Skip to main content
SpringerLink
Log in

Pedometric Treatment of Soil Attributes

  • Chapter
  • First Online:
Pedometrics

Part of the book series: Progress in Soil Science ((PROSOIL))

Abstract

There are some universally described soil attributes that are worthy of more detailed pedometric description. Here, we largely concentrate on field properties which have particular issues associated with them. We are not attempting to be exhaustive. Over the years most countries have performed field descriptions, and laboratory analysis of soil based on some kind of standard technique. The methods that can be utilized for in-situ field description were already developed in the 1950s and refined and standardised by most countries in the 1970s and 1980s. These efforts have resulted in what is referred to as soil legacy data. The aim of this chapter is to illustrate how these soil legacy data can be modified for pedometric, quantitative and in general terms more objective soil analysis. Here, we will also discuss how we can use these quantitative descriptions to perform a more quantitative analysis of soil attributes, utilizing mathematical descriptors or how we can achieve a more quantitative measurement and assessment of soil attributes utilizing new technology and computational advances.

“The soil itself must be the object of observation and experiment and the facts obtained must be soil facts before they can be incorporated into soil science. The science of zoology was developed through the study of animals, that of botany through the study of plants, and soil science must be developed through the study of the soil”.

C. F. Marbut 1920

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  • Ackerson JP, Demattê JAM, Morgan CLS (2015) Predicting clay content on field-moist intact tropical soils using a dried, ground VisNIR library with external parameter orthogonalization. Geoderma 259–260:196–204

    Article  Google Scholar 

  • Anderson A, McBratney A (1995) Soil aggregates as mass fractals. Soil Res 33:757–772

    Article  Google Scholar 

  • Atterberg A (1905) Die rationelle Klassifikation der Sande und Kiese. Chemiker-Zeitung 29: 195–198

    Google Scholar 

  • Bagnold RA (1954) The physics of blown sand and desert dunes. Methuen, London

    Google Scholar 

  • Barrett LR (2002) Spectrophotometric color measurement in situ in well drained sandy soils. Geoderma 108:49–77

    Article  Google Scholar 

  • Barron V, Torrent J (1986) Use of the Kubelka – Munk theory to study the influence of iron oxides on soil colour. J Soil Sci 37:499–510

    Article  Google Scholar 

  • Baumann K, Schöning I, Schrumpf M, Ellerbrock RH, Leinweber P (2016) Rapid assessment of soil organic matter: soil color analysis and Fourier transform infrared spectroscopy. Geoderma 278:49–57

    Article  Google Scholar 

  • Beaudette D, Roudier P (2016) aqp: algorithms for quantitative pedology. A toolkit for soil scientists. R package version 1.9.10. URL http://aqp.r-forge.r-project.org/

  • Bedidi A, Cervelle B, Madeira J, Pouget M (1992) Moisture effects on visible spectral characteristics of lateritic soils. Soil Sci 153:129–141

    Article  Google Scholar 

  • Bellon-Maurel V, McBratney A (2011) Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils – critical review and research perspectives. Soil Biol Biochem 43:1398–1410

    Article  Google Scholar 

  • Ben-Dor E, Heller D, Chudnovsky A (2008) A novel method of classifying soil profiles in the field using optical means. Soil Sci Soc Am J 72:1113–1123

    Article  Google Scholar 

  • Berezin PN, Voronin AD (1981) Use of probability distribution functions for describing the particle-size distribution of soils. Moscow University Soil Science Bulletin (English Translation of Vestnik Moskovskogo Universiteta 36, 28–34

    Google Scholar 

  • Billmeyer FW, Saltzman M (1981) Principles of color technology. Wiley, New York

    Google Scholar 

  • Buchan GD (1989) Applicability of the simple lognormal model to particle-size distribution in soils. Soil Sci 147:155–161

    Article  Google Scholar 

  • Buchan GD, Grewal KS, Robson AB (1993) Improved models of particle-size distribution: an illustration of model comparison techniques. Soil Sci Soc Am J 57:901–908

    Article  Google Scholar 

  • Chang C-W, Laird DA, Hurburgh CRJ (2005) Influence of soil moisture on near-infrared reflectance spectroscopic measurement of soil properties. Soil Sci 170:244–255

