Soil and Landscape Grid National Soil Attribute Maps - Soil Colour (3" resolution) - Release 1
We used Digital Soil Mapping (DSM) technologies combined with collations of observed soil colour data from TERN's Soil Data Federation System, to produce surface and subsoil maps of soil colour at a 90 m resolution.<br><br>
The map gives an estimate of the spatial distribution of RGB soil colour across Australia.<br><br>
Detailed information about the Soil and Landscape Grid of Australia can be found at - <a href=" https://esoil.io/TERNLandscapes/Public/Pages/SLGA/index.html ">SLGA</a>.<br><br>
<ul style="list-style-type: disc;">
<li>Period (temporal coverage; approximately): 1950-2020;</li>
<li>Spatial resolution: 3 arc seconds (approx 90 m);</li>
<li>Number of pixels with coverage per layer: 2007M (49200 * 40800);</li>
<li>Data license : Creative Commons Attribution 4.0 (CC BY);</li>
<li>Target data standard: GlobalSoilMap specifications;</li>
<li>Format: Cloud Optimised GeoTIFF;</li></ul>
Simple
Identification info
- Date (Creation)
- 2020-10-13
- Date (Publication)
- 2022-10-31
- Date (Revision)
- 2024-12-16
- Edition
- 1.0
Identifier
Publisher
Author
CSIRO Agriculture and Food - Malone, Brendan ()
Waite Road, Waite, South Australia, 5064, Australia
Waite
South Australia
5064
Australia
Collaborator
Commonwealth Scientific and Industrial Research Organisation
Building 101, Clunies Ross Street, Black Mountain, 2601, Australian Capital Territory, Australia
Black Mountain
Australian Capital Territory
2601
Australia
Collaborator
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
Collaborator
University of Sydney
City Road, Camperdown, New South Wales, 2050, Australia
Camperdown
New South Wales
2050
Australia
Collaborator
Geoscience Australia
101 Jerrabomberra Avenue, Symonston, 2609, Australian Capital Territory, Australia
Symonston
Australian Capital Territory
2609
Australia
Collaborator
Department of Land Resource Management (2012-2016), Northern Territory Government
25 Chung Wah Terrace, Palmerston, Northern Territory, 0830, Australia
Palmerston
Northern Territory
0830
Australia
Collaborator
Office of Environment and Heritage (2011-2019), New South Wales
4 Parramatta Square, 12 Darcy Street, Parramatta, 2150, New South Wales, Australia
Parramatta
New South Wales
2150
Australia
Collaborator
Department of Science, Information Technology, Innovation and the Arts (2012-2015), Queensland Government
400 George Street, Brisbane, Queensland, 4000, Australia
Brisbane
Queensland
4000
Australia
Collaborator
Department of Environment, Water and Natural Resources (2012-2018), South Australian Government
81-95 Waymouth Street, Adelaide, South Australia, 5000, Australia
Adelaide
South Australia
5000
Australia
Collaborator
Department of Primary Industries, Parks, Water and Environment, Tasmanian Government
59 Liverpool Street, Hobart, Tasmania, 7000, Australia
Hobart
Tasmania
7000
Australia
Collaborator
Department of Environment and Primary Industries (2013-2015), Victorian Government
8 Nicholson Street, Melbourne, Victoria, 3000, Australia
Melbourne
Victoria
3000
Australia
Collaborator
Department of Agriculture and Food (2006-2017), Western Australian Government
3 Baron-Hay Court South Perth Western Australia 6151, Australia
South Perth
Western Australia
6151
Australia
- Website
- https://www.tern.org.au/
- Purpose
- The map gives a modelled estimate of the spatial distribution of soil colour across Australia.
- 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
- <p></p>This work was jointly funded by CSIRO, Terrestrial Ecosystem Research Network (TERN) and the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS).<br> We are grateful to the custodians of the soil site data in each state and territory for providing access to the soil site data, and all of the organisations listed as collaborating agencies for their significant contributions to the project and its outcomes.
- Status
- Completed
Point of contact
CSIRO Agriculture and Food - Malone, Brendan ()
Waite Road, Waite, South Australia, 5064, Australia
Waite Road
Waite
South Australia
5064
Australia
Spatial resolution
- Spatial resolution
- 90
- Topic category
-
- Environment
- Geoscientific information
Extent
N
S
E
W
))
Temporal extent
- Time period
- 1950-01-01 2020-10-13
- Maintenance and update frequency
- Not planned
- GCMD Science Keywords
- ANZSRC Fields of Research
- TERN Parameter Vocabulary
- QUDT Units of Measure
- GCMD Horizontal Resolution Ranges
- GCMD Temporal Resolution Ranges
- Keywords (Discipline)
-
- Soil
- Raster
- Australian Soil Colour
- DSM
- Global Soil Map
- Spatial modelling
- Soil Maps
- Digital Soil Mapping
- SLGA
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
- Title
- Creative Commons Attribution 4.0 International Licence
- Alternate title
- CC-BY
- Edition
- 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. <br />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. <br /><br />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}.
- 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.<br> 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.<br><br> Please advise any work or publications that use this data via the online form at https://www.tern.org.au/research-publications/#reporting<br> Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.
