Comparisons between USDA Soil Taxonomy and the Australian Soil Classification System I: Data harmonization, calculation of taxonomic distance and inter-taxa variation

Geoderma ◽  
2017 ◽  
Vol 307 ◽  
pp. 198-209 ◽  
Author(s):  
Philip Hughes ◽  
Alex B. McBratney ◽  
Jingyi Huang ◽  
Budiman Minasny ◽  
Erika Micheli ◽  
...  
Geoderma ◽  
2018 ◽  
Vol 322 ◽  
pp. 48-55 ◽  
Author(s):  
Philip Hughes ◽  
Alex B. McBratney ◽  
Budiman Minasny ◽  
Jingyi Huang ◽  
Erika Micheli ◽  
...  

Soil Research ◽  
2020 ◽  
Vol 58 (6) ◽  
pp. 519
Author(s):  
H. F. Teng ◽  
R. A. Viscarra Rossel ◽  
R. Webster

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.


CATENA ◽  
2021 ◽  
Vol 196 ◽  
pp. 104824 ◽  
Author(s):  
Alexey Sorokin ◽  
Phillip Owens ◽  
Vince Láng ◽  
Zhuo-Dong Jiang ◽  
Erika Michéli ◽  
...  

2020 ◽  
Vol 15 (No. 2) ◽  
pp. 101-115 ◽  
Author(s):  
Tereza Zádorová ◽  
Daniel Žížala ◽  
Vít Penížek ◽  
Aleš Vaněk

The possibility of the adequate use of data and maps from historical soil surveys depends, to a large measure, on their harmonisation. Legacy data originating from a large-scale national mapping campaign, “Systematic soil survey of agricultural soils in Czechoslovakia (SSS, 1961–1971)”, were harmonised and converted according to the actual system of soil classification and descriptions used in Czechia – the Czech taxonomic soil classification system (CTSCS). Applying the methods of taxonomic distance and quantitative analysis and reclassification of the selected soil properties, the conversion of two types of mapping soil units with different detailed soil information (General soil representative (GSR), and Basic soil representative (BSR)) to their counterparts in the CTSCS has been effectuated. The results proved the good potential of the used methods for the soil data harmonisation. The closeness of the concepts of the two classifications was shown when a number of soil classes had only one counterpart with a very low taxonomic distance. On the contrary, soils with variable soil properties were approximating several related units. The additional information on the soil skeleton content, texture, depth and parent material, available for the BSR units, showed the potential in the specification of some units, though the harmonisation of the soil texture turned out to problematic due to the different categorisation of soil particles. The validation of the results in the study region showed a good overall accuracy (75% for GSR, 76.1% for BSR) for both spatial soil units, when better performance has been observed in BSR. The conversion accuracy differed significantly in the individual soil units, and ranged from almost 100% in Fluvizems to 0% in Anthropozems. The extreme cases of a complete mis-classification can be attributed to inconsistencies originating in the historical database and maps. The study showed the potential of modern quantitative methods in the legacy data harmonisation and also the necessity of a critical approach to historical databases and maps.


Author(s):  
Anthony S. R. Juo ◽  
Kathrin Franzluebbers

Several pedological soil classification schemes have been developed to classify soils worldwide based on morphological features, stage of weathering, and to some extent their chemical and physical properties. Three soil classification systems are commonly used as research and teaching tools in the tropics, namely, the USDA Soil Taxonomy classification, the FAO/UNESCO World Soil Legends, and the French soil classification system. Brazil, the country with the largest land area in the tropics, has its own national soil classification system. However, soil survey, classification, and interpretation are costly and time-consuming, and few countries in the tropics have completed soil maps that are at a scale detailed enough to be useful to farmers and land users. In the absence of soil information at state, county or farm level, the authors propose a simple descriptive grouping of major soils in the tropics based on clay mineralogy to facilitate discussion on soil management and plant production in the subsequent chapters of this book. Reference to the Soil Taxonomy classification will be made when such information is available. It should be pointed out that the main purpose of this technical grouping is to provide field workers, especially those who are less familiar with the various soil classification systems, with a simple framework for planning soil management strategies. It by no means replaces the national and international soil taxonomy and classification systems that are designed for communication among soil scientists and for more detailed interpretation of soil survey data and land-use planning. This technical scheme classifies major arable soils in the tropics into four groupings according to their dominant clay mineralogy. They are • kaolinitic soils • oxidic soils • allophanic soils • smectitic soils Kaolinitic soils are deeply weathered soils with a sand, loamy sand, or sandy loam texture in the surface horizon and a clayey B horizon (20-60%). Silt content is low (< 20%) throughout the profile. Kaolinite (> 90%) is the dominant mineral in the clay fraction. These soils have an effective CEC of less than 12 cmol/kg of clay in the lower B horizon. Kaolinitic soils have a relatively high bulk density, especially in the clayey subsoil horizons (> 1.40 Mg/m3). The structure of the subsoil horizons is usually massive or blocky.


Soil Research ◽  
2007 ◽  
Vol 45 (6) ◽  
pp. 428 ◽  
Author(s):  
Budiman Minasny ◽  
Alex B. McBratney ◽  
Damien J. Field ◽  
Grant Tranter ◽  
Neil J. McKenzie ◽  
...  

This paper aims to establish the means and ranges of clay, silt, and sand contents from field texture classes, and to investigate the differences in the field texture classes and texture determined from particle-size analysis. The results of this paper have 2 practical applications: (1) to estimate the particle size distribution and its uncertainty from field texture as input to pedotransfer functions, and (2) to examine the criteria of texture contrast soils in the Australian Soil Classification system. Estimates of clay, silt, and sand content for each field texture class are given and this allows the field texture classes to be plotted in the texture triangle. There are considerable differences between field texture classes and particle-size classes. Based on the uncertainties in determining the clay content from field texture, we establish the probability of the occurrence of a texture contrast soil according to the Australian Soil Classification system, given the texture of the B2 horizon and its overlying A horizon. I enjoy doing the soil-texture feel test with my fingers or kneading a clay soil, which is a short step from ceramics or sculpture. Hans Jenny (1984)


2020 ◽  
Vol 22 ◽  
pp. e00296
Author(s):  
Stewart Kyebogola ◽  
Lee C. Burras ◽  
Bradley A. Miller ◽  
Onesimus Semalulu ◽  
Russell S. Yost ◽  
...  

Geoderma ◽  
2016 ◽  
Vol 264 ◽  
pp. 340-349 ◽  
Author(s):  
Erika Michéli ◽  
Vince Láng ◽  
Phillip R. Owens ◽  
Alex McBratney ◽  
Jon Hempel

2009 ◽  
Vol 42 (9) ◽  
pp. 967-975 ◽  
Author(s):  
V. D. Tonkonogov ◽  
I. I. Lebedeva ◽  
M. I. Gerasimova ◽  
S. F. Khokhlov

Sign in / Sign up

Export Citation Format

Share Document