Data

Soil and Landscape Grid National Soil Attribute Maps - Coarse Fragments (3" resolution) - Release 1

Terrestrial Ecosystem Research Network
Dobarco, Mercedes ; Wadoux, Alexandre ; Malone, Brendan ; Minasny, Budiman ; McBratney, Alex ; Searle, Ross
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25919/c583-fd02&rft.title=Soil and Landscape Grid National Soil Attribute Maps - Coarse Fragments (3 resolution) - Release 1&rft.identifier=10.25919/c583-fd02&rft.publisher=Terrestrial Ecosystem Research Network&rft.description=This is Version 1 of the Soil Coarse Fragments product of the Soil and Landscape Grid of Australia. The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm and 100-200 cm. These depths are consistent with the specifications of the GlobalSoilMap.net project - GlobalSoilMaps. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels). These maps are generated using Digital Soil Mapping methods. Detailed information about the Soil and Landscape Grid of Australia can be found at - SLGA Attribute Definition: Soil Coarse Fragments Class Probabilities as defined in the Australian Soil and Land Survey Field Handbook (Units: Probability of CF class occurring); Period (temporal coverage; approximately): 1950-2022; Spatial resolution: 3 arc seconds (approximately 90 m); Total number of gridded maps for this attribute: 18; Number of pixels with coverage per layer: 2007M (49200 * 40800); Total size before compression: about 8GB; Total size after compression: about 4GB; Format: Cloud Optimised GeoTIFF.Data on the abundance of coarse fragments (particles > 2 mm) and gravimetric content (% weight) were extracted with using the the Terrestrial Ecosystem Research Network (TERN) Soil Data Federator managed by CSIRO (Searle et al., 2021). The Soil Data Federator is a web API that compiles soil data from various institutions and government agencies throughout Australia. The abundance (% volume) is assessed visually in the field as part of the soil profile description using standards described in the Australian Soil and Land Survey field Handbook (National Committee on Soils and Terrain , 2009). The abundance of rock fragments per soil horizon on the cut surface of the soil profile surface of the soil horizon occupied by coarse fragments was grouped into six categories: very few (0-2 %), few (2-10 %), common (2-20 %), many (20-50 %), abundant (50-90 %) and very abundant (> 90 %). The gravimetric content (% mass) is measured in the laboratory as percent mass of coarse fragments (particles > 2 mm) from the whole soil. Here, we take the profile surface abundance of coarse fragments as a proxy for volumetric coarse fragments (CFVol). The data was cleaned and processed to exclude duplicates and wrong data entries (e.g., missing values). The observations of CFVol (%) were converted into GlobalSoilMap depth intervals with the slab function of the aqp R package (Beaudette et al., 2021), assigning the most probable class to each depth interval. The gravimetric coarse fragments were also standardised to the GlobalSoilMap depth intervals with equal-area quadratic splines (Bishop et al., 1999). Observations of gravimetric coarse fragment content (CF_Weight) were transformed into volumetric with the equation: CF_Vol (%) = Vol_CF / Vol_WhSoil (Weight_CF / ρ_CF(Weight_WhSoil / ρ_WhSoil) =(CF_Weight * ρ_WhSoil) / ρ_CF Where, ρ_WhSoil is the bulk density prediction for bulk soil from SLGA (Viscarra Rossel et al., 2014), ρ_CF is assumed to be 2.65 g cm-3 (Hurlbut and Klein (1977) in Mckenzie et al. (2002) and CF_Vol is the volumetric coarse fragment content (continuous),which was assigned to the corresponding class. This resulted in CFVol observations for 110,308 locations. Mapping was produced using quantile regression forest fitted with the observed coarse fragments class data and a large set of environmental variables as predictors. 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.htmlProgress Code: completedMaintenance and Update Frequency: notPlanned&rft.creator=Dobarco, Mercedes &rft.creator=Wadoux, Alexandre &rft.creator=Malone, Brendan &rft.creator=Minasny, Budiman &rft.creator=McBratney, Alex &rft.creator=Searle, Ross &rft.date=2024&rft.edition=1.0&rft.relation=https://doi.org/10.1016/j.geoderma.2020.114579&rft.coverage=northlimit=-10.000416666; southlimit=-44.000416667; westlimit=112.999583333; eastLimit=153.999583334; projection=EPSG:4326&rft_rights=Creative Commons Attribution 4.0 International Licence http://creativecommons.org/licenses/by/4.0&rft_rights=&rft_rights=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 /><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 /><br />Please cite this dataset as {Author} ({PublicationYear}). {Title}. {Version, as appropriate}. Terrestrial Ecosystem Research Network. Dataset. {Identifier}.&rft_subject=environment&rft_subject=geoscientificInformation&rft_subject=SOILS&rft_subject=AGRICULTURE&rft_subject=EARTH SCIENCE&rft_subject=LAND SURFACE&rft_subject=Agricultural Land Management&rft_subject=AGRICULTURAL AND VETERINARY SCIENCES&rft_subject=AGRICULTURE, LAND AND FARM MANAGEMENT&rft_subject=Agricultural Spatial Analysis and Modelling&rft_subject=SOIL SCIENCES&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Soil Sciences not elsewhere classified&rft_subject=abundance of coarse fragments (Unitless)&rft_subject=Unitless&rft_subject=30 meters - < 100 meters&rft_subject=Decadal&rft_subject=TERN_Soils&rft_subject=TERN_Soils_DSM&rft_subject=Soil&rft_subject=TERN&rft_subject=Raster&rft_subject=Attributes&rft_subject=Continental&rft_subject=Australia&rft_subject=DSM&rft_subject=Global Soil Map&rft_subject=spatial modelling&rft_subject=3-dimensional soil mapping&rft_subject=spatial uncertainty&rft_subject=Soil Maps&rft_subject=Digital Soil Mapping&rft_subject=SLGA&rft_subject=Course Fragments Probability&rft.type=dataset&rft.language=English Access the data

