DEA Water Observations (Landsat)

Version:: 2.0.0
Type:: Derivative, Raster
Resolution:: 30 m
Coverage:: 16 Aug 1986 to Present
Data updates:: Daily frequency, Ongoing

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Overview

About

Digital Earth Australia (DEA) Water Observations uses an algorithm to classify each pixel from Landsat satellite imagery as ‘wet’, ‘dry’ or ‘invalid’. Combining the classified pixels into summaries, covering a year, season, or all of time (since 1986) gives the information on where water is usually, and where it is rarely.

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Key specifications

For more specifications, see the Specifications tab.

Technical name	Geoscience Australia Landsat Water Observations Collection 3
Bands	Single band of data (water)
DOI	10.26186/146257
Currency	See currency and the latest update date
Parent product	Landsat 5, 7, 8 and 9 NBART and Observational Attributes
Collection	Geoscience Australia Landsat Collection 3
Tags	geoscience_australia_landsat_collection_3, water, water_detection, surface_water
Licence	Creative Commons Attribution 4.0 International Licence

Cite this product

Data citation

Geoscience Australia, 2022. DEA Water Observations. Geoscience Australia, Canberra. https://dx.doi.org/10.26186/146257

Paper citation

Mueller, N., Lewis, A., Roberts, D., Ring, S., Melrose, R., Sixsmith, J., Lymburner, L., McIntyre, A., Tan, P., Curnow, S., & 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. https://doi.org/10.1016/j.rse.2015.11.003

Publications

Mueller, N., Lewis, A., Roberts, D., Ring, S., Melrose, R., Sixsmith, J., Lymburner, L., McIntyre, A., Tan, P., Curnow, S., & 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. https://doi.org/10.1016/j.rse.2015.11.003

Description

Background

It is important to know where water is normally present in a landscape, where water is rarely observed, and where inundation has occasionally occurred.

These observations tell us where flooding has occurred in the past, and allows us to understand wetlands, water connectivity and surface-groundwater relationships. This can lead to more effective emergency management and risk assessment.

This is the principal Digital Earth Australia (DEA) Water product (previously known as Water Observations from Space (WOfS)), providing the individual water observations per satellite image that are subsequently used in the following DEA Water suite and related water bodies products: DEA Waterbodies (Landsat), DEA Water Observations Statistics (Landsat), DEA Water Observations Filtered Statistics (Landsat).

This product shows where surface water was observed by the Landsat satellites on any particular day since mid 1986. These daily data layers are termed Water Observations (WOs).

What this product offers

DEA Water Observations provides surface water observations derived from Landsat satellite imagery for all of Australia from 1986 to present.

The Water Observations show the extent of water in a corresponding Landsat scene, along with the degree to which the scene was obscured by clouds, shadows or where sensor problems cause parts of a scene to not be observable.

Applications

The DEA Water Observations (WOs) are used to determine the area of surface water present in the corresponding satellite scene, and can be used for several water monitoring applications. Uses of the individual WOs include:

flood extent
amount of water in water bodies, major rivers and the coastal zone.

As the WOs are separated from the derived statistics of the associated DEA Water statistical products, the WOs are most useful for performing analyses requiring the investigation of surface water extent for particular times rather than over long term time series.

Technical information

Digital Earth Australia (DEA) Water Observations (WOs) is a gridded dataset indicating areas where surface water has been observed using the Geoscience Australia (GA) Earth observation satellite data holdings. The current product (version 2.0.0) includes observations taken between 1986 and the present (inclusive) from the Landsat 5, 7, 8 and 9 satellites. WOs cover all of mainland Australia and Tasmania but exclude off-shore Territories. The dataset is updated automatically as each new Landsat scene is acquired and processed to Analysis Ready Data (ARD) state.

Data is provided as Water Observation Feature Layers (WOFLs), in a 1 to 1 relationship with the input satellite data. Hence there is one WOFL for each satellite dataset processed for the occurrence of water. The meaning of each bit in the WOFLs is given in the table below. Prior to version 1.6.0, only one bit could be set per pixel, therefore the value of a pixel in an observation could be X OR Y OR Z. Hence in previous versions the WOs values could only be 0 or 1 or 2 or 4 or … or 128. From version 1.6.0 onward the data type has been changed to a bit field, where multiple bits can be set simultaneously. Hence the value of a pixel in an observation can be X AND Y AND Z, etc, hence values can range from 0 to 255.

