Enhanced Bare Earth Covariates for Soil and Lithological Modelling

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.

Identification info

Date (Creation): 1983-03-16

Date (Publication): 2021-02-19

Date (Revision): 2014-07-14

Edition: 1.0

Publisher

Terrestrial Ecosystem Research Network

Building 1019, 80 Meiers Rd

Indooroopilly

QLD

4068

Australia

+61 7 3365 9097

Author

Geoscience Australia - Wilford, John ()

Cnr Jerrabomberra Ave and Hindmarsh Drive, Symonston, ACT, 2609, Australia

Symonston

ACT

2609

Australia

+61 2 6246 5588

Author

Australian National University - Roberts, Dale ()

10 East Road, Acton, ACT, 2601, Australia

Acton

ACT

2601

Australia

+61 2 6246 5588

Website: https://www.tern.org.au/

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).

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.

Credit: 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/

Status: Completed

Point of contact

Geoscience Australia - Wilford, John ()

Cnr Jerrabomberra Ave and Hindmarsh Drive, Symonston, ACT, 2609, Australia

Cnr Jerrabomberra Ave and Hindmarsh Drive

Symonston

ACT

2609

Australia

02 6249 9182/9781

Topic category

Imagery base maps earth cover
Geoscientific information

Extent

Temporal extent

Time period: 1983-03-16 2018-06-30

Title: 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.

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.
Related documentation

Title: Enhanced Barest Earth Landsat Imagery for Soil and Lithological Modelling (documentation on AusSoilsDSM website)

Website: Enhanced Barest Earth Landsat Imagery for Soil and Lithological Modelling (documentation on AusSoilsDSM website)
Related documentation

Title: 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.

Website: 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.
Related documentation

Title: 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

Website: 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
Related documentation

Title: TERN Digital Soil Modelling Covariates Viewer

Website: TERN Digital Soil Modelling Covariates Viewer
Related documentation

Maintenance and update frequency: Not planned

GCMD Science Keywords

ANZSRC Fields of Research

TERN Platform Vocabulary

TERN Instrument Vocabulary

TERN Parameter Vocabulary

QUDT Units of Measure

GCMD Horizontal Resolution Ranges

30 meters - < 100 meters

GCMD Temporal Resolution Ranges

Weekly - < Monthly

Keywords (Discipline)

regolith

Resource specific usage

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.

Resource constraints

Use limitation: 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/

File name: 88x31.png

File description: CCBy Logo from creativecommons.org

File type: png

Linkage: https://w3id.org/tern/static/cc-by/88x31.png

Title: Creative Commons Attribution 4.0 International Licence

Alternate title: CC-BY

Edition: 4.0

Website: https://creativecommons.org/licenses/by/4.0/

Access constraints: License

Use constraints: Other restrictions

Other constraints: 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.

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

Other constraints: Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.

Resource constraints

Classification: Unclassified

Supplemental Information: Tile locations are provided as .png file within the zip. See ReadMe.txt for details.

Distribution Information

Distributor

Terrestrial Ecosystem Research Network

Building 1019, 80 Meiers Rd, Indooroopilly, QLD, Australia, 4068

Indooroopilly

QLD

4068

Australia

+61 2 3365 9097

OnLine resource: Data

Data quality info

Hierarchy level: Dataset

Other: 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.

Report

Result

Statement: 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.

Resource lineage

Statement: The Bare Earth Pixel Composite Model (BE-PCM) is derived from Landsat-5, 7 and 8 observations from 1986 - 2018 corrected to measurements of NBAR surface reflectance. 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).

Hierarchy level: Dataset

Process step

Description: ferric iron index (PC2 of BLUE and RED): The second component (PC2) of BLUE and RED wavelengths of the electromagnetic spectrum transformed by Principal Components Analysis (PCA) to reduce correlation and noise, refer to data file Other_FERRIC-PC2

Process step

Description: ferric iron index (PC4 of BLUE, RED, NIR and SWIR1): The fourth component (PC4) of BLUE, RED, NIR and SWIR1 wavelengths of the electromagnetic spectrum transformed by Principal Components Analysis (PCA) to reduce correlation and noise, refer to data file Other_FERRIC-PC4

Process step

Description: hydroxyl minerals index (SWIR1/SWIR2): The normalised difference index of Enhanced Bare Earth bands calculated as ((SWIR1 - SWIR2) / (SWIR1 + SWIR2)), refer to data file Other_ND-SWIR1-SWIR2

Process step

Description: hydroxyl minerals index (PC2 of SWIR1/SWIR2 and NIR/RED): The second component (PC2) of SWIR1/SWIR2 and NIR/RED wavelengths of the electromagnetic spectrum transformed by Principal Components Analysis (PCA) to reduce correlation and noise. Based on a directed PCA approach that tries to separate clay from vegetation (Fraser S. J. & Green A. A., 1987. A software defoliant for geological analysis of band ratios. International Journal of Remote Sensing). Refer to data file Other_HYDROXYL-1-PC2

