Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties

doi:10.1016/J.GEODERMA.2005.03.007

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Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties

Journal Article•DOI•

Visible, near infrared, mid infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties

R. A. Viscarra Rossel¹, Dennis Walvoort², Alex B. McBratney¹, Les J. Janik³, Jan O. Skjemstad³ - Show less +1 more•Institutions (3)

University of Sydney¹, Wageningen University and Research Centre², Commonwealth Scientific and Industrial Research Organisation³

01 Mar 2006-Geoderma (Elsevier)-Vol. 131, Iss: 1, pp 59-75

TL;DR: In this article, partial least squares regression (PLSR) was used to construct calibration models which were independently validated for the prediction of various soil properties from the soil spectra, including soil pHCa,p H w, lime requirement (LR), organic carbon (OC), clay, silt, sand, cation exchange capacity, exchangeable calcium (Ca), exchangeable aluminium (Al), nitrate-nitrogen (NO3-N), available phosphorus (PCol), exchangeability potassium (K) and electrical conductivity (EC).

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About: This article is published in Geoderma.The article was published on 2006-03-01. It has received 1730 citations till now. The article focuses on the topics: Soil test & Cation-exchange capacity.

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Journal Article•DOI•

Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps

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David J. Mulla¹•Institutions (1)

University of Minnesota¹

01 Apr 2013-Biosystems Engineering

TL;DR: A variety of spectral indices now exist for various precision agriculture applications, rather than a focus on only normalised difference vegetation indices as discussed by the authors, and the spectral bandwidth has decreased dramatically with the advent of hyperspectral remote sensing, allowing improved analysis of specific compounds, molecular interactions, crop stress, and crop biophysical or biochemical characteristics.

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1,296 citations

Cites methods from "Visible, near infrared, mid infrare..."

...…spectra have been used to interpret hyperspectral remote sensing data, including partial least squares (Lindgren, Geladi, & Wold, 1994; Viscarra Rossel et al., 2006), principal components analysis (Geladi, 2003), and pattern classification and recognition techniques (Stuckens, Coppin, & Bauer,…...
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...Advanced statistical methods for chemometric analysis of reflectance spectra have been used to interpret hyperspectral remote sensing data, including partial least squares (Lindgren, Geladi, & Wold, 1994; Viscarra Rossel et al., 2006), principal components analysis (Geladi, 2003), and pattern classification and recognition techniques (Stuckens, Coppin, & Bauer, 2000), including object oriented (Frohn, Reif, Lane, & Autrey, 2009) and decision tree (Wright & Gallant, 2007) classification techniques....
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...Viscarra Rossel, R. A., Walvoort, D. J. J., McBratney, A. B., Janik, L. J., & Skjemstad, J. O. (2006)....
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...The amount of radiation reflected by bare soils is affected primarily by soil moisture and organic matter content, but also by clay minerals and calcium carbonate or iron oxides (Thomasson, Sui, Cox, & AleRajehy, 2001; Viscarra Rossel, Walvoort, McBratney, Janik, & Skjemstad, 2006)....
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Book Chapter•DOI•

Visible and Near Infrared Spectroscopy in Soil Science

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Bo Stenberg¹, Raphael A. Viscarra Rossel², Abdul Mounem Mouazen³, Johanna Wetterlind¹•Institutions (3)

Swedish University of Agricultural Sciences¹, Commonwealth Scientific and Industrial Research Organisation², Cranfield University³

01 Jan 2010-Advances in Agronomy

TL;DR: A review on the state of soil visible-near infrared (vis-NIR) spectroscopy is provided in this article, focusing on important soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy metals.

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Abstract: This chapter provides a review on the state of soil visible–near infrared (vis–NIR) spectroscopy Our intention is for the review to serve as a source of up-to-date information on the past and current role of vis–NIR spectroscopy in soil science It should also provide critical discussion on issues surrounding the use of vis–NIR for soil analysis and on future directions To this end, we describe the fundamentals of visible and infrared diffuse reflectance spectroscopy and spectroscopic multivariate calibrations A review of the past and current role of vis–NIR spectroscopy in soil analysis is provided, focusing on important soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy metals We then discuss the performance and generalization capacity of vis–NIR calibrations, with particular attention on sample pretratments, covariations in data sets, and mathematical data preprocessing Field analyses and strategies for the practical use of vis–NIR are considered We conclude that the technique is useful to measure soil water and mineral composition and to derive robust calibrations for SOM and clay content Many studies show that we also can predict properties such as pH and nutrients, although their robustness may be questioned For future work we recommend that research should focus on: (i) moving forward with more theoretical calibrations, (ii) better understanding of the complexity of soil and the physical basis for soil reflection, and (iii) applications and the use of spectra for soil mapping and monitoring, and for making inferences about soils quality, fertility and function To do this, research in soil spectroscopy needs to be more collaborative and strategic The development of the Global Soil Spectral Library might be a step in the right direction

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1,063 citations

Cites background from "Visible, near infrared, mid infrare..."

...Viscarra Rossel et al. (2006a) modeled mineral-organic mixes as a function of vis–NIR spectra to estimate mineral-organic composition of independent test mixes....
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...…and sub soil 2-72 19 250-2500nm 0.72 8.9 (Islam et al., 2003) NSW Australia; 17 ha field Top soil 8-24 3 1000-2500nm 0.60 1.9 (Viscarra Rossel et al., 2006b) Canadian district Profiles 1-87 NA 1100-2498nm 0.81 8.6 (Malley et al., 2000) Swedish agriculture Top soil 0-70 15 1100-2500…...
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...…Australia Top and sub soil 0-40 9 250-2500nm 0.05 9.8 (Islam et al., 2003) NSW Australia; 17 ha field Top soil 6-20 3 1000-2500nm 0.41 2.3 (Viscarra Rossel et al., 2006b) Canadian districts Profiles 1-76 NA 1100-2498nm 0.36 13.2 (Malley et al., 2000) Sand Origin Soil information Range S.D.…...
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...For this reason, a number of studies have used soil color to estimate SOM (e.g., Viscarra Rossel et al., 2006b, 2008b)....
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...…and crushing, the sample is not affected by the analysis in any way, no (hazardous) chemicals are required, measurement takes a few seconds, several soil properties can be estimated from a single scan, and the technique can be used both in the laboratory and in situ (Viscarra Rossel et al., 2006c)....
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Journal Article•DOI•

Using data mining to model and interpret soil diffuse reflectance spectra.

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R. A. Viscarra Rossel¹, Thorsten Behrens²•Institutions (2)

Commonwealth Scientific and Industrial Research Organisation¹, University of Tübingen²

15 Aug 2010-Geoderma

TL;DR: In this article, the root mean square error (RMSE) and the Akaike Information Criterion (AIC) were used to compare different data mining algorithms for modelling soil visible-near infrared (vis-NIR) diffuse reflectance spectra and to assess the interpretability of the results.

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928 citations

Journal Article•DOI•

Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy

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Véronique Bellon-Maurel¹, Elvira Fernández-Ahumada¹, B. Palagos¹, Jean-Michel Roger¹, Alex B. McBratney² - Show less +1 more•Institutions (2)

SupAgro¹, University of Sydney²

01 Oct 2010-Trends in Analytical Chemistry

TL;DR: In this paper, the authors investigated the critical points to be aware of when accuracy of NIR-based measurements is assessed and proposed a new index based on the quartiles of the empirical distribution.

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Abstract: Near-infrared (NIR) and mid-IR spectroscopy applied to soil compositional analysis started to develop markedly in the 1990s, taking advantage of earlier advances in instrumentation and chemometrics for agricultural products. Today, NIR spectroscopy is envisioned as replacing laboratory analysis in certain applications (e.g., soil-carbon-credit assessment at the farm level). However, accuracy is still unsatisfactory compared with standard laboratory procedures, leading some authors to think that such a challenge will never be met. This article investigates the critical points to be aware of when accuracy of NIR-based measurements is assessed. First is the decomposition of the standard error of prediction into components of bias and variance, only the latter being reducible by averaging. This decomposition is not used routinely in the soil-science literature. Contrarily, a log-normal distribution of reference values is very often encountered with soil samples [e.g., elemental concentrations (e.g., carbon)] with numerous small or zero values. These very skewed distributions make us take precautions when using inverse regression methods (e.g., principal component regression or partial least squares), which force the predictions towards the centre of the calibration set, leading to negative effects on the standard error prediction – and therefore on prediction accuracy – especially when log-normal distributions are encountered. Such distributions, which are very common for soil components, also make the ratio of performance to deviation a useless, even hazardous, tool, leading to erroneous conclusions. We propose a new index based on the quartiles of the empirical distribution – ratio of performance to inter-quartile distance – to overcome this problem.

