Product catalogue
Enhanced barest earth Landsat imagery for soil and lithological modelling: Dataset
<b>Please Note:</b> The data related to this Abstract can be obtained by contacting <a href = "mailto: clientservices@ga.gov.au">Manager Client Services</a> and quoting Catalogue number 144231. The data are arranged by regions, so please download the Data Description document found in the Downloads tab to determine your area of interest. clientservices@ga.gov <b>Please Note:</b> The data related to this Abstract can be obtained by contacting <a href = "mailto: clientservices@ga.gov.au">Manager Client Services</a> and quoting Catalogue number 144231. The data are arranged by regions, so please download the Data Description document found in the Downloads tab to determine your area of interest.
Remotely sensed datasets provide fundamental information for understanding the chemical, physical and temporal dynamics of the atmosphere, lithosphere, biosphere and hydrosphere. Satellite remote sensing has been used extensively in mapping the nature and characteristics of the terrestrial land surface, including vegetation, rock, soil and landforms, across global to local-district scales. With the exception of hyper-arid regions, mapping rock and soil from space has been problematic because of vegetation that either masks the underlying substrate or confuses the spectral signatures of geological materials (i.e. diagnostic mineral spectral features), making them difficult to resolve. As part of the Exploring for the Future program, a new barest earth Landsat mosaic of the Australian continent using time-series analysis significantly reduces the influence of vegetation and enhances mapping of soil and exposed rock from space. Here, we provide a brief background on geological remote sensing and describe a suite of enhanced images using the barest earth Landsat mosaic for mapping surface mineralogy and geochemistry. These geological enhanced images provide improved inputs for predictive modelling of soil and rock properties over the Australian continent. In one case study, use of these products instead of existing Landsat TM band data to model chromium and sodium distribution using a random forest machine learning algorithm improved model performance by 28–46%.
Simple
Identification info
- Date (Creation)
- 2020-06-29
- Date (Publication)
- 2020-08-25
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/144231
- Citation identifier
- Digital Object Identifier/https://doi.org/10.26186/144231
- Cited responsible party
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Role Organisation / Individual Name Details Author Wilford, J.
Author Roberts, D.
- Purpose
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Dataset
- Status
- Completed
- Point of contact
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Role Organisation / Individual Name Details Resource provider Minerals, Energy and Groundwater Division
External Contact Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Thomas, M.
MEG Internal Contact
- Spatial representation type
- Topic category
-
- Geoscientific information
Extent
Temporal extent
- Time period
- 1980-01-01
Extent
))
- Maintenance and update frequency
- As needed
Resource format
- Title
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Product data repository: Various Formats
- Website
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Data Store directory containing the digital product files
Data Store directory containing one or more files, possibly in a variety of formats, accessible to Geoscience Australia staff only for internal purposes
- theme.ANZRC Fields of Research.rdf
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EARTH SCIENCES
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- Theme
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remote sensing
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- Project
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EFTF
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- Keywords
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Satellite imagery
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- Keywords
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Soils
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- Keywords
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Rock
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- Keywords
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Mineralogy
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- Keywords
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Landsat TM
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- Keywords
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Exploring for the Future
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- Keywords
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Surface
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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
-
4.0
- Access constraints
- License
- Use constraints
- License
Resource constraints
- Title
-
Australian Government Security ClassificationSystem
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Associated resource
- Association Type
- Informed
- Title
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Enhanced barest earth Landsat imagery for soil and lithological modelling
- Citation identifier
- 134472
- Citation identifier
- d18c6065-83b3-4ec0-b92c-cfea6810b0fe
- 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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Data Description (pdf) [125 KB]
Data Description (pdf) [125 KB]
- Distribution format
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pdf
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- OnLine resource
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Link to related Abstract
Link to related Abstract
- Distribution format
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html
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Resource lineage
- Statement
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The landsat image enhancements describe in the paper are based on the barest earth dataset explained in Roberts D., Wilford J. & Ghattas O., 2019. Exposed soil and mineral map of the Australian continent revealing the land at its barest. Nature Communications 10:5297.
Metadata constraints
- Title
-
Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Metadata
- Metadata identifier
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urn:uuid/3ed5aec2-cf92-4c60-8485-a3c0d4c6fe2a
- Title
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GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
- Contact
-
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
- Name
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Dataset
Alternative metadata reference
- Title
-
Geoscience Australia - short identifier for metadata record with
uuid
- Citation identifier
- eCatId/144231
- Date info (Creation)
- 2019-04-08T01:55:29
- Date info (Revision)
- 2019-04-08T01:55:29
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