    Article  Google Scholar 

  • Chaplot V, Bernoux M, Walter C, Curmi P, Herpin U (2001) Soil carbon storage prediction in temperate hydromorphic soils using a morphologic index and digital elevation model. Soil Sci 166:48–60

    Article  Google Scholar 

  • CIE (1931) Commission Internationale de l’Eclairage (CIE) Proceedings. Cambridge University Press, Cambridge

    Google Scholar 

  • Clark MW (1981) Quantitative shape analysis: a review. Math Geol 13:303–320

    Article  Google Scholar 

  • Eck DV, Hirmas DR, Giménez D (2013) Quantifying soil structure from field excavation walls using multistripe laser triangulation scanning. Soil Sci Soc Am J 77(4):1319–1328

    Article  Google Scholar 

  • Escadafal R (1993) Remote sensing of soil color: principles and applications. Remote Sens Rev 7:261–279

    Article  Google Scholar 

  • Escadafal R, Huete A (1991) Improvement in remote sensing of low vegetation cover in arid regions by correcting vegetation indices for soil noise. C R Acad Sci 312:1385–1391

    Google Scholar 

  • Escadafal R, Girard M-C, Courault D (1989) Munsell soil color and soil reflectance in the visible spectral bands of landsat MSS and TM data. Remote Sens Environ 27:37–46

    Article  Google Scholar 

  • Evans CV, Franzmeier DP (1988) Color index values to represent wetness and aeration in some Indiana soils. Geoderma 41:353–368

    Article  Google Scholar 

  • Fajardo M, McBratney A, Whelan B (2016) Fuzzy clustering of Vis-NIR spectra for the objective recognition of soil morphological horizons in soil profiles. Geoderma 263:244–253

    Article  Google Scholar 

  • Fernandez RN, Schulze DG (1987) Calculation of soil color from reflectance Spectra1. Soil Sci Soc Am J 51:1277–1282

    Article  Google Scholar 

  • Fontán JM, Calvache S, López-Bellido RJ, López-Bellido L (2010) Soil carbon measurement in clods and sieved samples in a Mediterranean vertisol by visible and near-infrared reflectance spectroscopy. Geoderma 156:93–98

    Article  Google Scholar 

  • Fredlund MD, Fredlund DG, Wilson GW (2000) An equation to represent grain-size distribution. Canadian Geotechnical Journal 37(4):817–827. doi:10.1139/t00-015

    Article  Google Scholar 

  • Ge L, Lai W, Lin Y (2005) Influence of and correction for moisture in rocks, soils and sediments on in situ XRF analysis. X-Ray Spectrom 34:28–34

    Article  Google Scholar 

  • Ge Y, Morgan CLS, Grunwald S, Brown DJ, Sarkhot DV (2011) Comparison of soil reflectance spectra and calibration models obtained using multiple spectrometers. Geoderma 161:202–211

    Article  Google Scholar 

  • Gee GW, Or D (2002) 2.4 Particle-size analysis. In: Methods of soil analysis. Part 4. Science Society of America, Madison, pp 255–293

    Google Scholar 

  • Geeves GW, Cresswell HP, Murphy BW, Gessler PE, Chartres CJ, Little IP, Bouwman GM (1995) The physical, chemical and morphological properties of soils in the wheat-belt of southern NSW and northern Victoria. NSW Department of Conservation and Land Management/CSIRO Aust. Division of Soils Occasional report

    Google Scholar 

  • Getreuer P (2011) Colorspace transformations. Matlab package

    Google Scholar 

  • Gobin A, Campling P, Deckers J, Feyen J (2000) Quantifying soil morphology in tropical environments: methods and application in soil classification. Soil Sci Soc Am J 64:1423–1433

    Article  Google Scholar 

  • Gómez-Robledo L, López-Ruiz N, Melgosa M, Palma AJ, Capitán-Vallvey LF, Sánchez-Marañón M (2013) Using the mobile phone as Munsell soil-colour sensor: an experiment under controlled illumination conditions. Comput Electron Agric 99:200–208

    Article  Google Scholar 

  • Harris D (2007) Quantitative chemical analysis, 7th edn. WHFrrman&Co, New York

    Google Scholar 

  • Hartemink AE, Minasny B (2014) Towards digital soil morphometrics. Geoderma 230–231:305–317

