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Data

Enhanced Bare Earth Covariates for Soil and Lithological Modelling 

Ver: 1.0
Status of Data: completed
Update Frequency: notPlanned
Security Classification: unclassified
Dataset Published: 2021-02-19
Dataset Last Modified: 2026-07-07
Metadata viewed 16966 times
Dataset accessed 356 times
Metadata Created: 2020-12-14
Metadata Last Modified: 2026-08-19
How to cite this collection:
Wilford, J. & Roberts, D. (2021). Enhanced Bare Earth Covariates for Soil and Lithological Modelling. Version 1.0. Terrestrial Ecosystem Research Network. Dataset. https://portal.tern.org.au/metadata/d39e4f2c-f771-4aef-99f8-1e624f416955 
Data can be accessed from the following links:
HTTPData
HTTPPoint-of-truth metadata URL
HTTPro-crate-metadata.json
This dataset consists of bare earth covariates designed to indicate the presence of iron oxides, ferrous minerals, quartz/carbonate and hydroxyl minerals, to support soil and lithological modelling across Australia.
Bare earth layers (bands) represent the weighted geometric median of pixel values derived from a 30 year time-series of Landsat 5, 7 and 8 imagery converted to at-surface-reflectance, using the latest techniques to reduce the influence of vegetation (see Publications: Roberts, Wilford & Ghattas 2019). Bare earth layers are (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.
Covariates are then derived from principal components analysis and ratios of specific bare earth layers to target identification of elements of surface geochemistry. Layers are available as mosaics or tiles in 30 or 90 metre resolution. 
Credit
We at TERN acknowledge the Traditional Owners and Custodians throughout Australia, New Zealand and all nations. We honour their profound connections to land, water, biodiversity and culture and pay our respects to their Elders past, present and emerging. This work is part of the Exploring for the Future program and was completed by Geoscience Australia and Australian National University supported by TERN Landscapes https://www.tern.org.au/tern-observatory/tern-landscapes/ 
Purpose
As part of the Exploring for the Future program, the 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 (see Publications: Roberts et al 2019). 
Lineage
Data not provided. 
Method DocumentationData not provided.
Procedure StepsData not provided.
Spatial Description
Data not provided. 
Temporal Coverage
From 1983-03-16 to 2018-06-30 
Spatial Resolution

Data not provided.

Vertical Extent

Data not provided.

Data Quality Assessment Scope
The bare earth algorithm uses a weight geo-median approach to reduce noise and generate a robust estimate of the spectral response of the barest state (i.e. least vegetated) across the whole continent. The geo-median approach also tends to remove variations in soil moisture. A mask is used within the barest earth workflow to remove cloud (see Roberts et. al 2019).
Predictions were made for chromium and sodium for a region in Western Australia, comparing machine learning results for barest earth and non-barest earth datasets to reference geochemical survey data. 
Data Quality Report
Data not provided. 
Data Quality Assessment Outcome
The bare earth bands were assessed over a local calibration site near Canberra and were compared with a soil spectral datasets. All bands showed a reduction in the influence of green vegetation spectral responses (see Roberts et. al 2019).
R-squared results using the random forest algorithm were 0.3 (non–barest earth) and 0.44 (barest earth) for sodium, and 0.36 (non–barest earth) and 0.46 (barest earth) for chromium, representing a ~46% and ~28% improvement in model performance for sodium and chromium, respectively. 
ANZSRC - FOR
Inorganic geochemistry
Other earth sciences not elsewhere classified
Soil chemistry and soil carbon sequestration (excl. carbon sequestration science)
Data Stream
Soil and Landscape Grid
GCMD Sciences
ELEMENTS
ROCKS/MINERALS/CRYSTALS
SOILS
Horizontal Resolution
30 meters - < 100 meters
Instruments
ETM+
OLI
TM
Parameters
at-surface reflectance
bedrock index (Red-to-Green ratio)
bedrock index (SWIR2-to-Red ratio)
carbonate/quartz index (BLUE-to-SWIR2 ratio)
ferric iron index (PC2 of RED and BLUE)
ferric iron index (PC4 of BLUE, RED, NIR and SWIR1)
ferrous minerals index (SWIR1-to-NIR)
ferruginous-to-non-ferruginous regolith index (NIR-to-Green ratio)
hydroxyl minerals index (PC1 of SWIR1-to-SWIR2 and NIR-to-RED)
hydroxyl minerals index (PC2 of SWIR1-to-SWIR2 and NIR-to-RED)
hydroxyl minerals index (PC2 of SWIR1, SWIR2)
hydroxyl minerals index (PC3 of BLUE, NIR, SWIR1, SWIR2)
hydroxyl minerals index (PC4 of BLUE, NIR, SWIR1, SWIR2)
hydroxyl minerals index (SWIR1-to-SWIR2)
iron oxide and bedrock index (SWIR1-to-Blue ratio)
iron oxide index (Red-to-Blue ratio)
iron oxide index (SWIR2-to-Green ratio)
iron oxide index (SWIR2-to-NIR ratio)
Platforms
LANDSAT-5
LANDSAT-7
LANDSAT-8
Project
TERN Landscapes
Temporal Resolution
Weekly - < Monthly
Topic
geoscientificInformation
imageryBaseMapsEarthCover
User Defined
regolith
Author
Wilford, John
Roberts, Dale
Contact Point
Wilford, John
Publisher
Terrestrial Ecosystem Research Network
Enhanced Barest Earth Landsat Imagery for Soil and Lithological Modelling (documentation on AusSoilsDSM website)
Wilford, J. and Roberts, D., (2020) Enhanced barest earth Landsat imagery for soil and lithological modelling. In: Czarnota, K.(et al) (eds.) Exploring for the Future: Extended Abstracts, Geoscience Australia, Canberra, 1–4.
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.
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
TERN Digital Soil Modelling Covariates Viewer
Supplemental Information
Tile locations are provided as .png file within the zip. See ReadMe.txt for details. 
Resource Specific Usage
The enhanced products are based on standard processing techniques for enhancing surface mineralogy. However relationships my vary across different regions and it is recommended that the user takes this into account when interpreting the data and assesses against local geology and landforms. 
Environment Description
Data not provided. 
Terrestrial Ecosystem Research Network
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Creative Commons Attribution 4.0 International Licence
https://creativecommons.org/licenses/by/4.0/
The Creative Commons Attribution 4.0 International (CC BY 4.0) license allows others to copy, distribute, display, and create derivative works provided that they credit the original source and any other nominated parties. Details are provided at https://creativecommons.org/licenses/by/4.0/ 
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Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.

Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting 
Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}. 
TERN services are provided on an "as-is" and "as available" basis. Users use any TERN services at their discretion and risk. They will be solely responsible for any damage or loss whatsoever that results from such use including use of any data obtained through TERN and any analysis performed using the TERN infrastructure.
Web links to and from external, third party websites should not be construed as implying any relationships with and/or endorsement of the external site or its content by TERN.

Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting