This record has been deprecated by eCat 148920 DEA Waterbodies Version 3.0 with approval from A.Metlenko on 01/04/2025.

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.

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.

Digital Earth Australia Waterbodies uses Geoscience Australia’s archive of over 30 years of Landsat satellite imagery to identify where over 300,000 waterbodies are in the Australian landscape and tells us the wet surface area within those waterbodies.

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.

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 2700m2 (3 Landsat pixels).

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.

Refer to Krause et al. 2021 for full details of this dataset. https://doi.org/10.3390/rs13081437

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.

Digital Earth Australia (DEA) 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.

DEA Waterbodies uses Geoscience Australia’s archive of over 30 years of Landsat satellite imagery to identify where over 300,000 waterbodies are in the Australian landscape and tells us the wet surface area within those waterbodies.

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.

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 2700m2 (3 Landsat pixels).

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.

More information on using this dataset can be accessed on the DEA Knowledge Hub at https://docs.dea.ga.gov.au/data/product/dea-waterbodies-landsat/?tab=overview. Refer to the research paper Krause et al. 2021 for additional details: https://doi.org/10.3390/rs13081437

The update from version 2 to version 3.0 of the DEA Waterbodies product and service was created through a collaboration between Geoscience Australia, the National Aerial Firefighting Centre, Natural Hazards Research Australia, and FrontierSI to make the product more useful in hazard applications.

Geoscience Australia, the National Aerial Firefighting Centre, Natural Hazards Research Australia, and FrontierSI advise that the information published by this service comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, FrontierSI, Geoscience Australia, the National Aerial Firefighting Centre and Natural Hazards Research Australia (including its employees and consultants) are excluded from all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it.

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).

This dataset contains hotspot point data, derived from satellite-born instruments that detect light in the thermal wavelengths found on the Digital Earth Australia Hotspots application. Typically, satellite data are processed with a specific algorithm that highlights areas with an unusually high temperature. Hotspot sources include the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor aboard the National Aeronautics and Space Administration (NASA) Terra and Aqua satellites, the Advanced Very High Resolution Radiometer (AVHRR) night time imagery from the National Oceanic and Atmospheric Administration (NOAA) satellites, the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi- NPP satellite. Please note: As these data are stored on a Corporate system, we are only able to supply the web services (see download links).

email earth.observation@ga.gov.au.

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)

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.

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.

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.

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.

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).

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 Hotspots is a national bushfire monitoring system that provides timely information about hotspots to emergency service managers across Australia. The mapping system uses satellite sensors to detect areas producing high levels of infrared radiation (called Hotspots) to allow users to identify potential fire locations with a possible risk to communities and property. Digital Earth Australia Hotspots is not published in real time and should not be used for safety of life decisions.

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

The Digital Earth Australia notebooks and tools repository ("DEA notebooks") hosts Jupyter Notebooks, Python scripts and workflows for analysing Digital Earth Australia (DEA) satellite data and …Show full descriptionThe Digital Earth Australia notebooks and tools repository ("DEA notebooks") hosts Jupyter Notebooks, Python scripts and workflows for analysing Digital Earth Australia (DEA) satellite data and derived products. The repository is intended to provide a guide to getting started with DEA, and to showcase the wide range of geospatial analyses that can be achieved using DEA data and open-source software including Open Data Cube and xarray. DEA notebooks is a live Github project and is regularly updated. See the project wiki and readme for more detailed information.

Digital Earth Australia (DEA) Land Cover provides annual land cover classifications for Australia using the Food and Agriculture Organisation Land Cover Classification System taxonomy Version 2 (Di Gregorio and Jansen, 1998; 2005). DEA Land Cover translates over 30 years of satellite imagery into evidence of how Australia's land, vegetation and waterbodies have changed over time. Land cover is the observed physical cover on the Earth's surface including trees, shrubs, grasses, soils, exposed rocks, water bodies, plantations, crops and built structures. A consistent, Australia-wide land cover product helps understanding of how the different parts of the environment change and inter-relate. Earth observation data recorded over a period of time firstly allows the observation of the state of land cover at a specific time and secondly the way that land cover changes by comparison between times. For more information, please see the DEA Landcover Landsat This product is part of the Digital Earth Australia Program

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.

Value: These data are used to understand distributions of and changes in surface character, environmental systems, land use.

Scope: Australian mainland and some part of adjacent nations.

