Satellite imagery for monitoring and mapping soil chromium pollution in a mine waste dump
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41210%2F21%3A85319" target="_blank" >RIV/60460709:41210/21:85319 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.mdpi.com/2072-4292/13/7/1277" target="_blank" >https://www.mdpi.com/2072-4292/13/7/1277</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/rs13071277" target="_blank" >10.3390/rs13071277</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Satellite imagery for monitoring and mapping soil chromium pollution in a mine waste dump
Popis výsledku v původním jazyce
Weathering and oxidation of sulphide minerals in mine wastes release toxic elements in surrounding environments. As an alternative to traditional sampling and chemical analysis methods, the capability of proximal and remote sensing techniques was investigated in this study to predict Chromium (Cr) concentration in 120 soil samples collected from a dumpsite in Sarcheshmeh copper mine, Iran. The samples mineralogy and Cr concentration were determined and were then subjected to laboratory reflectance spectroscopy in the range of Visible Near Infrared Shortwave Infrared (VNIR SWIR: 350 to 2500 nm). The raw spectra were preprocessed using Savitzky Golay First Derivative (SG FD) and Savitzky Golay Second-Derivative (SG SD) algorithms. The important wavelengths were determined using Partial Least Squares Regression (PLSR) coefficients and Genetic Algorithm (GA). Artificial Neural Networks (ANN), Stepwise Multiple Linear Regression (SMLR) and PLSR data mining methods were applied to the selected spectral var
Název v anglickém jazyce
Satellite imagery for monitoring and mapping soil chromium pollution in a mine waste dump
Popis výsledku anglicky
Weathering and oxidation of sulphide minerals in mine wastes release toxic elements in surrounding environments. As an alternative to traditional sampling and chemical analysis methods, the capability of proximal and remote sensing techniques was investigated in this study to predict Chromium (Cr) concentration in 120 soil samples collected from a dumpsite in Sarcheshmeh copper mine, Iran. The samples mineralogy and Cr concentration were determined and were then subjected to laboratory reflectance spectroscopy in the range of Visible Near Infrared Shortwave Infrared (VNIR SWIR: 350 to 2500 nm). The raw spectra were preprocessed using Savitzky Golay First Derivative (SG FD) and Savitzky Golay Second-Derivative (SG SD) algorithms. The important wavelengths were determined using Partial Least Squares Regression (PLSR) coefficients and Genetic Algorithm (GA). Artificial Neural Networks (ANN), Stepwise Multiple Linear Regression (SMLR) and PLSR data mining methods were applied to the selected spectral var
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
40104 - Soil science
Návaznosti výsledku
Projekt
<a href="/cs/project/GJ18-28126Y" target="_blank" >GJ18-28126Y: Hodnocení kontaminace půdy s využitím hyperspektrálních satelitních dat</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Remote Sensing
ISSN
2072-4292
e-ISSN
2072-4292
Svazek periodika
13
Číslo periodika v rámci svazku
7
Stát vydavatele periodika
CH - Švýcarská konfederace
Počet stran výsledku
20
Strana od-do
0-20
Kód UT WoS článku
000638790600001
EID výsledku v databázi Scopus
2-s2.0-85103828575