Version 1.6.0 was updated with changes to the way different factors impeding water detection are dealt with. These changes result in improved detection rates and allow discrimination of different factors impeding water observations. Masking of the ocean with a pre-defined mask has been removed, and the extent of the ocean is now defined by the algorithm. Masking for terrain and solar incident angle have been de-coupled in order to provide better visibility about the reason for masking. The solar incident angle threshold used to remove poor quality observations collected when the sun is at a very low angle has been reduced from 30 degrees to 10 degrees. This change increases the number of observations included in the dataset during winter months while still removing those that are most badly impacted by shadowing caused by low solar incident angle.

Version 2.0.0 introduces the integration of Landsat 9, providing an increase in available observations from November 2021 onwards.

The table below describes the meaning of each bit set per pixel in each WOFL. Where multiple factors impeding a clear observation are detected all the respective bits will be set. For example a value of 136 indicates water (128) AND terrain shadow (8) were observed for the pixel.

Bit	Flagging	Decimal Value	Description
0	no data	1	Pixel masked out due to NO_DATA in NBART source, 0 = valid data in NBART
1	contiguity	2	Pixel masked out due to lack of data contiguity
2	solar incidence	4	Pixel masked out due to solar incidence > 10 degrees
3	terrain shadow	8	Pixel masked out due to terrain shadow
4	high slope	16	Pixel masked out due to high slope
5	cloud shadow	32	Pixel masked out due to cloud shadow
6	cloud	64	Pixel masked out due to cloud
7	water	128	Water detected

Full details of the original algorithms and features of DEA Water Observations can be found in the Water Observations from Space paper by Mueller et al. (2015).

Lineage

Digital Earth Australia (DEA) Water Observations is derived from Landsat 5, 7, 8 and 9 imagery. Imagery is initially corrected to Analysis Ready Data (ARD) standard, and masked for cloud, cloud-shadow, data contiguity, steep slope, solar incidence angle, and terrain shadow. Water classification is achieved using a decision tree based on the individual spectral bands of the Landsat satellites and derived normalised difference indicies associated with water and vegetation. The output is then stored as an 8-bit, bit-field with values from 0 - 255 indicating the presence or absence of each mask type and the presence or absence of water.

Processing steps

The water detection algorithm used to detect water from each observed pixel is based on a statistical regression tree analysis of a set of normalised difference indices and corrected band values. The regression is based on a set of water and non-water samples created by visual interpretation of 20 Landsat scenes from across Australia. The sample locations ensure that the logistic regression is based on the full geographic range of conditions experienced in Australia.

The regression analysis determined a set of best indices and bands for the analysis and the associated thresholds in each component to derive a final classification tree, producing a water/non-water classification for each pixel in the Data Cube. The final water classification for each pixel is modified by Pixel Quality (see associated PQ product information) and terrain. Once the water algorithm has completed its process, the water detection for a pixel through time is combined to produce a total number of water observations for each pixel. This is compared to a total number of clear observations for the same pixel, derived from the PQ analysis. The ratio is expressed as a percentage water recurrence.

References

Quality

Accuracy

The accuracy of the original Water Observations from Space (WOfS) algorithms was assessed using an independent set of 3.4 million validation points. The points were identified based on visual interpretation of Landsat imagery within 20 test areas across Australia. The points were identified in the same locations as the training data, but were selected from different years (i.e. imagery from one set of years was used to generate points to train the algorithm, and imagery from a separate set of years was used to generate the points that were used evaluate the accuracy of the algorithm).

The classification has an overall accuracy of 97%. Areas identified as water within the accuracy assessment data are being correctly identified 93% of the time and are being misclassified as not water 7% of the time. These errors of omission typically occur along rivers, small waterbodies and swamps where the presence of both water and vegetation within the pixel leads a failure to identify water. This means that the DEA Water Observations product is likely to underestimate the extent of water in locations that contain mixed water and vegetation pixels. As a consequence of this the product may not be fit for applications that require information about the inundation characteristics of vegetated wetlands, small farm dams, and rivers less than 50 metres wide.