Licence & Rights:

Open Licence view details
CC-BY

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}.

Access:

Open view details

unclassified

Contact Information

Street Address:
Terrestrial Ecosystem Research Network
Building 1019, 80 Meiers Rd
QLD 4068
Australia
Ph: +61 7 3365 9097

esupport@tern.org.au

Brief description

This is Version 1 of the Soil Coarse Fragments product of the Soil and Landscape Grid of Australia.

The Soil and Landscape Grid of Australia has produced a range of digital soil attribute products. Each product contains six digital soil attribute maps, and their upper and lower confidence limits, representing the soil attribute at six depths: 0-5 cm, 5-15 cm, 15-30 cm, 30-60 cm, 60-100 cm and 100-200 cm. These depths are consistent with the specifications of the GlobalSoilMap.net project - GlobalSoilMaps. The digital soil attribute maps are in raster format at a resolution of 3 arc sec (~90 x 90 m pixels).

These maps are generated using Digital Soil Mapping methods.

Detailed information about the Soil and Landscape Grid of Australia can be found at - SLGA

  • Attribute Definition: Soil Coarse Fragments Class Probabilities as defined in the Australian Soil and Land Survey Field Handbook (Units: Probability of CF class occurring);
  • Period (temporal coverage; approximately): 1950-2022;
  • Spatial resolution: 3 arc seconds (approximately 90 m);
  • Total number of gridded maps for this attribute: 18;
  • Number of pixels with coverage per layer: 2007M (49200 * 40800);
  • Total size before compression: about 8GB;
  • Total size after compression: about 4GB;
  • Format: Cloud Optimised GeoTIFF.

