DEA Water Observations Statistics (Landsat)

ga_ls_wo_fq_apr_oct_3, ga_ls_wo_fq_nov_mar_3, ga_ls_wo_fq_cyear_3, ga_ls_wo_fq_myear_3

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

../../../_images/WOfS-Burketown-Normanton-QLD.png

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.

This version includes breaking changes

All tile grid references have been changed to refer to a new origin point. Learn more in the Version 2.0.0 changelog.

Access the data

For help accessing the data, see the Access tab.

Explore data availability

DEA Explorer

Apr-Oct summaries since 1986 - AWS access

Data sources

Nov-Mar summaries since 1986 - AWS access

Data sources

Annual calendar year summaries since 1986 - AWS access

Data sources

All-time summary 1986 to present - AWS access

Data sources

Apr-Oct summaries since 1986 - NCI access

Data sources

Nov-Mar summaries since 1986 - NCI access

Data sources

Annual calendar year summaries since 1986 - NCI access

Data sources

All-time summary 1986 to present - NCI access

Data sources

View code examples

Code examples

Get via web service

Web services

Key specifications

For more specifications, see the Specifications tab.

Technical name	Geoscience Australia Landsat Water Observation Statistics Collection 3
Bands	3 bands of data (count_wet, count_clear, and more)
DOI	10.26186/146091
Currency	See currency and the latest and next update dates
Parent product	DEA Water Observations (Landsat)
Collection	Geoscience Australia Landsat Collection 3
Tags	geoscience_australia_landsat_collection_3, surface_water, water_detection, floods, wetlands
Licence	Creative Commons Attribution 4.0 International Licence

Cite this product

Data citation

Mueller, N. 2022. Geoscience Australia Landsat Water Observation Statistics Collection 3. Geoscience Australia, Canberra. https://dx.doi.org/10.26186/146091

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

These are the statistics generated from the DEA Water Observations (Water Observations from Space) suite of products, which gives summaries of how often surface water was observed by the Landsat satellites for various periods (per year, per season and for the period from 1986 to the present).

Water Observations Statistics (WO-STATS) provides information on how many times 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.

What this product offers

Each dataset in this product consists of the following datasets:

Clear Count: how many times an area could be clearly seen (i.e. not affected by clouds, shadows or other satellite observation problems)
Wet Count: how many times water was detected in observations that were clear
Water Frequency: what percentage of clear observations were detected as wet (i.e. the ratio of wet to clear as a percentage)

Applications

Helps understand where flooding may have occurred in the past, to inform emergency management and risk assessment.
Provides an indication of the permanence of surface water in the Australian landscape by showing where water is observed rarely in comparison to where it is often observed, informing water management and mapping.
Can assist with wetland analyses, water connectivity and surface-ground water relationships.
The annual product provides information on how surface water changes per year across Australia, and is useful for drought analysis.
The seasonal product is useful for understanding the differences in water availability between the summer and winter periods across Australia.

Technical information

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.

WO-STATS is available in multiple forms, depending on the length of time over which the statistics are calculated. At present the following are available:

DEA WO Multi-Year: ga_ls_wo_fq_myear_3: statistics calculated from the full depth of time series (1986 to present) unfiltered
DEA WO Calendar Year: ga_ls_wo_fq_cyear_3: statistics calculated from each calendar year (1986 to present)
DEA WO November to March: ga_ls_wo_fq_nov_mar_3: statistics calculated yearly from November to March (1986 to present)
DEA WO April to October: ga_ls_wo_fq_apr_oct_3: statistics calculated yearly from April to October (1986 to present)

In addition, a confidence-filtered Multi-Year Summary is under development, which will contain a confidence layer and subsequent filtered water frequency layer. This provides a noise-reduced view of the unfiltered multi-year summary.

Lineage

This product is created from the WO water classification (Water Observations (Landsat)). Every pixel location is analysed statistically to derive the count of clear observations, the count of clear-wet observations and then to calculate the percentage of clear observations that were also wet. This provides a ‘normalised’ water frequency product for all of Australia.

Each product within the WO-STATS set is derived from the available Landsat observations within the respective period: calendar years; Apr-Oct each year; Nov-Mar each year; all-of-time (first available Landsat observation in the DEA archive to the most recent).

To create the confidence layer required for the filtered product, a logistic regression is created between the un-filtered product and information about terrain, built-up areas, and coarse national water observations. In this way the confidence reflects the likelihood that the observed water is scientifically feasible at every pixel.