Water can be incorrectly detected by the classification algorithm in areas where steep terrain or tall buildings cause frequently shaded pixels. These errors of commission are occurring in 8% of samples used to evaluate the accuracy of the classification. This means that the product may overestimate the amount of water in locations that are adjacent to steep terrain or in dense urban areas. Terrain masks and urban masks were used in the confidence layer to reduce this overestimation, however some residual errors remain. As a consequence of this the product may not be fit for applications that require information about the inundation characteristics of urban areas or locations adjacent to steep terrain.

In addition to the limitations of the classification algorithm, the satellite observation frequency also introduces limitations to the product. The product is likely to be underestimating the extent of inundation for infrequent flood events because the 8 day revisit frequency (best case scenario notwithstanding the possibility of cloud obscuring the floodwaters) will potentially fail to observe the flood peak. This is an intrinsic limitation of the observation strategy. As a consequence of this limitation, the product is not suited to applications that require a. the identification of a ‘maximum extent of inundation’ line, or b. detailed information about the extent of infrequent flood events.

Limitations

Observation of Earth by the satellites used for this service depends on clear skies. Furthermore, the satellites do not observe all places every day. The Landsat satellites, which are the basis for this service, view a given 185 kilometre wide strip of Australia only once every 16 days. The observations show only what was visible on the day of the satellite pass. As a result, not all historical floods will have been observed by satellite.

The automated surface water detection algorithm, which has been developed by Geoscience Australia, can sometimes mistakenly label large buildings; cloud shadow; large uniform black tarpaulins; or snow as “water”. The algorithm is designed to locate large areas of water and as a result may miss small water bodies.

The satellite archive used for this service is of limited duration (1986 to present), and subject to the cloud and repeat coverage restrictions noted above. In addition, Australia is subject to wide variations in weather and climate. Therefore the absence of water observations prior to 1986 in a particular location does not provide certainty that surface water will never be observed there in future.

The probability that surface water may appear at a given location may vary over time due to changes in drainage and other infrastructure (such as dams). Where such changes have occurred, the historical water observations for that location may no longer give a true picture of the future probability of surface water being observed.

Specifications

Bands

Bands are distinct layers of data within a product that can be loaded using the Open Data Cube (on the DEA Sandbox or NCI) or DEA’s STAC API. Here are the bands of the product: ga_ls_wo_3.

	Aliases	Resolution	No-data	Units	Type	Description
water	-	30 m	1	-	uint8	-

For more information on these bands, see the Description tab.

Product information

This metadata provides general information about the product.

Product ID	ga_ls_wo_3	Used to load data from the Open Data Cube.
Short name	DEA Water Observations (Landsat)	The name that is commonly used to refer to the product.
Technical name	Geoscience Australia Landsat Water Observations Collection 3	The full technical name that refers to the product and its specific provider, sensors, and collection.
Version	2.0.0	The version number of the product. See the History tab.
Lineage type	Derivative	Derivative products are derived from other products.
Spatial type	Raster	Raster data consists of a grid of pixels.
Spatial resolution	30 m	The size of the pixels in the raster.
Temporal coverage	16 Aug 1986 to Present	The time span for which data is available.
Update frequency	Daily	The expected frequency of data updates. Also called ‘Temporal resolution’.
Update activity	Ongoing	The activity status of data updates.
Currency	See the Currency Report	Currency is a measure based on data publishing and update frequency.
Latest update date	Currency Report	See Table A of the report.
DOI	10.26186/146257	The Digital Object Identifier.
Catalogue ID	146257	The Data and Publications catalogue (eCat) ID.
Licence	Creative Commons Attribution 4.0 International Licence	See the Credits tab.

Product categorisation

This metadata describes how the product relates to other DEA products.

Parent product	Landsat 5, 7, 8 and 9 NBART and Observational Attributes
Collection	Geoscience Australia Landsat Collection 3
Tags	geoscience_australia_landsat_collection_3, water, water_detection, surface_water

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Code examples	View code examples	Learn how to use the DEA Sandbox.
Web services	Get via web service	Learn how to use DEA’s web services.

History

Version history

Versions are numbered using the Semantic Versioning scheme (Major.Minor.Patch). Note that this list may include name changes and predecessor products.

v2.0.0	-	Current version
v1.6.0	of	DEA Water Observations (Landsat)

Changelog

Version: 2.0.0

Landsat 9 was incorporated into this product starting in October 2021.

Credits

License and copyright

Released under Creative Commons Attribution 4.0 International Licence.