Soil Spectral Inference with R: Analysing Digital Soil Spectra using the R Programming Environment

Voorkant
Springer Nature, 25 feb 2021 - 247 pagina's
This book provides a didactic overview of techniques for inferring information from soil spectroscopic data, and the codes in the R programming language for performing such analyses. It is intended for students, researchers and practitioners looking to infer soil information from spectroscopic data, focusing mainly on, but not restricted to, the infrared range of the electromagnetic spectrum. Little prior knowledge of the R programming language or digital soil spectra is required. We work through the steps to process spectroscopic data systematically.
 

Geselecteerde pagina's

Inhoudsopgave

1 Introduction
1
2 Getting Started with R
11
3 Materials
26
4 Data Handling of Spectra
37
5 Preprocessing of Spectra
49
6 Exploratory Soil Spectral Analysis
81
7 Similarity Between Spectra and the Detection of Outliers
114
8 Selection of the Samples for Laboratory Analysis
143
9 Estimating Soil Properties and Classes from Spectra
165
10 Spectral Transfer and Transformation
215
Copyright

Overige edities - Alles bekijken

Soil Spectral Inference with R: Analysing Digital Soil Spectra using the R ...
Alexandre M.J.-C. Wadoux,Brendan Malone,Budiman Minasny,Mario Fajardo,Alex B. McBratney
Geen voorbeeld beschikbaar - 2022
Soil Spectral Inference with R: Analysing Digital Soil Spectra using the R ...
Alexandre M.J.-C. Wadoux,Brendan Malone,Budiman Minasny,Mario Fajardo,Alex B. McBratney
Geen voorbeeld beschikbaar - 2021

Veelvoorkomende woorden en zinsdelen

2500 Wavelength nm absorbance accuracy algorithm alpha analysis apply argument average blue calculate calibration called carbon centre chapter classes clay collected colour column compute contains correction correlation create dataset define derived described distance estimate et al example function green implementation important indicate infrared install laboratory legend linear load Mahalanobis distance material matrix mean measures method mineral moisture multivariate names Note object Observed obtained original outliers package perform plot points prediction principal component random range reference reflectance regression removed required package rgb(red RMSE scale Science scores selected shows similar soil properties soil samples soil spectral soilspec specify spectra spectral library spectroscopy spectrum squares standard statistical step transformation validation values variables variance vector Wavelength nm Fig window X X X xlab ylab ylim

Over de auteur (2021)

Alexandre Wadoux is Research Associate in soil science at the University of Sydney and member of the Sydney Institute of Agriculture, Australia. Brendan Malone is Senior Research Scientist in soil science at CSIRO Canberra, Australia. Budiman Minasny is Professor in soil-landscape modelling at the University of Sydney, Australia. Mario Fajardo is Postdoctoral Research Fellow at the Precision Agriculture Laboratory of the University of Sydney, Australia. Alex McBratney is Professor of Digital Agriculture & Soil Science at the University of Sydney and Director of the Sydney Institute of Agriculture, Australia.

Bibliografische gegevens

TitelSoil Spectral Inference with R: Analysing Digital Soil Spectra using the R Programming Environment
Progress in Soil Science
AuteursAlexandre M.J.-C. Wadoux, Brendan Malone, Budiman Minasny, Mario Fajardo, Alex B. McBratney
UitgeverSpringer Nature, 2021
ISBN3030648966, 9783030648961
Lengte247 pagina's
  
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