Processing steps

Calculation of clear count, wet count and water summary (percentage of clear observations that are wet).

For each WO pixel through time:

count the number of clear observations (ie observations not masked by pixel quality for cloud, shadows or sensor issues) to produce clear count dataset;
count the number of clear observations that are wet to produce wet count dataset;
create the ratio of wet to clear from the wet and clear count datasets and produce as a percentage dataset.

References

Quality

Accuracy

Please refer to the Landsat Surface Reflectance Product Description for the accuracy and limitations of the atmospheric, BRDF and topographic shading processing sequence. Please refer to Mueller et al. 2016 for details on the accuracy and limitations of Water Observations from Space (WOfS and WOfS-STATS).

WO-STATS provides a summary of water classification results from the WOfS product for all of Australia. As it cannot perfectly filter out misclassifications due to clouds, cloud shadows and issues to do with satellite sensor problems (such as the Landsat 7 SLC-Off failure), the summary also contains these misclassifications. In general misclassifications occur in the very low frequency observations and so can cause a misrepresentation of flooded areas. Misclassifications can also be caused by the presence of vegetation covering the water or within the water.

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 products: ga_ls_wo_fq_apr_oct_3, ga_ls_wo_fq_nov_mar_3, ga_ls_wo_fq_cyear_3, ga_ls_wo_fq_myear_3.

	Aliases	Resolution	No-data	Units	Type	Description
count_wet	-	30 m	-999	-	int16	Wet Count: how many times water was detected in observations that were clear.
count_clear	-	30 m	-999	-	int16	Clear Count: how many times an area could be clearly seen.
frequency	-	30 m	NaN	-	float32	Water Frequency: what percentage of clear observations were detected as wet.

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

Product information

This metadata provides general information about the product.

Product IDs	ga_ls_wo_fq_apr_oct_3 ga_ls_wo_fq_nov_mar_3 ga_ls_wo_fq_cyear_3 ga_ls_wo_fq_myear_3	Used to load data from the Open Data Cube.
Short name	DEA Water Observations Statistics (Landsat)	The name that is commonly used to refer to the product.
Technical name	Geoscience Australia Landsat Water Observation Statistics 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	1986 to Present	The time span for which data is available.
Update frequency	Yearly	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 and next update dates	See the Currency Report	See Table B of the report.
DOI	10.26186/146091	The Digital Object Identifier.
Catalogue ID	146091	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	DEA Water Observations (Landsat)
Collection	Geoscience Australia Landsat Collection 3
Tags	geoscience_australia_landsat_collection_3, surface_water, water_detection, floods, wetlands

Access

Access the data

DEA Explorer	Explore data availability	Learn how to use the DEA Explorer.
Data sources	Apr-Oct summaries since 1986 - AWS access Nov-Mar summaries since 1986 - AWS access Annual calendar year summaries since 1986 - AWS access All-time summary 1986 to present - AWS access Apr-Oct summaries since 1986 - NCI access Nov-Mar summaries since 1986 - NCI access Annual calendar year summaries since 1986 - NCI access All-time summary 1986 to present - NCI access	Learn how to access the data via AWS.
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.

Access constraints

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 Statistics (Landsat)

Changelog

Version 2.0.0 released

Breaking change: Shift in grid origin point — The south-west origin point of the DEA Summary Product Grid has been shifted 18 tiles west and 15 tiles south. Therefore, all tile grid references have been changed. For instance, a tile reference of x10y10 has changed to x28y25. The tile grid references of all derivative products generated from 2024 onwards will also be changed; however, Analysis Ready Data products will not be affected.
Enhanced cloud masking to reduce noise — An enhancement to cloud masking has reduced cloud and shadow noise. This enhancement (known as ‘cloud buffering’) involved cleaning cloud masks using a 6-pixel dilation on cloud and shadows. Note that some areas of very high surface reflectance (e.g. sand dunes and ocean areas) may exhibit worsened noise or data gaps, but these are infrequent occurrences with low impact.
Landsat 9 product — Landsat 9 is processed from 2022 onwards.

2024-01-24: Water Observations 2023 annual summary released

Product id: ga_ls_wo_fq_cyear_3

To access the updated product, see the Access tab.

Credits

License and copyright

Released under Creative Commons Attribution 4.0 International Licence.

The code for DEA-WO and its derivatives is available through GitHub under Apache 2.0 Open licensing.