Resource constraints
- Classification
- Unclassified
Distribution Information
- Distribution format
-
Distributor
Distributor
Terrestrial Ecosystem Research Network
80 Meiers Road, Indooroopilly, Queensland, 4068, Australia
Indooroopilly
Queensland
4068
Australia
- OnLine resource
- Cloud Optimised GeoTIFFs - Soil Colour
- OnLine resource
-
slga_soilcolour
National Soil Attribute Maps - Soil Colour
- OnLine resource
- Landscape Data Visualiser - Soil Colour
- OnLine resource
- ro-crate-metadata.json
Resource lineage
- Statement
- The map was produced as per methods described at - https://aussoilsdsm.esoil.io/slga-version-2-products/soil-colour<br><br> Soil colour is arguably one of the most obvious and easily observed soil morphological characteristics. Soil scientists use soil colour to differentiate genetic soil horizons as well as for the classification of soil types, e.g. The Australian Soil Classification.<br><br> In Australia, prior work of mapping the colour of Australian soils was performed by Viscarra Rossel et al. (2010), but was limited to just surface soils, output mapping to 5 km spatial resolution, and only utilised a relatively small collection of vis-NIR spectra (from which colour was inferred) to develop spatial soil colour models.<br><br> From data discovery via the Australian Soil Data Federator, we were able to compile over 300 000 soil colour field observations (dry soil condition) collected across Australia. About 160 000 were for topsoils, while about 140 000 were for subsoils. Rather than exclusively using vis-NIR spectra, a logical line of investigation is to exploit the availability of a comparatively larger field observed dataset.<br><br> Colour Space Conversions<br><br> Field classification of soil colours are near exclusively recorded using the Munsell HVC (Hue, Value, Chroma) colour system. Munsell HVC soil colour descriptions are not conducive for quantitative studies (Robertson 1977). Using a lookup table, we performed a conversion from the Munsell HVC colour space to the CIELAB colour space. The CIELAB colour space can describe any uniform colour space by the three variables: L*, a*, and b*. Each variable represents the lightness of the colour (L* = 0 yields black and L* = 100 indicates diffuse white), its position between red/magenta and green (a*, negative values indicate green while positive values indicate magenta) and its position between yellow and blue (b*, negative values indicate blue and positive values indicate yellow).<br><br> Digital soil mapping<br><br> Random Forest machine learning was used to independently model L*, a*, and b* target variables as a function of a suite of available national extent environmental covariates. While we did investigate various options for combined target variable modelling given the covarying relationships of the colour variables, neither were able to match the prediction skill of the independently treated approach. The L* variable was modelled as a categorical variable, both a*, and b* were modelled as continuous variables. For both top- and subsoil models, a dataset (n=10000) was selected out of each of the available datasets prior to any modelling for the sole purpose of evaluating the goodness of fit of the fitted models, akin to an out-of-bag model evaluation.<br><br> After modelling, the combined L*, a*, and b* were post-processed to line up the nearest HVC colour space chip using Euclidean distance quantification.<br><br> For colour visualisation of the soil colour maps, predictions were transformed to the RGB colour space using the same lookup table as for the conversion form Munsell HVC to CIELAB.<br><br> All processing for the generation of these products was undertaken using the R programming language. R Core Team (2020).<br><br> Code - https://github.com/AusSoilsDSM/SLGA Observation data - https://esoil.io/TERNLandscapes/Public/Pages/SoilDataFederator/SoilDataFederator.html Covariate rasters - https://esoil.io/TERNLandscapes/Public/Pages/SLGA/GetData-COGSDataStore.html
- Hierarchy level
- Dataset
- Title
- Methods Summary - Soil-Colour
- Website
-
https://aussoilsdsm.esoil.io/slga-version-2-products/soil-colour
Method documentation
- Title
- R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria.
- Website
-
https://www.R-project.org/
Method documentation
- Title
- Robertson, A. R., The CIE 1976 color-difference formulae, Color Research and Application, 1977, 2: 7–11.
- Website
-
https://doi.org/10.1002/j.1520-6378.1977.tb00104.x
Method documentation
- Title
- Viscarra Rossel, R. A., Behrens, T., Ben-Dor, E., Brown, D. J., Demattê, J. A. M., Shepherd, K. D., Shi, Z., Stenberg, B., Stevens, A., Adamchuk, V., Aïchi, H., Barthès, B. G., Bartholomeus, H. M., Bayer, A. D., Bernoux, M., Böttcher, K., Brodský, L., Du, C. W., Chappell, A., … Ji, W. (2016). A global spectral library to characterize the world’s soil. Earth-Science Reviews, 155, 198–230.
- Website
-
https://doi.org/10.1016/J.EARSCIREV.2016.01.012
Method documentation
Reference System Information
- Reference system identifier
- EPSG/EPSG:4326
- Reference system type
- Geodetic Geographic 2D
Metadata
- Metadata identifier
-
urn:uuid/1d9a9989-142e-4785-8122-711f95f20871
- Title
- TERN GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
Point of contact
Type of resource
- Resource scope
- Dataset
- Metadata linkage
-
https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/1d9a9989-142e-4785-8122-711f95f20871
Point-of-truth metadata URL
- Date info (Creation)
- 2021-08-10T00:00:00
- Date info (Revision)
- 2024-12-16T00:00:00
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
Overviews
thumbnail
Spatial extent
N
S
E
W
Provided by
Associated resources
Not available