    Article  Google Scholar 

  • Hartemink AE, Minasny B (2016) Digital soil morphometrics. Springer International Publishing, Cham

    Book  Google Scholar 

  • He X, Vepraskas MJ, Lindbo DL, Skaggs RW (2003) A method to predict soil saturation frequency and duration from soil color. Soil Sci Soc Am J 67:961–969

    Article  Google Scholar 

  • Hodgson JM, Hollis JM, Jones RJA, Palmer RC (1976) A comparison of field estimates and laboratory analyses of the silt and clay contents of some west midland soils. J Soil Sci 27: 411–419

    Article  Google Scholar 

  • Holden NM (1993) A two-dimensional quantification of soil ped shape. J Soil Sci 44:209–219

    Article  Google Scholar 

  • Horta A, Malone B, Stockmann U, Minasny B, Bishop TFA, McBratney AB, Pallasser R, Pozza L (2015) Potential of integrated field spectroscopy and spatial analysis for enhanced assessment of soil contamination: a prospective review. Geoderma 241–242:180–209

    Article  Google Scholar 

  • Huete AR, Escadafal R (1991) Assessment of biophysical soil properties through spectral decomposition techniques. Remote Sens Environ 35:149–159

    Article  Google Scholar 

  • Hwang SI (2004) Effect of texture on the performance of soil particle-size distribution models. Geoderma 123:363–371

    Article  Google Scholar 

  • Hwang SI, Lee KP, Lee DS, Powers SE (2002) Models for estimating soil particle-size distributions. Soil Sci Soc Am J 66:1143–1150

    Article  Google Scholar 

  • Ihaka R, Murrell P, Hornik K, Fischer JC, Zeileis A (2015) Colourspace: color space manipulation. R package version 1.2-6. URL http://CRAN.R-project.org/package=colorspace

  • Islam K, Singh B, McBratney A (2003) Simultaneous estimation of several soil properties by ultra-violet, visible, and near-infrared reflectance spectroscopy. Soil Res 41:1101–1114

    Article  Google Scholar 

  • Ivey JL, McBride RA (1999) Delineating the zone of topsoil disturbance around buried utilities on agricultural land. Land Degrad Dev 10:531–544

    Article  Google Scholar 

  • Jaky J (1944) Soil mechanics. Egyetemi Nyomda, Budapest (In Hungarian). Cited it Probalistic solutions in geotechnics. Dev Geotech Eng 46:157

    Google Scholar 

  • Ji W, Viscarra Rossel RA, Shi Z (2015) Accounting for the effects of water and the environment on proximally sensed vis–NIR soil spectra and their calibrations. Eur J Soil Sci 66:555–565

    Article  Google Scholar 

  • Jones EJ, McBratney AB (2016a) In situ analysis of soil mineral composition through conjoint use of visible, near-infrared and X-ray fluorescence spectroscopy. In: Hartemink EA, Minasny B (eds) Digital soil morphometrics. Springer International Publishing, Cham, pp 51–62

    Chapter  Google Scholar 

  • Jones EJ, McBratney AB (2016b) What is digital soil morphometrics and where might it be going? In: Hartemink EA, Minasny B (eds) Digital soil morphometrics. Springer International Publishing, Cham, pp 1–15

    Google Scholar 

  • Knight HG (1938) New size limits for silt and clay. Soil Sci Soc Am Proc 2:502

    Article  Google Scholar 

  • Kosko B (1994) Fuzzy systems as universal approximators. IEEE Trans Comput 43:1329–1333

    Article  Google Scholar 

  • Kuhn M, Weston S, Keefer C, Coulter N (2013) Cubist package. Version 0.0.13

    Google Scholar 

  • Kusumo BH, Hedley MJ, Tuohy MP, Hedley CB, Arnold GC (2010) Predicting soil carbon and nitrogen concentrations and pasture root densities from proximally sensed soil spectral reflectance. In: Viscarra Rossel RA, McBratney AB, Minasny B (eds) Proximal soil sensing. Springer, Switzerland

    Google Scholar 

  • Laiho JVP, Perämäki P (2005) Evaluation of portable X-ray fluorescence (PXRF) sample preparation methods. Spec Paper Geol Surv Finland 38:73–82

    Google Scholar 

  • Legros JP, Pedro G (1985) The cause of particle-size distribution in soil profiles derived from crystalline rocks, France. Geoderma 36:15–25

