Discrimination of Australian soil horizons and classes from their visible-near infrared spectra

A - Papers appearing in refereed journals

Viscarra Rossel, R. A. and Webster, R. 2011. Discrimination of Australian soil horizons and classes from their visible-near infrared spectra. European Journal of Soil Science. 62 (4), pp. 637-647. https://doi.org/10.1111/j.1365-2389.2011.01356.x

AuthorsViscarra Rossel, R. A. and Webster, R.

A soil's reflectance spectrum in the visible and near infrared is rich in information. It is an integrative property of the soil that measures its colour, the abundance of iron oxides, clay minerals and carbonates, the amount of water and organic matter and its particle size. We explored the merit of discriminating between soil horizons, of which we had 13 654 samples, and soil orders from the Australian Soil Classification, of which we had samples from 1697 profiles with designated horizons, by analysing quantitatively their diffuse reflectance spectra in the visible-near infrared (vis-NIR) range (350-2500 nm). We re-sampled the spectra to 10-nm intervals and converted them to logarithms of deviations from their convex hulls. We then transformed them to canonical variates, which we display as scatter diagrams in low-order canonical planes. The minerals, colour and organic constituents thought to be responsible for their discrimination are identified. Each spectrum was re-examined and allocated to the group whose centroid was nearest in the canonical space. Topsoil horizons (A, A2 and transitional AB and AC horizons) were distinguishable from subsoils (B, C and transitional BC horizons). Vertosols, Ferrosols, Podosols (Podzols), Organosols, Calcarosols, Rudosols, Sodosols, Hydrosols, Kandosols and Kurosols were in general well separated from other soil orders and were assigned to their own orders such that 80% or more were correctly allocated. These orders possess characteristics that are easily distinguished by vis-NIR spectroscopy. Re-allocations to other orders were interpretable and could be related to identifying features of the ASC classification. Our results show that spectra distinguish soil horizons and soil type. They suggest that vis-NIR spectroscopy could make an important contribution to the definition and identification of classes in an effective system of soil classification.

KeywordsSoil Science
Year of Publication2011
JournalEuropean Journal of Soil Science
Journal citation62 (4), pp. 637-647
Digital Object Identifier (DOI)https://doi.org/10.1111/j.1365-2389.2011.01356.x
Open accessPublished as non-open access
FunderAustralian Collaborative Land Evaluation Program (ACLEP)
Funder project or codeSEF
Complex spatial variation of environmental variables: sampling, prediction and interpretation

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