Process step

Description: hydroxyl minerals index (PC1 of SWIR1/SWIR2 and NIR/RED): The first component (PC1) of SWIR1/SWIR2 and NIR/RED wavelengths of the electromagnetic spectrum transformed by Principal Components Analysis (PCA) to reduce correlation and noise. Based on a directed PCA approach that tries to separate clay from vegetation (Fraser S. J. & Green A. A., 1987. A software defoliant for geological analysis of band ratios. International Journal of Remote Sensing). Refer to data file Other_HYDROXYL-1-PC1

Process step

Description: hydroxyl minerals index (PC2 of SWIR1 and SWIR2): The second component (PC2) of SWIR1 and SWIR2 wavelengths of the electromagnetic spectrum transformed by Principal Components Analysis (PCA) to reduce correlation and noise. Based on a directed PCA approach that tries to separate clay from vegetation (Fraser S. J. & Green A. A., 1987. A software defoliant for geological analysis of band ratios. International Journal of Remote Sensing). Refer to data file Other_HYDROXYL-2-PC2

Process step

Description: hydroxyl minerals index (PC3 of BLUE, NIR, SWIR1 and SWIR2): The third component (PC3) of BLUE, NIR, SWIR1, SWIR2 wavelengths of the electromagnetic spectrum transformed by Principal Components Analysis (PCA) to reduce correlation and noise. Based on a directed PCA approach that tries to separate clay from vegetation (Fraser S. J. & Green A. A., 1987. A software defoliant for geological analysis of band ratios. International Journal of Remote Sensing). Refer to data file Other_HYDROXYL-3-PC3

Process step

Description: hydroxyl minerals index (PC4 of BLUE, NIR, SWIR1 and SWIR2): The fourth component (PC4) of BLUE, NIR, SWIR1, SWIR2 wavelengths of the electromagnetic spectrum transformed by Principal Components Analysis (PCA) to reduce correlation and noise. Based on a directed PCA approach that tries to separate clay from vegetation (Fraser S. J. & Green A. A., 1987. A software defoliant for geological analysis of band ratios. International Journal of Remote Sensing). Refer to data file Other_HYDROXYL-3-PC4

Process step

Description: iron oxide index (RED/BLUE): The normalised difference index of Enhanced Bare Earth bands calculated as ((RED - BLUE) / (RED + BLUE)), refer to data file Other_ND-RED-BLUE

Process step

Description: iron oxide index (SWIR2/NIR): The normalised difference index of Enhanced Bare Earth bands calculated as (((SWIR2 - NIR) / (SWIR2 + NIR)), refer to data file Other_ND-SWIR2-NIR

Process step

Description: iron oxide and bedrock index (SWIR1/BLUE): The normalised difference index of Enhanced Bare Earth bands calculated as ((SWIR1 - BLUE) / (SWIR1 + BLUE)), refer to data file Other_ND-SWIR1-BLUE

Process step

Description: iron oxide/bedrock index (SWIR1/NIR): The normalised difference index of Enhanced Bare Earth bands calculated as ((SWIR1 - NIR) / (SWIR1 + NIR)), refer to data file Other_ND-SWIR1-NIR

Process step

Description: iron oxide/bedrock index (RED/GREEN): The normalised difference index of Enhanced Bare Earth bands calculated as ((RED - GREEN) / (RED + GREEN)), refer to data file Other_ND-RED-GREEN

Process step

Description: iron oxide index (SWIR2/GREEN): The normalised difference index of Enhanced Bare Earth bands calculated as ((SWIR2 - GREEN) / (SWIR2 + GREEN)), refer to data file Other_ND-SWIR2-GREEN

Process step

Description: iron oxide index (SWIR2/RED): The normalised difference index of Enhanced Bare Earth bands calculated as ((SWIR2 - RED) / (SWIR2 + RED)), refer to data file Other_ND-SWIR2-RED

Process step

Description: iron oxide index (NIR/GREEN): The normalised difference index of Enhanced Bare Earth bands calculated as ((NIR - GREEN) / (NIR + GREEN)), refer to data file Other_ND-NIR-GREEN

Reference System Information

Reference system identifier: EPSG/EPSG:4326

Reference system type: Geodetic Geographic 2D

Metadata

Metadata identifier

urn:uuid/d39e4f2c-f771-4aef-99f8-1e624f416955

Title: TERN GeoNetwork UUID

Language: English

Character encoding: UTF8

Point of contact

Terrestrial Ecosystem Research Network

Building 1019, 80 Meiers Rd

Indooroopilly

QLD

4068

Australia

+61 7 3365 9097

Type of resource

Resource scope: Dataset

Metadata linkage: https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/d39e4f2c-f771-4aef-99f8-1e624f416955
Point-of-truth metadata URL

Date info (Creation): 2020-12-14T00:00:00

Date info (Revision): 2022-09-15T00:00:00

Metadata standard

Title: ISO 19115-1:2014/AMD 1:2018 Geographic information - Metadata - Fundamentals

Edition: 1

Metadata standard

Title: ISO/TS 19115-3:2016

Edition: 1.0

Metadata standard

Title: ISO/TS 19157-2:2016

Edition: 1.0

Title: Terrestrial Ecosystem Research Network (TERN) Metadata Profile of ISO 19115-3:2016 and ISO 19157-2:2016

Date (published): 2021

Edition: 1.0

Identifier

Code: 10.5281/zenodo.5652221

Website: https://github.com/ternaustralia/TERN-ISO19115/releases/tag/v1.0

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