Comparing Different Data Preprocessing Methods for Monitoring Soil Heavy Metals Based on Soil Spectral Features

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F15%3A68208" target="_blank" >RIV/60460709:41210/15:68208 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60076658:12520/15:43888842

Výsledek na webu

<a href="http://dx.doi.org/10.17221/113/2015-SWR" target="_blank" >http://dx.doi.org/10.17221/113/2015-SWR</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17221/113/2015-SWR" target="_blank" >10.17221/113/2015-SWR</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Comparing Different Data Preprocessing Methods for Monitoring Soil Heavy Metals Based on Soil Spectral Features

Popis výsledku v původním jazyce

The lands near mining industries in the Czech Republic are subjected to soil pollution with heavy metals. Excessive heavy metal concentrations in soils not only dramatically impact the soil quality, but also due to their persistent nature and indefinitebiological half-lives, potentially toxic metals can accumulate in the food chain and can eventually endanger human health. Monitoring and spatial information of these elements require a large number of samples and cumbersome and time-consuming laboratorymeasurements. A faster method has been developed based on a multivariate calibration procedure using support vector machine regression (SVMR) with cross-validation, to establish a relationship between reflectance spectra in the visible-near infrared (Vis-NIR) region and concentration of Mn, Cu, Cd, Zn, and Pb in soil. Spectral preprocessing methods, first and second derivatives (FD and SD), standard normal variate (SNV), multiplicative scatter correction (MSC), and continuum removal (CR

Název v anglickém jazyce

Comparing Different Data Preprocessing Methods for Monitoring Soil Heavy Metals Based on Soil Spectral Features

Popis výsledku anglicky

The lands near mining industries in the Czech Republic are subjected to soil pollution with heavy metals. Excessive heavy metal concentrations in soils not only dramatically impact the soil quality, but also due to their persistent nature and indefinitebiological half-lives, potentially toxic metals can accumulate in the food chain and can eventually endanger human health. Monitoring and spatial information of these elements require a large number of samples and cumbersome and time-consuming laboratorymeasurements. A faster method has been developed based on a multivariate calibration procedure using support vector machine regression (SVMR) with cross-validation, to establish a relationship between reflectance spectra in the visible-near infrared (Vis-NIR) region and concentration of Mn, Cu, Cd, Zn, and Pb in soil. Spectral preprocessing methods, first and second derivatives (FD and SD), standard normal variate (SNV), multiplicative scatter correction (MSC), and continuum removal (CR

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DF - Pedologie

OECD FORD obor

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Projekt

—

Návaznosti

O - Projekt operacniho programu

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Soil and Water Research

ISSN

1801-5395

e-ISSN

—

Svazek periodika

10

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

10

Strana od-do

218-227

Kód UT WoS článku

000365457100003

EID výsledku v databázi Scopus

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