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668 citations

Journal Article•DOI•

The use of remote sensing in soil and terrain mapping — A review

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Vera Leatitia Mulder¹, S. de Bruin¹, Michael E. Schaepman², Michael E. Schaepman¹, T. Mayr³ - Show less +1 more•Institutions (3)

Wageningen University and Research Centre¹, University of Zurich², Cranfield University³

15 Apr 2011-Geoderma

TL;DR: In this article, the use of optical and microwave remote sensing data for soil and terrain mapping with emphasis on applications at regional and coarser scales is reviewed. But, most studies so far have been performed on a local scale and only few on regional or smaller map scale.

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635 citations

Cites background or methods from "Visible, near infrared, mid infrare..."

...However, the relationships are not sufficiently robust for practical application in wide variety of soils (Viscarra Rossel et al., 2006a)....
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...Examples include sand, silt and clay (Chang and Laird, 2002; Hahn and Gloaguen, 2008; Minasny et al., 2008; Nanni and Demattê, 2006; Salisbury and D'Aria, 1992), Fe2O3, SiO2, Al2O3 (Boardman, 1994; Genú and Demattê, 2006; Nanni and Demattê, 2006; Stoner and Baumgardner, 1981), soil organic matter (Ben-Dor et al., 2002; Chang and Laird, 2002; Gomez et al., 2008; McCarty et al., 2002; Metternicht and Zinck, 2003; Stoner and Baumgardner, 1981; ViscarraRossel et al., 2006a), soilmoisture, salt and carbonates (Ben-Dor et al., 2002; Farifteh et al., 2006)....
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...A wide variety of soil attributes have been derived with use of statistical and chemometric analysis of spectroscopic data (Minasny and McBratney, 2008; Viscarra Rossel, 2008) which can be used for digital soil mapping (Minasny et al., 2009)....
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...…these methods are useful tools for predicting soil texture, but calibration of the models is based on local conditions and therefore these models will typically not work outside the studied areas (Demattê et al., 2007; Minasny et al., 2008; Thomasson et al., 2001; Viscarra Rossel et al., 2006b)....
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...98 between spectrally measured and chemically analysed samples have been obtained using mid infrared and combined diffuse reflectance spectroscopy (Barnes et al., 2003; Chang and Laird, 2002; McCarty et al., 2002; Viscarra Rossel et al., 2006b)....
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Bradley Efron¹, Robert Tibshirani•Institutions (1)

South Dakota School of Mines and Technology¹

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TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.

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Abstract: AN EXAMINATION OF THE DEGTJAREFF METHOD FOR DETERMINING SOIL ORGANIC MATTER, AND A PROPOSED MODIFICATION OF THE CHROMIC ACID TITRATION METHOD A. WALKLEY;I. BLACK; Soil Science

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17,132 citations

Additional excerpts

...Dichromate oxidation Walkley and Black (1934)...
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TL;DR: In this article, the authors describe methods of particle-size analysis for soils, including a variety of classification schemes and standard methods for size distributions using pipet and hydrometer techniques.

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Abstract: Book Chapter describing methods of particle-size analysis for soils. Includes a variety of classification schemes. Standard methods for size distributions using pipet and hydrometer techniques are described. New laser-light scattering and related techniques are discussed. Complete with updated references.

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Paul Geladi¹, Bruce R. Kowalski¹•Institutions (1)

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TL;DR: In this paper, a tutorial on the Partial Least Squares (PLS) regression method is provided, and an algorithm for a predictive PLS and some practical hints for its use are given.

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6,393 citations

"Visible, near infrared, mid infrare..." refers background in this paper

...PLSR takes advantage of the correlation that exists between the spectra and the soil, thus the resulting spectral vectors are directly related to the soil attribute (Geladi and Kowalski, 1986)....
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