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.

中文翻译：

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一种匹配土壤分类系统的多元方法，以澳大利亚为例

当地土壤分类系统之间的差异阻碍了来自不同国家的土壤学家之间的交流。粮农组织-联合国教科文组织世界土壤地图是无数土壤科学家在全球范围内合作的成果，得到了国际认可。理想情况下，土壤学家应该能够将当地系统中的整个类与国际土壤分类系统中的类相匹配。澳大利亚土壤分类 (ASC) 系统是专门为澳大利亚土壤创建的，在澳大利亚被广泛使用，澳大利亚土壤学家希望在为其他地方的读者写作时将他们认可的顺序翻译成粮农组织土壤单位。我们使用多变量分析探讨了将 ASC 中的土壤顺序与粮农组织图例中的单位相匹配的可行性。二十种土壤特性，变量，4927 个剖面是根据它们的可见-近红外反射 (vis-NIR) 光谱估计的。我们将轮廓排列在由标准化变量定义的欧几里得 20 维正交向量空间中。在该空间中计算类质心，并且还计算了FAO 方案中ASC 订单和单位的质心之间的欧几里得距离。任何 ASC 顺序的质心与粮农组织分类中的一个单位之间的最短距离被视为最佳匹配。除了一个例外，最好的匹配是经验丰富的土壤学家可能期望的匹配。向量空间中的第二个和第三个最近的邻居提供了额外的洞察力。我们得出结论，可见近红外光谱足以很好地代表土壤的基本特征，因此光谱可以构成通用土壤分类系统开发的基础。在我们的例子中，我们可以放心地将 ASC 的命令分配给粮农组织计划的单位。类似的方法可用于将其他国家分类系统与一个或其他国际土壤分类系统联系起来。