Lineage

Data on the abundance of coarse fragments (particles > 2 mm) and gravimetric content (% weight) were extracted with using the the Terrestrial Ecosystem Research Network (TERN) Soil Data Federator managed by CSIRO (Searle et al., 2021). The Soil Data Federator is a web API that compiles soil data from various institutions and government agencies throughout Australia. The abundance (% volume) is assessed visually in the field as part of the soil profile description using standards described in the Australian Soil and Land Survey field Handbook (National Committee on Soils and Terrain , 2009). The abundance of rock fragments per soil horizon on the cut surface of the soil profile surface of the soil horizon occupied by coarse fragments was grouped into six categories: very few (0-2 %), few (2-10 %), common (2-20 %), many (20-50 %), abundant (50-90 %) and very abundant (> 90 %). The gravimetric content (% mass) is measured in the laboratory as percent mass of coarse fragments (particles > 2 mm) from the whole soil. Here, we take the profile surface abundance of coarse fragments as a proxy for volumetric coarse fragments (CFVol). The data was cleaned and processed to exclude duplicates and wrong data entries (e.g., missing values). The observations of CFVol (%) were converted into GlobalSoilMap depth intervals with the slab function of the aqp R package (Beaudette et al., 2021), assigning the most probable class to each depth interval. The gravimetric coarse fragments were also standardised to the GlobalSoilMap depth intervals with equal-area quadratic splines (Bishop et al., 1999).
Observations of gravimetric coarse fragment content (CF_Weight) were transformed into volumetric with the equation:

CF_Vol (%) = Vol_CF / Vol_WhSoil (Weight_CF / ρ_CF(Weight_WhSoil / ρ_WhSoil) =(CF_Weight * ρ_WhSoil) / ρ_CF

Where, ρ_WhSoil is the bulk density prediction for bulk soil from SLGA (Viscarra Rossel et al., 2014), ρ_CF is assumed to be 2.65 g cm-3 (Hurlbut and Klein (1977) in Mckenzie et al. (2002) and CF_Vol is the volumetric coarse fragment content (continuous),which was assigned to the corresponding class. This resulted in CFVol observations for 110,308 locations.

Mapping was produced using quantile regression forest fitted with the observed coarse fragments class data and a large set of environmental variables as predictors.

Progress Code: completed
Maintenance and Update Frequency: notPlanned

Notes

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.


The observed data used to produce this map was obtained from state and federal soil survey agencies. The work was supported by TERN. CSIRO maintains and makes the data through the Australian Soil Resource Information System.
Purpose
The aim is to operate an open national capability that provides access to verified, science-quality land surface dynamics data and soils information layers, plus high-end data analytics tools that integrated with other TERN observations can meet the needs of ecosystem researchers and actionable information for policy makers and natural resource managers.

The map gives a modelled estimate of the spatial distribution of Soil Coarse Fragments Class Probabilities as defined in the Australian Soil and Land Survey Field Handbook in soils across Australia.

Created: 2022-10-06

Issued: 2024-08-06

Modified: 2024-08-06

Data time period: 1950-01-01 to 2022-10-06

This dataset is part of a larger collection

153.99958,-10.00042 153.99958,-44.00042 112.99958,-44.00042 112.99958,-10.00042 153.99958,-10.00042

133.4995833335,-27.0004166665

Other Information
Point-of-truth metadata URL

uri : https://geonetwork.tern.org.au/geonetwork/srv/eng/catalog.search#/metadata/4dd5ced8-4116-45ad-bfb1-ec4b8ad375a0

Soil Coarse Fragments

uri : https://aussoilsdsm.esoil.io/slga-version-2-products/soc-fractions

Beaudette, D. E., Roudier, P., and Brown, A.: aqp: Algorithms for Quantitative Pedology, R package version 1.42, [code], 2022

doi : https://doi.org/10.1016/j.cageo.2012.10.020

Soil and Landscape Grid National Soil Attribute Maps - Bulk Density - Whole Earth (3" resolution) - Release 1. v5. CSIRO. Data Collection.

doi : https://doi.org/10.4225/08/546EE212B0048

Bishop, T. F. A., McBratney, A. B., and Laslett, G. M.: Modelling soil attribute depth functions with equal-area quadratic smoothing splines, Geoderma, 91, 27–45, 1999

doi : https://doi.org/10.1016/S0016-7061(99)00003-8

McKenzie, N., Coughlan, K., and Cresswell, H.: Soil physical measurement and interpretation for land evaluation, CSIRO Publishing, 2002. 

doi : https://doi.org/10.1071/9780643069879