    Article  Google Scholar 

  • Leone AP, Escadafal R (2001) Statistical analysis of soil colour and spectroradiometric data for hyperspectral remote sensing of soil properties (example in a southern Italy Mediterranean ecosystem). Int J Remote Sens 22:2311–2328

    Article  Google Scholar 

  • Leone AP, Sommer S (2000) Multivariate analysis of laboratory spectra for the assessment of soil development and soil degradation in the southern Apennines (Italy). Remote Sens Environ 72:346–359

    Article  Google Scholar 

  • Liu M, Samal A (2002a) Cluster validation using legacy delineations. Image Vis Comput 20: 459–467

    Article  Google Scholar 

  • Liu M, Samal A (2002b) A fuzzy clustering approach to delineate agroecozones. Ecol Model 149:215–228

    Article  Google Scholar 

  • Madeira J, Bedidi A, Cervelle B, Pouget M, Flay N (1997) Visible spectrometric indices of hematite (Hm) and goethite (Gt) content in lateritic soils: the application of a Thematic Mapper (TM) image for soil-mapping in Brasilia, Brazil. Int J Remote Sens 18:2835–2852

    Article  Google Scholar 

  • Mandelbrot BB (1989) Fractal geometry: what is it, and what does it do? Proc R Soc Lond A Math Phys Sci 423:3–16

    Article  Google Scholar 

  • Markowicz AA (2008) Quantification and correction procedures. In: Potts PJ, West M (eds) Portable X-ray fluorescence spectrometry: capabilities for in situ analysis. The Royal Society of Chemistry, Cambridge, pp 13–38

    Chapter  Google Scholar 

  • Mathieu R, Pouget M, Cervelle B, Escadafal R (1998) Relationships between satellite-based radiometric indices simulated using laboratory reflectance data and Typic soil color of an arid environment. Remote Sens Environ 66:17–28

    Article  Google Scholar 

  • Mathieu R, Cervelle B, Rémy D, Pouget M (2007) Field-based and spectral indicators for soil erosion mapping in semi-arid mediterranean environments (coastal cordillera of central Chile). Earth Surf Process Landf 32:13–31

    Article  Google Scholar 

  • McBratney AB, Odeh IOA (1997) Fuzzy sets in soil science application of fuzzy sets in soil science: fuzzy logic, fuzzy measurements and fuzzy decisions. Geoderma 77:85–113

    Article  Google Scholar 

  • McBratney AB, Anderson AN, Lark RM, Odeh IO (2002) 1.8 newer application techniques. In: Dane JH, Topp CG (eds) Methods of soil analysis: part 4 physical methods. Soil Science Society of America, Madison, pp 159–200

    Google Scholar 

  • Melville MD, Atkinson G (1985) Soil colour: its measurement and its designation in models of uniform colour space. J Soil Sci 36:495–512

    Article  Google Scholar 

  • Minasny B, McBratney AB (2001) The Australian soil texture boomerang: a comparison of the Australian and USDA/FAO soil particle-size classification systems. Soil Res 39:1443–1451

    Article  Google Scholar 

  • Minasny B, McBratney AB (2008) Regression rules as a tool for predicting soil properties from infrared reflectance spectroscopy. Chemom Intell Lab Syst 94:72–79

    Article  Google Scholar 

  • Minasny B, McBratney AB, Bellon-Maurel V, Roger J-M, Gobrecht A, Ferrand L, Joalland S (2011) Removing the effect of soil moisture from NIR diffuse reflectance spectra for the prediction of soil organic carbon. Geoderma 167–168:118–124

    Article  Google Scholar 

  • Moeys J (2015) Soiltexture: functions for soil texture plot, classification and transformation. R package version 1.3.3. http://CRAN.R-project.org/package=soiltexture

  • Mouazen AM, De Baerdemaeker J, Ramon H (2006) Effect of wavelength range on the measurement accuracy of some selected soil constituents using visual-near infrared spectroscopy. J Near Infrared Spectrosc 14:189–199

    Article  Google Scholar 

  • Munsell Color (2009) Munsell soil-color charts with genuine Munsell color chips. Munsell Color, Grand Rapids

    Google Scholar 

  • Nemes A, Wösten JHM, Lilly A, Oude Voshaar JH (1999) Evaluation of different procedures to interpolate particle-size distributions to achieve compatibility within soil databases. Geoderma 90:187–202

