Journal ArticleDOI
Global soil characterization with VNIR diffuse reflectance spectroscopy
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TLDR
In this article, the authors applied visible and near-infrared (VNIR) diffuse reflectance spectroscopy (DRS) to airdry soil (b2 mm) with auxiliary predictors including sand content or pH, and obtained validation root mean squared deviation (RMSD) estimates of 54 g kg − 1 for clay, 7.9 g kg � 1 for soil organic C (SOC), 5.6 g kg ¼ 1 for inorganic C (IC), and 5.5 cmolc kg - 1 for cation exchange capacity (CAbout:
This article is published in Geoderma.The article was published on 2006-06-01. It has received 694 citations till now. The article focuses on the topics: Cation-exchange capacity & Soil survey.read more
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Book ChapterDOI
Visible and Near Infrared Spectroscopy in Soil Science
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.
Journal ArticleDOI
Using data mining to model and interpret soil diffuse reflectance spectra.
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.
Journal ArticleDOI
Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy
Véronique Bellon-Maurel,Elvira Fernández-Ahumada,B. Palagos,Jean-Michel Roger,Alex B. McBratney +4 more
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.
Journal ArticleDOI
A global spectral library to characterize the world’s soil
R. A. Viscarra Rossel,Thorsten Behrens,Eyal Ben-Dor,David J. Brown,José Alexandre Melo Demattê,Keith D. Shepherd,Zhou Shi,Bo Stenberg,Antoine Stevens,Viacheslav I. Adamchuk,Hamouda Aichi,Bernard Barthès,Harm Bartholomeus,Anita D. Bayer,Martial Bernoux,Kristin Böttcher,L. Brodský,Changwen Du,Adrian Chappell,Youssef Fouad,Valérie Genot,Cécile Gomez,Sabine Grunwald,Andreas Gubler,César Guerrero,Carolyn Hedley,Maria Knadel,H.J.M. Morrás,Marco Nocita,Leonardo Ramirez-Lopez,Pierre Roudier,E.M. Rufasto Campos,P. Sanborn,V.M. Sellitto,Kenneth A. Sudduth,Barry G. Rawlins,Christian Walter,Leigh A. Winowiecki,Suk Young Hong,Wenjun Ji,Wenjun Ji,Wenjun Ji +41 more
TL;DR: In this article, the authors developed and analyzed a global soil visible-near infrared (vis-NIR) spectral library, which is currently the largest and most diverse database of its kind, and showed that the information encoded in the spectra can describe soil composition and be associated to land cover and its global geographic distribution, which acts as a surrogate for global climate variability.
Journal ArticleDOI
The Performance of Visible, Near-, and Mid-Infrared Reflectance Spectroscopy for Prediction of Soil Physical, Chemical, and Biological Properties
José M. Soriano-Disla,Les J. Janik,Raphael A. Viscarra Rossel,Lynne M. Macdonald,Mike J. McLaughlin +4 more
TL;DR: In this article, the applicability of visible (Vis), near-infrared (NIR), and mid infrared (MIR) reflectance spectroscopy for the prediction of soil properties is discussed.
References
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A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting
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TL;DR: The model studied can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting, and it is shown that the multiplicative weight-update Littlestone?Warmuth rule can be adapted to this model, yielding bounds that are slightly weaker in some cases, but applicable to a considerably more general class of learning problems.
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