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RESEARCH ARTICLE

Derivation of soil-attribute estimations from legacy soil maps

Nathan P. Odgers A F , Karen W. Holmes B C D , Ted Griffin B and Craig Liddicoat E
+ Author Affiliations
- Author Affiliations

A Department of Environmental Sciences, Faculty of Agriculture and Environment, C81 Biomedical Building, The University of Sydney, NSW 2006, Australia.

B Department of Agriculture and Food Western Australia, 3 Baron-Hay Court, South Perth, WA 6151, Australia.

C Soil Matrix Group, School of Earth and Environment, The University of Western Australia, Stirling Highway, Crawley, WA 6009, Australia.

D CSIRO Sustainable Agriculture Flagship, Ecosciences Precinct, Dutton Park 4001, Australia.

E Department of Environment, Water and Natural Resources, Plant Biodiversity Centre, Hackney Road, Botanic Gardens, Adelaide, SA 5001, Australia.

F Corresponding author. Email: nathan.odgers@sydney.edu.au

Soil Research 53(8) 881-894 https://doi.org/10.1071/SR14274
Submitted: 1 October 2014  Accepted: 31 March 2015   Published: 29 July 2015

Abstract

It is increasingly necessary to apply quantitative techniques to legacy soil polygon maps given that legacy soil maps may be the only source of soil information over large areas. Spatial disaggregation provides a means of extracting information from legacy soil maps and enables us to downscale the original information to produce new soil class maps at finer levels of detail. This is a useful outcome in its own right; however, the disaggregated soil-class coverage can also be used to make digital maps of soil properties with associated estimates of uncertainty. In this work, we take the spatially disaggregated soil-class coverage for all of Western Australia and the agricultural region of South Australia and demonstrate its application in mapping clay content at six depth intervals in the soil profile. Estimates of uncertainty are provided in the form of the 90% prediction interval. The work can be considered an example of harmonisation to a common output specification. The validation results highlighted areas in the landscape and taxonomic spaces where more knowledge of soil properties is necessary.

Additional keywords: clay content, digital soil mapping, legacy soil data, prediction interval, spatial disaggregation, weighted mean.


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