    Article  Google Scholar 

  • Nikiforoff CC (1941) Morphological classification of soil structure. Soil Sci 52:193–212

    Article  Google Scholar 

  • Odeh IOA, Chittleborough DJ, McBratney AB (1991) Elucidation of soil-landform interrelationships by canonical ordination analysis. Geoderma 49:1–32

    Article  Google Scholar 

  • O’Rourke SM, Stockmann U, Holden NM, McBratney AB, Minasny B (2016) An assessment of model averaging to improve predictive power of portable vis-NIR and XRF for the determination of agronomic soil properties. Geoderma 279:31–44

    Article  Google Scholar 

  • Padarian J, Minasny B, McBratney A (2012) Using genetic programming to transform from Australian to USDA/FAO soil particle-size classification system. Soil Res 50(6):443–446

    Article  Google Scholar 

  • Pettijohn FJ (1957) Sedimentary rocks. Harper and Row, New York

    Google Scholar 

  • Quinlan JR( 1993) Combining instance-based and model-based learning. Proceedings of the tenth international conference on machine learning, San Mateo, CA, pp 236–243

    Chapter  Google Scholar 

  • Ringrose-Voase AJ (1987) A scheme for the quantitative description of soil macrostructure by image analysis. J Soil Sci 38:343–356

    Article  Google Scholar 

  • Roger J-M, Chauchard F, Bellon-Maurel V (2003) EPO–PLS external parameter orthogonalisation of PLS application to temperature-independent measurement of sugar content of intact fruits. Chemom Intell Lab Syst 66:191–204

    Article  Google Scholar 

  • Roudier P, Manderson A, Hedley C (2016) Advances towards quantitative assessments of soil profile properties. In: Hartemink EA, Minasny B (eds) Digital soil morphometrics. Springer International Publishing, Cham, pp 113–132

    Chapter  Google Scholar 

  • Rousseva SS (1997) Data transformations between soil texture schemes. Eur J Soil Sci 48:749–758

    Article  Google Scholar 

  • Sánchez-Marañón M, Huertas R, Melgosa M (2005) Colour variation in standard soil-colour charts. Soil Res 43:827–837

    Article  Google Scholar 

  • Sánchez-Marañón M, Martín-García JM, Delgado R (2011) Effects of the fabric on the relationship between aggregate stability and color in a Regosol–Umbrisol soilscape. Geoderma 162:86–95

    Article  Google Scholar 

  • Sharma A, Weindorf DC, Man T, Aldabaa AAA, Chakraborty S (2014) Characterizing soils via portable X-ray fluorescence spectrometer: 3. Soil reaction (pH). Geoderma 232–234:141–147

    Article  Google Scholar 

  • Sharma A, Weindorf DC, Wang D, Chakraborty S (2015) Characterizing soils via portable X-ray fluorescence spectrometer: 4. Cation exchange capacity (CEC). Geoderma 239–240:130–134

    Article  Google Scholar 

  • Shepherd KD, Walsh MG (2002) Development of reflectance spectral libraries for characterization of soil properties. Soil Sci Soc Am J 66:988–998

    Article  Google Scholar 

  • Shields JA, St. Arnaud RJ, Paul EA, Clayton JS (1966) Measurement of soil color. Can J Soil Sci 46:83–90

    Article  Google Scholar 

  • Shiozawa S, Campbell G (1991) On the calculation of the mean particle diameter and standard deviation from sand, silt, and clay fractions. Soil Sci 152(6):427–431

    Article  Google Scholar 

  • Shirazi MA, Hart JW, Boersma L (1988) A unifying quantitative analysis of soil texture: improvement of precision and extension of scale. Soil Sci Soc Am J 52:181–190

    Article  Google Scholar 

  • Shirazi MA, Boersma L (1984) A unifying quantitative analysis of soil texture. Soil Sci Soc Am J 48:142–147

    Article  Google Scholar 

  • Skaggs TH, Arya LM, Shouse PJ, Mohanty BP (2001) Estimating particle-size distribution from limited soil texture data. Soil Sci Soc Am J 65(4):1038–1044