Access data via the DEA web page - https://www.dea.ga.gov.au/products/baseline-data

The Digital Earth Australia Hotspots web service has been developed as part of the Sentinel national bushfire monitoring system. The service delivers hotspots point data from (a growing number of) …Show full descriptionThe Digital Earth Australia Hotspots web service has been developed as part of the Sentinel national bushfire monitoring system. The service delivers hotspots point data from (a growing number of) satellite-born instruments that detect light in the thermal wavelengths. Typically, the satellite data are processed with a specific algorithm that highlights areas with an unusually high temperature. In principle, however, hotspots may be sourced from non-satellite sources. The hotspots are compiled for two uses: Public site and Secure site (access provided to authorised users only). The hotspots can be overlaid on the Landsat and Himawari-8 mosaic, MODIS burnt areas, NEXIS population data and landcover.

Background: Australia has a highly dynamic coastline of over 30,000 km, with over 85% of its population living within 50 km of the coast. This coastline is subject to a wide range of pressures, including extreme weather and climate, sea level rise and human development. Understanding how the coastline responds to these pressures is crucial to managing this region, from social, environmental and economic perspectives.

What this product offers: Digital Earth Australia Coastlines is a continental dataset that includes annual shorelines and rates of coastal change along the entire Australian coastline from 1988 to the present.

The product combines satellite data from Geoscience Australia's Digital Earth Australia program with tidal modelling to map the typical location of the coastline at mean sea level for each year. The product enables trends of coastal erosion and growth to be examined annually at both a local and continental scale, and for patterns of coastal change to be mapped historically and updated regularly as data continues to be acquired. This allows current rates of coastal change to be compared with that observed in previous years or decades.

The ability to map shoreline positions for each year provides valuable insights into whether changes to our coastline are the result of particular events or actions, or a process of more gradual change over time. This information can enable scientists, managers and policy makers to assess impacts from the range of drivers impacting our coastlines and potentially assist planning and forecasting for future scenarios.

Applications - Monitoring and mapping rates of coastal erosion along the Australian coastline - Prioritise and evaluate the impacts of local and regional coastal management based on historical coastline change - Modelling how coastlines respond to drivers of change, including extreme weather events, sea level rise or human development - Supporting geomorphological studies of how and why coastlines have changed across time

Abstract Digital Earth Australia Coastlines is a continental dataset that includes annual shorelines and rates of coastal change along the entire Australian coastline from 1988 to the present. The product combines satellite data from Geoscience Australia's Digital Earth Australia program with tidal modelling to map the most representative location of the shoreline at mean sea level for each year. The product enables trends of coastal retreat and growth to be examined annually at both a local and continental scale, and for patterns of coastal change to be mapped historically and updated regularly as data continues to be acquired. This allows current rates of coastal change to be compared with that observed in previous years or decades. The ability to map shoreline positions for each year provides valuable insights into whether changes to our coastline are the result of particular events or actions, or a process of more gradual change over time. This information can enable scientists, managers and policy makers to assess impacts from the range of drivers impacting our coastlines and potentially assist planning and forecasting for future scenarios. The DEA Coastlines product contains five layers:

Annual shorelines Rates of change points Coastal change hotspots (1 km) Coastal change hotspots (5 km) Coastal change hotspots (10 km)

Annual shorelines Annual shoreline vectors that represent the median or ‘most representative’ position of the shoreline at approximately 0 m Above Mean Sea Level for each year since 1988. Dashed shorelines have low certainty. Rates of change points A point dataset providing robust rates of coastal change for every 30 m along Australia’s non-rocky coastlines. The most recent annual shoreline is used as a baseline for measuring rates of change. Points are shown for locations with statistically significant rates of change (p-value <= 0.01; see sig_time below) and good quality data (certainty = "good"; see certainty below) only. Each point shows annual rates of change (in metres per year; see rate_time below), and an estimate of uncertainty in brackets (95% confidence interval; see se_time). For example, there is a 95% chance that a point with a label -10.0 m (±1.0 m) is retreating at a rate of between -9.0 and -11.0 metres per year. Coastal change hotspots (1 km, 5 km, 10 km) Three points layers summarising coastal change within moving 1 km, 5 km and 10km windows along the coastline. These layers are useful for visualising regional or continental-scale patterns of coastal change. Currency Date modified: August 2023 Modification frequency: Annually Data extent Spatial extent North: -9° South: -44° East: 154° West: 112° Temporal extent From 1988 to Present Source information

Product description and metadata Digital Earth Australia Coastlines catalog entry Data download Interactive Map

