Printed from the TERN Data Discovery portal

http://portal.tern.org.au/enhanced-bare-earth-lithological-modelling/21910
The maximum number of records allowed to be saved is 20.You have exceeded the limit.

134.2880855,-26.4181685

157.447265,-9.154163 157.447265,-43.682174 111.128906,-43.682174 111.128906,-9.154163 157.447265,-9.154163

View
TERN/d39e4f2c-f771-4aef-99f8-1e624f416955 21910
METADATA

Enhanced Bare Earth Covariates for Soil and Lithological Modelling

Description

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
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).

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

Lineage

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).

Data Creation
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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

Temporal coverage

From 2018-06-30 To 2018-06-30

Dates

  • Date modified

    16/05/2022

Citation information

How to cite this collection:

Wilford, J., Roberts, D. (2021): Enhanced Bare Earth Covariates for Soil and Lithological Modelling. Version 1.0.0. Terrestrial Ecosystem Research Network. (Dataset). https://portal.tern.org.au/enhanced-bare-earth-lithological-modelling/21910

Access data

This data can be accessed from the following websites

Access metadata

Source Metadata URL

Rights and Licensing

Creative Commons Attribution 4.0 International Licence

http://creativecommons.org/licenses/by/4.0

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

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

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.

unclassified