    Article  Google Scholar 

  • Soriano-Disla JM, Janik LJ, Viscarra Rossel RA, MacDonald LM, McLaughlin MJ (2014) The performance of visible, near-, and mid-infrared reflectance spectroscopy for prediction of soil physical, chemical, and biological properties. Appl Spectrosc Rev 49:139–186

    Article  Google Scholar 

  • Spielvogel S, Knicker H, Kögel-Knabner I (2004) Soil organic matter composition and soil lightness. J Plant Nutr Soil Sci 167:545–555

    Article  Google Scholar 

  • Stenberg B, Viscarra Rossel RA, Mouazen AM, Wetterlind J (2010) Visible and near infrared spectroscopy in soil science. Adv Agron 107:163–215

    Article  Google Scholar 

  • Stockmann U, Cattle SR, Minasny B, McBratney AB (2016a) Utilizing portable X-ray fluorescence spectrometry for in-field investigation of pedogenesis. Catena 139:220–231

    Article  Google Scholar 

  • Stockmann U, Jang HJ, Minasny B, McBratney AB (2016b) The effect of soil moisture and texture on Fe concentration using portable X-ray fluorescence spectrometers. In: Hartemink EA, Minasny B (eds) Digital soil morphometrics. Springer International Publishing, Cham, pp 63–71

    Chapter  Google Scholar 

  • Sudduth KA, Hummel JW (1993) Portable, near-infrared spectrophotometer for rapid soil analysis. Trans Am Soc Agric Eng 36:185–193

    Article  Google Scholar 

  • Sudduth KA, Hummel JW (1996) Geographic operating range evaluation of a NIR soil sensor. Trans Am Soc Agric Eng 39:1599–1604

    Article  Google Scholar 

  • Sutherland RA, Lee C-T (1994) Discrimination between coastal subenvironments using textural characteristics. Sedimentology 41:1133–1145

    Article  Google Scholar 

  • Terrain TNCFSA (2009) Australian soil and land survey field handbook. CSIRO Publishing, Melbourne

    Google Scholar 

  • Thompson JA, Bell JC (1996) Color index for identifying hydric conditions for seasonally saturated Mollisols in Minnesota. Soil Sci Soc Am J 60:1979–1988

    Article  Google Scholar 

  • Torrent J, Schwertmann U, Fechter H, Alferez F (1983) Quantitative relationships between soil color and hematite content. Soil Sci 136:354–358

    Article  Google Scholar 

  • Viscarra Rossel RA, Minasny B, Roudier P, McBratney AB (2006a) Colour space models for soil science. Geoderma 133:320–337

    Article  Google Scholar 

  • Viscarra Rossel RA, Walvoort DJJ, McBratney AB, Janik LJ, Skjemstad JO (2006b) Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma 131:59–75

    Article  Google Scholar 

  • Viscarra Rossel RA, Fouad Y, Walter C (2008) Using a digital camera to measure soil organic carbon and iron contents. Biosyst Eng 100:149–159

    Article  Google Scholar 

  • Viscarra Rossel RA, Cattle SR, Ortega A, Fouad Y (2009) In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy. Geoderma 150:253–266

    Article  Google Scholar 

  • Viscarra Rossel RA, Adamchuk VI, Sudduth KA, McKenzie NJ, Lobsey C (2011) Proximal soil sensing: an effective approach for soil measurements in space and time. Adv Agron 113: 243–291

    Article  Google Scholar 

  • Viscarra Rossel RA, Behrens T, Ben-Dor E, Brown DJ, Demattê JAM, Shepherd KD, Shi Z, Stenberg B, Stevens A, Adamchuk V, Aïchi H, Barthès BG, Bartholomeus HM, Bayer AD, Bernoux M, Böttcher K, Brodský L, Du CW, Chappell A, Fouad Y, Genot V, Gomez C, Grunwald S, Gubler A, Guerrero C, Hedley CB, Knadel M, Morrás HJM, Nocita M, Ramirez-Lopez L, Roudier P, Campos EMR, Sanborn P, Sellitto VM, Sudduth KA, Rawlins BG, Walter C, Winowiecki LA, Hong SY, Ji W (2016) A global spectral library to characterize the world’s soil. Earth Sci Rev 155:198–230

    Article  Google Scholar 

  • Vogel HJ, Cousin I, Roth K (2002) Quantification of pore structure and gas diffusion as a function of scale. Eur J Soil Sci 53:465–473

