Parent material distribution mapping from tropical soils data via machine learning and portable X-ray fluorescence (pXRF) spectrometry in Brazil

Knowledge about parent material (PM) is crucial to understand the properties of overlying soils. Assessing PM of very deep soils, however, is not easy. Previous studies have predicted PM via proximal sensors and machine learning algorithms, but within small areas and with low soil variety. This stud...

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Vydáno v:	Geoderma Ročník 354; s. 113885
Hlavní autoři:	Mancini, Marcelo, Weindorf, David C., Silva, Sérgio Henrique Godinho, Chakraborty, Somsubhra, Teixeira, Anita Fernanda dos Santos, Guilherme, Luiz Roberto Guimarães, Curi, Nilton
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 15.11.2019
Témata:	B horizons Brazil Digital soil mapping discriminant analysis fluorescence land use Machine learning Parent material Pedology prediction Prediction models principal component analysis soil sampling support vector machines Tropical soils X-radiation X-ray fluorescence spectroscopy Brazil Pedology RF Digital soil mapping Prediction models Machine learning LDA Tropical soils Parent material SVM PM PCA
ISSN:	0016-7061, 1872-6259
On-line přístup:	Získat plný text
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