Product catalogue
Landsat 30+ Barest Earth
An estimate of the spectra of the barest state (i.e., least vegetation) observed from imagery of the Australian continent collected by the Landsat 5, 7, and 8 satellites over a period of more than 30 years (1983 – 2018). The bands include BLUE (0.452 - 0.512), GREEN (0.533 - 0.590), RED, (0.636 - 0.673) NIR (0.851 - 0.879), SWIR1 (1.566 - 1.651) and SWIR2 (2.107 - 2.294) wavelength regions. The approach is robust to outliers (such as cloud, shadows, saturation, corrupted pixels) and also maintains the relationship between all the spectral wavelengths in the spectra observed through time. The product reduces the influence of vegetation and allows for more direct mapping of soil and rock mineralogy. This product complements the Landsat-8 Barest Earth which is based on the same algorithm but just uses Landsat8 satellite imagery from 2013-2108. Landsat-8’s OLI sensor provides improved signal-to-noise radiometric (SNR) performance quantised over a 12-bit dynamic range compared to the 8-bit dynamic range of Landsat-5 and Landsat-7 data. However the Landsat 30+ Barest Earth has a greater capacity to find the barest ground due to the greater temporal depth.
Reference: Exposed Soil and Mineral Map of the Australian Continent Revealing the Land at its Barest - Dale Roberts, John Wilford and Omar Ghattas Ghattas (2019). Nature Communications, DOI: 10.1038/s41467-019-13276-1.
Simple
Identification info
- Date (Creation)
- 2018-09-21T05:03:36
- Date (Publication)
- 2019-01-25T00:31:56
- Date (Revision)
- 2019-04-09T01:08:54
- Date (Revision)
- 2019-11-25T06:10:18
- Date (Revision)
- 2019-11-25T06:10:48
- Edition
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2.0.0
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/131897
- Cited responsible party
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Role Organisation / Individual Name Details Owner Commonwealth of Australia (Geoscience Australia)
Voice Author Wilford, J.
Author Roberts, D.
- Point of contact
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Role Organisation / Individual Name Details Point of contact Minerals, Energy and Groundwater Division
External Contact Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Thomas, M.
MEG Internal Contact
- Topic category
-
- Geoscientific information
Extent
))
Temporal extent
- Time period
- 2013-05-01 2018-09-20
- Maintenance and update frequency
- Annually
- Keywords
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Satellite imagery
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- Keywords
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Bare earth
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- Keywords
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Soil mineralogy
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- Keywords
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Rock mineralogy
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- Keywords
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Landsat 8
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- Keywords
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imagery soil, regolith and geology
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- Keywords
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Published_External
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Resource constraints
- Title
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Creative Commons Attribution 4.0 International Licence
- Alternate title
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CC-BY
- Edition
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4.0
- Access constraints
- License
- Use constraints
- License
Resource constraints
- Title
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Australian Government Security ClassificationSystem
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
- Language
- English
- Character encoding
- UTF8
Distribution Information
- Distributor contact
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
Voice
- OnLine resource
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Link to NCI THREDDS
Link to NCI THREDDS
- Distribution format
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html
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- OnLine resource
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Link to AWS
Link to AWS
- Distribution format
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- OnLine resource
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Link to GSKY web service
Link to GSKY web service
- OnLine resource
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Link to AWS web service
Link to AWS web service
Resource lineage
- Statement
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Large-scale image composites are increasingly important for a variety of applications such as land cover mapping, change detection, and the generation of high-quality data to parameterise and validate bio-physical and geophysical models. A number of compositing methodologies are being used in remote sensing in general, however challenges such as maintaining the spectral relationship between bands, mitigating against boundary artifacts due to mosaicking scenes from different epochs, and ensuring spatial regularity across the mosaic image still exist.
The creation of good composite images is a particularly important technology since the opening of the Landsat archive by the United States Geological Survey. The greater availability of satellite imagery has resulted in demand to provide large regional mosaics that are representative of conditions over specific time periods while also being free of clouds and other unwanted image noise. One approach is the stitching together of a number of clear images. Another is the creation of mosaics where pixels from different epochs are combined based on some algorithm from a time series of observations. This ‘pixel composite’ approach to mosaic generation provides a more consistent result compared with stitching clear images due to the improved color balance created by the combining of one-by-one pixel representative images. Another strength of pixel-based composites is their ability to be automated for application to very large data collections and time series such as national satellite data archives.
The Bare Earth pixel composite mosaic (BE-PCM) provides an approach that leverages high-dimensional statistical theory to deliver a spectrally consistent, artefact-free pixel composite product that is representative of the barest (i.e., least vegetation) state at each pixel over the specific time period.
The BE-PCM is derived from Landsat-8 OLI observations from 2013 to September 2018 corrected to measurements of NBAR surface reflectance (e.g., SR-N_25_2.0.0 or SR-NT_25_2.0.0). The data are masked for cloud, shadows and other image artefacts using the pixel quality product (PQ_25_2.0.0) to help provide as clear a set of observations as possible from which to calculate the BE-PCM.
The BE-PCM methodology and algorithm is given in Roberts, Wilford, Ghattas (2018). The technology builds on the earlier work of Roberts et al. (2017) where a method for producing cloud-free pixel composite mosaics using ‘geometric medians’ was proposed.
Note: The constituent pixels in the BE-PCM pixel composite mosaics are synthetic, meaning that the pixels have not been physically observed by the satellite. Rather they are the computed high-dimensional median of a time series of pixels which gives a robust estimate of the median state of the Earth at its barest (i.e., least vegetation).
References
Roberts, D., Wilford, J., Ghattas, O. (2018). Revealing the Australian Continent at its Barest. Submitted and under review.
Roberts, D., Mueller, N., Mcintyre, A. (2017). High-dimensional pixel composites from earth observation time series.
IEEE Transactions on Geoscience and Remote Sensing 55 (11), 6254-6264
- Hierarchy level
- Dataset
- Description
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Please refer to the lineage section.
Metadata constraints
- Title
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Australian Government Security ClassificationSystem
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Metadata
- Metadata identifier
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urn:uuid/0621fb28-69fb-4f2d-a0a6-469a35e28984
- Title
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GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
- Contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Thomas, M.
MEG Internal Contact
Type of resource
- Resource scope
- Dataset
Alternative metadata reference
- Title
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Geoscience Australia - short identifier for metadata record with
uuid
- Citation identifier
- eCatId/131897
- Date info (Revision)
- 2018-05-01T11:20:35
- Date info (Creation)
- 2018-05-01T11:20:35
Metadata standard
- Title
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AU/NZS ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-3
- Title
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
- Edition
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Version 2.0, September 2018
- Citation identifier
- https://pid.geoscience.gov.au/dataset/ga/122551