Demands on Soil Classification and Soil Survey Strategies: Special-Purpose Soil Classification Systems for Local Practical Use

2013 ◽  
pp. 51-83 ◽  
Author(s):  
R. W. Fitzpatrick
Keyword(s):  
Soil Classification ◽  
Classification Systems ◽  
Soil Survey

scholarly journals A Comparative Analysis of a Detailed and Semi-Detailed Soil Mapping for Sustainable Land Management Using Conventional and Currently Applied Methodologies in Greece

Land ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 154 ◽  
Author(s):  
Orestis Kairis ◽  
Vassiliki Dimitriou ◽  
Chrysoula Aratzioglou ◽  
Dionisios Gasparatos ◽  
Nicholas Yassoglou ◽  
...  
Keyword(s):  
Soil Classification ◽  
Botanical Garden ◽  
Soil Mapping ◽  
Classification Systems ◽  
Soil Survey ◽  
Sustainable Land Use ◽  
Soil Taxonomy ◽  
Reference Base ◽  
World Reference Base ◽  
Soil Surveys

Two soil mapping methodologies at different scales applied in the same area were compared in order to investigate the potential of their combined use to achieve an integrated and more accurate soil description for sustainable land use management. The two methodologies represent the main types of soil mapping systems used and still applied in soil surveys in Greece. Diomedes Botanical Garden (DBG) (Athens, Greece) was used as a study area because past cartographic data of soil survey were available. The older soil survey data were obtained via the conventional methodology extensively used over time since the beginnings of soil mapping in Greece (1977). The second mapping methodology constitutes the current soil mapping system in Greece recently used for compilation of the national soil map. The obtained cartographic and soil data resulting from the application of the two methodologies were analyzed and compared using appropriate geospatial techniques. Even though the two mapping methodologies have been performed at different mapping scales, using partially different mapping symbols and different soil classification systems, the description of the soils based on the cartographic symbols of the two methodologies presented an agreement of 63.7% while the soil classification by the two taxonomic systems namely Soil Taxonomy and World Reference Base for Soil Resources had an average coincidence of 69.5%.

Major Arable Soils of the Tropics :A Descriptive Grouping Based on Clay Mineralogy

2003 ◽  
Author(s):  
Anthony S. R. Juo ◽  
Kathrin Franzluebbers
Keyword(s):  
Classification System ◽  
Clay Mineralogy ◽  
Soil Management ◽  
Soil Classification ◽  
Classification Systems ◽  
Soil Survey ◽  
Arable Soils ◽  
Soil Taxonomy ◽  
Detailed Interpretation ◽  
The Tropics

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.

INTERPRETATION SHEETS FOR ENGINEERING CLASSIFICATIONS IN SOIL SURVEYS

1983 ◽  
Vol 63 (4) ◽  
pp. 679-689 ◽  
Author(s):  
G. WILSON
Keyword(s):  
Key Words ◽  
Soil Classification ◽  
Classification Systems ◽  
Soil Survey ◽  
Time Element ◽  
Effective Use ◽  
Soil Surveys ◽  
Engineering Soil ◽  
Engineering Classification ◽  
Mapping Units

The UNIFIED and AASHTO systems are used in engineering to classify soils for specific purposes. To facilitate use of the soil surveys by engineers, it has been customary to interpret soil survey mapping units in terms of these engineering classification systems. The procedure, however, is often difficult to follow and normally time-consuming. When used in combination with pedotechnical setting sheets, interpretation sheets reduce this time element and provide for more effective use of the soil survey information. This paper demonstrates development and application of the interpretation sheets. Key words: Engineering soil classification, pedotechnical interpretations, UNIFIED, AASHTO, soil engineering

Soils of Southeast Asia

2005 ◽  
Author(s):  
R. Dudal
Keyword(s):  
Southeast Asia ◽  
Soil Classification ◽  
Tropical Soils ◽  
Parent Material ◽  
Humid Tropics ◽  
Classification Systems ◽  
Soil Survey ◽  
Soil Science ◽  
United States Department ◽  
The Tropics

Towards the end of the nineteenth century, with the advent of soil science, soils of the humid tropics were recognized as a separate entity called ‘tropical forest lateritic soils’. The term ‘lateritic’ was derived from laterite (Latin later, brick), a term coined by Buchanan (1807) to describe an iron-rich clay from south India which, when hardened upon exposure, was used as building material. Originally it was thought that laterite represented soil formations throughout the humid tropics, hence the generalization of the name to all red soils in the region. The great diversity of the tropical soils was realized only around the 1930s along with the limited areal occupation of laterite in the tropics. It was actually in Southeast Asia that Vageler (1930) and Mohr (1944) wrote the first two books on tropical soils, based essentially on their study of soils in Indonesia. The two volumes of Mohr’s book were published in Dutch in 1934–8. The English translation appeared in 1944. They attempted to classify soils of the tropics according to thickness, degree of weathering, parent material, and fertility. The understanding of the morphology, genesis, and distribution of soils in Southeast Asia evolved with the establishment and development of soil surveys in different countries of the region from the 1950s. A first overview was prepared by Dudal and Moormann (1964), using the 1938 and 1960 soil classification systems of the United States Department of Agriculture (USDA) (Baldwin, Kellogg, and Thorp 1938; Soil Survey Staff 1960). A revised version was in place by 1974 (Dudal, Moormann, and Riquier 1974). Preparation of a soil map of the world at a scale of 1:5 million started in 1961 at the initiative of the Food and Agricultural Organization of the United Nations (FAO), UNESCO, and the International Society of Soil Science (ISSS). In 1974 a unified soil classification was prepared and published (FAO 1974). A volume was specifically devoted to Southeast Asia (FAO 1979). The present chapter is based on this publication, and reference should be made to it and the accompanying map (1:5 million) for detailed information about the soils of the region.