Lineage statement The DEA Coastlines product is under active development. A full and current product description is best sourced from the DEA Coastlines website. For a full summary of changes made in previous versions, refer to Github. Data dictionary Layer attribute columns Annual shorelines

Attribute name Description

OBJECTID Automatically generated system ID

year The year of each annual shoreline

certainty A column providing important data quality flags for each annual shoreline (see the Quality assurance section of the product description and metadata page for more detail about each data quality flag)

tide_datum The tide datum of each annual shoreline (e.g. "0 m AMSL")

id_primary The name of the annual shoreline's Primary sediment compartment from the Australian Coastal Sediment Compartments framework

Rates of change points and Coastal change hotspots

Attribute name Description

OBJECTID Automatically generated system ID

uid A unique geohash identifier for each point

rate_time Annual rates of change (in metres per year) calculated by linearly regressing annual shoreline distances against time (excluding outliers). Negative values indicate retreat and positive values indicate growth

sig_time Significance (p-value) of the linear relationship between annual shoreline distances and time. Small values (e.g. p-value < 0.01 or 0.05) may indicate a coastline is undergoing consistent coastal change through time

se-time Standard error (in metres) of the linear relationship between annual shoreline distances and time. This can be used to generate confidence intervals around the rate of change given by rate_time (e.g. 95% confidence interval = se_time * 1.96).

outl_time Individual annual shoreline are noisy estimators of coastline position that can be influenced by environmental conditions (e.g. clouds, breaking waves, sea spray) or modelling issues (e.g. poor tidal modelling results or limited clear satellite observations). To obtain reliable rates of change, outlier shorelines are excluded using a robust Median Absolute Deviation outlier detection algorithm, and recorded in this column

dist_1990, dist_1991, etc Annual shoreline distances (in metres) relative to the most recent baseline shoreline. Negative values indicate that an annual shoreline was located inland of the baseline shoreline. By definition, the most recent baseline column will always have a distance of 0 m

angle_mean, angle_std The mean angle and standard deviation between the baseline point to all annual shorelines. This data is used to calculate how well shorelines fall along a consistent line; high angular standard deviation indicates that derived rates of change are unlikely to be correct

valid_obs, valid_span The total number of valid (i.e. non-outliers, non-missing) annual shoreline observations, and the maximum number of years between the first and last valid annual shoreline

sce Shoreline Change Envelope (SCE). A measure of the maximum change or variability across all annual shorelines, calculated by computing the maximum distance between any two annual shorelines (excluding outliers). This statistic excludes sub-annual shoreline variability like tides, storms and seasonal effects

nsm Net Shoreline Movement (NSM). The distance between the oldest (1988) and most recent annual shoreline (excluding outliers). Negative values indicate the coastline retreated between the oldest and most recent shoreline; positive values indicate growth. This statistic does not reflect sub-annual shoreline variability, so will underestimate the full extent of variability at any given location

max_year, min_year The year that annual shorelines were at their maximum (i.e. located furthest towards the ocean) and their minimum (i.e. located furthest inland) respectively (excluding outliers). This statistic excludes sub-annual shoreline variability

certainty A column providing important data quality flags for each annual shoreline (see the Quality assurance section of the product description and metadata page for more detail about each data quality flag)

id_primary The name of the point's Primary sediment compartment from the Australian Coastal Sediment Compartments framework

Contact Geoscience Australia, clientservices@ga.gov.au

Geoscience Australia (GA) has acquired Landsat satellite image data over Australia since 1979, from instruments including the Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS). This data represents raw telemetry which has either been received directly at Geoscience Australia’s (GAs) receiving stations (Alice Springs or – formerly - Hobart), or downloaded from the United States Geological Survey Organisation. The data is maintained in raw telemetry format as a baseline to downstream processes. While this data has been used extensively for numerous land and coastal mapping studies, its utility for accurate monitoring of environmental resources has been limited by the processing methods that have been traditionally used to correct for inherent geometric and radiometric distortions in EO imagery. To improve access to Australia’s archive of Landsat TM/ETM+/OLI data, several collaborative projects have been undertaken in conjunction with industry, government and academic partners. These projects have enabled implementation of a more integrated approach to image data correction that incorporates normalising models to account for atmospheric effects, BRDF (Bi-directional Reflectance Distribution Function) and topographic shading (Li et al., 2012). The approach has been applied to Landsat TM/ETM+ and OLI imagery to create the surface reflectance products. Value: The Landsat Raw Data Archive is processed and further calibrated to input to development of information products toward an improved understanding of the distribution and status of environmental phenomena. Scope: Data is provided via the US Geological Survey's (USGS) Landsat program, following downlink and recording of the data at Alice Springs Antenna (operated by Geoscience Australia) or downloaded directly from USGS EROS To view the entire collection click on the keyword "HVC 144643" in the below Keyword listing

