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Australian Soil Classification Map

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Description

We used Digital Soil Mapping (DSM) technologies combined with the real-time collations of soil attribute data from TERN's recently developed Soil Data Federation System, to produce a map of Australian Soil Classification Soil Order classes with quantified estimates of mapping reliability at a 90m resolution.
Credit
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 map gives an estimate of the spatial distribution of soil types across Australia.

Temporal coverage

From 1/1/1950 to 8/10/2021

Dates

Date modified

8/10/2021

Citation information

How to cite this collection:

Searle, R. (2021): Australian Soil Classification Map. Version 1.0.0. Terrestrial Ecosystem Research Network. (Dataset). https://doi.org/10.25901/edyr-wg85

Rights and Licensing

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}.

Spatial coverage

Keywords

Parameters
Data Resolution
GCMD Science
ANZSRC - FOR
Topic Categories
User Defined
  • Australian Soil Types

Additional information

AuthorsAuthors
Point of ContactPoint of Contact
PublisherPublisher
Distributor's OrganisationDistributor's Organisation
Data QualityData Quality
  • Colour Map details:
  • Data Quality Assessment Result:
    The overall map accuracy is 61%. Each pixel also has an estimate of the Random Forest model structural uncertainty represented as a confusion index. The confusion index is available from the same location as this dataset.

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