A multivariate method for matching soil classification systems, with an Australian example

A - Papers appearing in refereed journals

Teng, H. F., Viscarra, Rossel, R. A. and Webster, R. 2020. A multivariate method for matching soil classification systems, with an Australian example. Soil Research. 58 (6), pp. 519-527. https://doi.org/10.1071/SR19320

AuthorsTeng, H. F., Viscarra, Rossel, R. A. and Webster, R.

Differences between local systems of soil classification hinder the communication between pedologists from different countries. The FAO–UNESCO Soil Map of the World, as a fruit of world-wide collaboration between innumerable soil scientists, is recognised internationally. Ideally, pedologists should be able to match whole classes in their local systems to those in an international soil classification system. The Australian Soil Classification (ASC) system, created specifically for Australian soil, is widely used in Australia, and Australian pedologists wish to translate the orders they recognise into the FAO soil units when writing for readers elsewhere. We explored the feasibility of matching soil orders in the ASC to units in the FAO legend using a multivariate analysis. Twenty soil properties, variates, of 4927 profiles were estimated from their visible–near infrared reflectance (vis–NIR) spectra. We arranged the profiles in a Euclidean 20-dimensional orthogonal vector space defined by standardised variates. Class centroids were computed in that space, and the Euclidean distances between the centroids of the ASC orders and units in the FAO scheme were also computed. The shortest distance between a centroid of any ASC order and one of units in the FAO classification was treated as a best match. With only one exception the best matches were those that an experienced pedologist might expect. Second and third nearest neighbours in the vector space provided additional insight. We conclude that vis–NIR spectra represent sufficiently well the essential characters of the soil and so spectra could form the basis for the development of a universal soil classification system. In our case, we could assign with confidence the orders of the ASC to the units of the FAO scheme. A similar approach could be applied to link other national classification systems to one or other international systems of soil classification.

KeywordsSoil classification; Class matching; World soil map; Principal components analysis; Australia
Year of Publication2020
JournalSoil Research
Journal citation58 (6), pp. 519-527
Digital Object Identifier (DOI)https://doi.org/10.1071/SR19320
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
Funder project or codeS2N - Soil to Nutrition [ISPG]
Output statusPublished
Publication dates
Online25 Jun 2020
Publication process dates
Accepted04 May 2020
PublisherCSIRO Publishing

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