The Digital Earth Australia (DEA) Coastlines Explorer application shows annual shorelines and rates of coastal change along the entire Australian coastline from 1988 to the present.The application uses satellite data from Geoscience Australia's DEA program and tidal modelling to map the shoreline at mean sea level for each year. It enables annual analysis of coastal retreat and growth at both local and national scales. Patterns of coastal change can be mapped historically and updated regularly as new data becomes available. This allows current rates of coastal change to be compared with those from previous years or decades.Mapping shoreline positions each year provides valuable insights into whether changes are caused by specific events or gradual processes. This information helps scientists, managers and policy makers assess the impacts of various coastal drivers impacting our coastlines and supports planning and forecasting for future scenarios.The DEA Coastlines Explorer application contains three layers:DEA Coastlines annual shorelinesDEA Coastlines rates of coastal changeDEA Coastlines coastal change hotspotsDEA Coastlines annual shorelinesThis layer shows the position of the Australian coastline each year since 1988. It represents the most typical location of the shoreline at mean sea level.Each year's coastline is shown as a line on the map. If the line is dashed, it means there is lower certainty in the accuracy of that year's data.DEA Coastlines rates of coastal changeThis layer provides robust rates of coastal change for every 30 m along Australia’s non-rocky coastlines. The most recent annual shoreline is used as a baseline for measuring rates of change.Points are shown where the rate of change is statistically significant (p-value ≤ 0.01) and data quality is high (certainty = "good"). Each point shows the annual rates of change (in metres per year) and an uncertainty estimate (95% confidence interval).For example, for a point labelled -10.0 m (±1.0 m) there is a 95% chance the shoreline is retreating at a rate between -9.0 and -11.0 metres per year.DEA Coastlines coastal change hotspotThis merged layer summarises coastal change within moving 1 km, 5 km, and 10 km windows along the coastline. This layer helps visualise regional and national patterns of coastal change.Each layer includes all attributes from the DEA Coastlines rates of coastal change dataset, plus additional attributes that highlight significant coastal change.For more information, visit the DEA Coastlines - DEA Knowledge Hub.Key FeaturesTimeline: To analyse and visualise temporal data patterns over multiple years.Bookmark: Feature to guide users through the data and insights. CurrencyDate modified: 15 July 2025Modification frequency: As needed. Refer to individual layers for layer currency. ChangelogVersion 1.0.0 (2025-07-15)Experience Builder application created with the following features:LegendLayerAdd dataBasemapPrintShareBookmarksTimelineDrawSelectMeasureCoordinatesTable ContactDigital Earth Australia, earth.observation@ga.gov.au

Digital Earth Australia (DEA) Water Observations uses an algorithm to classify each pixel from Landsat satellite imagery as 'wet', 'dry', or 'invalid'. Water Observations Statistics provides information on how many times each year the Landsat satellites were able to clearly see an area, how many times those observations were wet, and what that means for the percentage of time that water was observed in the landscape. Combining the classified pixels into summaries covering each year gives the information on where water is usually, and where it is rarely. As no confidence filtering is applied to this product, it is affected by noise where misclassifications have occurred in the input water classifications, and can be difficult to interpret on its own. For more information, please see the DEA Water Observations Statistics Landsat This product is part of the Digital Earth Australia Program

Lake George water levels for the period 1987–2019, estimated using Landsat and Sentinel satellite imagery. Data were obtained by performing a query of the Open Data Cube (ODC; Open Data Cube, 2020) Landsat and Sentinel archive using scripts from the Digital Earth Australia Notebooks repository (Geoscience Australia, 2020). These images were subsequently processed to estimate lake depths based on the Lake George area/depth relationship presented in Dataset I. Refer to the Australian Journal of Earth Sciences article associated with these datasets for more information on the imagery processing methods.Geoscience Australia (2020, January). Digital Earth Australia Notebooks GitHub Repository. https://github.com/GeoscienceAustralia/dea-notebooksOpen Data Cube (2020, January). Open Data Cube. https://www.opendatacube.org/