Estimating Atterberg limits of soils from reflectance spectroscopy and pedotransfer functions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F21%3A85572" target="_blank" >RIV/60460709:41210/21:85572 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S0016706121003803" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0016706121003803</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.geoderma.2021.115300" target="_blank" >10.1016/j.geoderma.2021.115300</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Estimating Atterberg limits of soils from reflectance spectroscopy and pedotransfer functions

Popis výsledku v původním jazyce

Attenberg limits are broadly used for engineering and geology purposes as well as in agricultural and environmental applications. Laboratory methods used for their determination are, however, laborious, destructive and tool dependent. The aim of this study was to test the feasibility of using visible near infrared spectroscopy as a fast and accurate alternative to the conventional measurement of Atterberg limits and the PI for 229 geographically diverse soil samples originating from 24 countries. Three types of calibration techniques including Partial Least Squares (PLS) regression, Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were applied to the spectral data. The performance of the best visNIRS models was validated using 45 independent samples and compared with two existing and one newly developed pedotransfer functions (PTF). The application of SVM yielded marginally better predictive ability than PLS and ANN for all modelled properties. The SVM models estimated LL, PL, and

Název v anglickém jazyce

Estimating Atterberg limits of soils from reflectance spectroscopy and pedotransfer functions

Popis výsledku anglicky

Attenberg limits are broadly used for engineering and geology purposes as well as in agricultural and environmental applications. Laboratory methods used for their determination are, however, laborious, destructive and tool dependent. The aim of this study was to test the feasibility of using visible near infrared spectroscopy as a fast and accurate alternative to the conventional measurement of Atterberg limits and the PI for 229 geographically diverse soil samples originating from 24 countries. Three types of calibration techniques including Partial Least Squares (PLS) regression, Artificial Neural Networks (ANN) and Support Vector Machines (SVM) were applied to the spectral data. The performance of the best visNIRS models was validated using 45 independent samples and compared with two existing and one newly developed pedotransfer functions (PTF). The application of SVM yielded marginally better predictive ability than PLS and ANN for all modelled properties. The SVM models estimated LL, PL, and

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40104 - Soil science

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Geoderma

ISSN

0016-7061

e-ISSN

1872-6259

Svazek periodika

402

Číslo periodika v rámci svazku

nov

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

10

Strana od-do

0-0

Kód UT WoS článku

000688581600001

EID výsledku v databázi Scopus

2-s2.0-85112433450