Computerized Cone Penetration Test for Soil Classification

2008 ◽  
Vol 2053 (1) ◽  
pp. 47-64 ◽  
Author(s):  
Murad Y. Abu-Farsakh ◽  
Zhongjie Zhang ◽  
Mehmet Tumay ◽  
Mark Morvant
Keyword(s):  
Classification System ◽  
Soil Classification ◽  
Cone Penetration Test ◽  
Classification Systems ◽  
Fuzzy Classification ◽  
Classification Methods ◽  
Penetration Test ◽  
Cone Penetration ◽  
Cone Tip Resistance ◽  
Tip Resistance

Computerized MS-Windows Visual Basic software of a cone penetration test (CPT) for soil classification was developed as part of an extensive effort to facilitate the implementation of CPT technology in many geotechnical engineering applications. Five CPT soil engineering classification systems were implemented as a handy, user-friendly, software tool for geotechnical engineers. In the probabilistic region estimation and fuzzy classification methods, a conformal transformation is first applied to determine the profile of soil classification index (U) with depth from cone tip resistance (qc) and friction ratio (Rf). A statistical correlation was established in the probabilistic region estimation method between the U index and the compositional soil type given by the Unified Soil Classification System. Conversely, the CPT fuzzy classification emphasizes the certainty of soil behavior. The Schmertmann and Douglas and Olsen methods provide soil classification charts based on cone tip resistance and friction ratio. However, Robertson et al. proposed a three-dimensional classification system that is presented in two charts: one chart uses corrected tip resistance (qt) and friction ratio (Rf); the other chart uses qt and pore pressure parameter (Bq) as input data. Five sites in Louisiana were selected for this study. For each site, CPT tests and the corresponding soil boring results were correlated. The soil classification results obtained using the five different CPT soil classification methods were compared.

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

Soil Research ◽  
2020 ◽  
Vol 58 (6) ◽  
pp. 519
Author(s):  
H. F. Teng ◽  
R. A. Viscarra Rossel ◽  
R. Webster
Keyword(s):  
Vector Space ◽  
Classification System ◽  
Near Infrared ◽  
Soil Classification ◽  
Classification Systems ◽  
Near Infrared Reflectance ◽  
Local Systems ◽  
Soil Units ◽  
International Systems ◽  
Australian Soil

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.

Using genetic programming to transform from Australian to USDA/FAO soil particle-size classification system

Soil Research ◽  
2012 ◽  
Vol 50 (6) ◽  
pp. 443 ◽  
Author(s):  
José Padarian ◽  
Budiman Minasny ◽  
Alex McBratney
Keyword(s):  
Particle Size ◽  
Genetic Programming ◽  
Classification Systems ◽  
Soil Survey ◽  
Pedotransfer Functions ◽  
Programming Technique ◽  
Size Classification ◽  
The Difference ◽  
Prior Models ◽  
Australian Soil

The difference between the International (adopted by Australia) and the USDA/FAO particle-size classification systems is the limit between silt and sand fractions (20 μm for the International and 50 µm for the USDA/FAO). In order to work with pedotransfer functions generated under the USDA/FAO system with Australian soil survey data, a conversion should be attempted. The aim of this work is to improve prior models using larger datasets and a genetic programming technique, in the form of a symbolic regression. The 2–50 µm fraction was predicted using a USDA dataset which included both particle-size classification systems. The presented model reduced the root mean square error (%) by 14.96 and 23.62% (IGBP-DIS dataset and Australian dataset, respectively), compared with the previous model.

Classification and Mitigation of Soil Salinization

2017 ◽  
Author(s):  
Tibor Tóth
Keyword(s):  
Soil Salinity ◽  
Soil Classification ◽  
Soil Salinization ◽  
Classification Systems ◽  
Salt Accumulation ◽  
Soil Taxonomy ◽  
Sodic Soils ◽  
Water Rates ◽  
Irrigated Lands ◽  
The Right

Soil salinity has been causing problems for agriculturists for millennia, primarily in irrigated lands. The importance of salinity issues is increasing, since large areas are affected by irrigation-induced salt accumulation. A wide knowledge base has been collected to better understand the major processes of salt accumulation and choose the right method of mitigation. There are two major types of soil salinity that are distinguished because of different properties and mitigation requirements. The first is caused mostly by the large salt concentration and is called saline soil, typically corresponding to Solonchak soils. The second is caused mainly by the dominance of sodium in the soil solution or on the soil exchange complex. This latter type is called “sodic” soil, corresponding to Solonetz soils. Saline soils have homogeneous soil profiles with relatively good soil structure, and their appropriate mitigation measure is leaching. Naturally sodic soils have markedly different horizons and unfavorable physical properties, such as low permeability, swelling, plasticity when wet, and hardness when dry, and their limitation for agriculture is mitigated typically by applying gypsum. Salinity and sodicity need to be chemically quantified before deciding on the proper management strategy. The most complex management and mitigation of salinized irrigated lands involves modern engineering including calculations of irrigation water rates and reclamation materials, provisions for drainage, and drainage disposal. Mapping-oriented soil classification was developed for naturally saline and sodic soils and inherited the first soil categories introduced more than a century ago, such as Solonchak and Solonetz in most of the total of 24 soil classification systems used currently. USDA Soil Taxonomy is one exception, which uses names composed of formative elements.

Sign in / Sign up

Export Citation Format

Share Document