its objectives and deliver benefits to the Australian Government and industry.