    Article  Google Scholar 

  • Vogel HJ, Weller U, Schlüter S (2010) Quantification of soil structure based on Minkowski functions. Comput Geosci 36:1236–1245

    Article  Google Scholar 

  • Waiser TH, Morgan CLS, Brown DJ, Hallmark CT (2007) In situ characterization of soil clay content with visible near-infrared diffuse reflectance spectroscopy. Soil Sci Soc Am J 71: 389–396

    Article  Google Scholar 

  • Walker PH, Chittleborough DJ (1986) Development of particle-size distributions in some Alfisols of southeastern Australia. Soil Sci Soc Am J 50:394–400

    Article  Google Scholar 

  • Wang D, Chakraborty S, Weindorf DC, Li B, Sharma A, Paul S, Ali MN (2015) Synthesized use of VisNIR DRS and PXRF for soil characterization: Total carbon and total nitrogen. Geoderma 243–244:157–167

    Article  Google Scholar 

  • Weindorf DC, Herrero J, Castañeda C, Bakr N, Swanhart S (2013) Direct soil gypsum quantification via portable x-ray fluorescence spectrometry. Soil Sci Soc Am J 77:2071–2077

    Article  Google Scholar 

  • Weindorf DC, Bakr N, Zhu Y (2014a) Chapter one – advances in portable X-ray fluorescence (PXRF) for environmental, pedological, and agronomic applications. In: Donald LS (ed) Advances in agronomy. Academic, Amsterdam, pp 1–45

    Google Scholar 

  • Weindorf DC, Bakr N, Zhu Y, McWhirt A, Ping CL, Michaelson G, Nelson C, Shook K, Nuss S (2014b) Influence of ice on soil elemental characterization via portable X-ray fluorescence spectrometry. Pedosphere 24:1–12

    Article  Google Scholar 

  • Wickham C (2016) Munsell: utilities for using Munsell colours. R package version 0.4.3. http://CRAN.R-project.org/package=munsell

  • Wijewardane NK, Ge Y, Morgan CLS (2016) Prediction of soil organic and inorganic carbon at different moisture contents with dry ground VNIR: a comparative study of different approaches. Eur J Soil Sci 67:605

    Article  Google Scholar 

  • Wold S, Sjöström M, Eriksson L (2001) PLS-regression: a basic tool of chemometrics. Chemom Intell Lab Syst 58:109–130

    Article  Google Scholar 

  • Wu C-Y, Jacobson AR, Laba M, Baveye PC (2009) Alleviating moisture content effects on the visible near-infrared diffuse-reflectance sensing of soils. Soil Sci 174:456–465

    Article  Google Scholar 

  • Wyrwoll KH, Smyth GK (1985) On using the log-hyperbolic distribution to describe the textural characteristics of eolian sediments. J Sediment Petrol 55:471–478

    Google Scholar 

  • Wyszecki G, Stiles WS (1982) Color science: concepts and methods, quantitative data and formulae. Wiley, New York

    Google Scholar 

  • Young IM, Crawford JW, Rappoldt C (2001) New methods and models for characterising structural heterogeneity of soil. Soil Tillage Res 61:33–45

    Article  Google Scholar 

  • Zadeh LA (1965) Fuzzy sets. Inf Control 8:338–353

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Sydney Institute of Agriculture & School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia

    Uta Stockmann, Edward J. Jones, Inakwu O. A. Odeh & Alex. B. McBratney

Authors
  1. Uta Stockmann
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Edward J. Jones
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Inakwu O. A. Odeh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Alex. B. McBratney
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Uta Stockmann .

Editor information

Editors and Affiliations

  1. Sydney Institute of Agriculture & School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia

    Alex. B. McBratney

  2. Sydney Institute of Agriculture & School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia

    Budiman Minasny

  3. Sydney Institute of Agriculture & School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia

    Uta Stockmann

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Stockmann, U., Jones, E.J., Odeh, I.O.A., McBratney, A.B. (2018). Pedometric Treatment of Soil Attributes. In: McBratney, A., Minasny, B., Stockmann, U. (eds) Pedometrics. Progress in Soil Science. Springer, Cham. https://doi.org/10.1007/978-3-319-63439-5_5

Download citation

Publish with us

Policies and ethics

Search

Navigation