DocumentCode
514972
Title
Notice of Retraction
Spectral Features and Regression Model of Mine Vegetation in the Press of Heavy Metal
Author
Hu Hong ; Yang Feng-jie ; Zhou Guang-zhu ; Li Yin-ming
Author_Institution
Coll. of Geol., Shandong Univ. of Sci. & Technol., Qingdao, China
Volume
2
fYear
2010
fDate
6-7 March 2010
Firstpage
57
Lastpage
59
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Vegetation reflectance spectra in field with spectrometer to be tested in this study, used eight kinds of spectral parameters to analysis spectral of vegetation, six kinds of heavy metal content in plant leaves to be measured, then the regression model from the spectral characteristic parameters to the heavy metal content can be built, according to this can inverse heavy metal content with spectral parameters, further analysis the pollution extent of mine vegetation. Sampling areas were polluted by Cr more seriously, secondly was Ni. The 4th point was polluted most seriously by the heavy metal, The regression equations of Pb, Cu, Zn heavy metals had high correlation coefficient. The red valley area and the water absorption area with the Zn content in leaves had a high linear correlation, the red valley depth and the water absorption depth with the Cu content in leaves had a high linear correlation.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Vegetation reflectance spectra in field with spectrometer to be tested in this study, used eight kinds of spectral parameters to analysis spectral of vegetation, six kinds of heavy metal content in plant leaves to be measured, then the regression model from the spectral characteristic parameters to the heavy metal content can be built, according to this can inverse heavy metal content with spectral parameters, further analysis the pollution extent of mine vegetation. Sampling areas were polluted by Cr more seriously, secondly was Ni. The 4th point was polluted most seriously by the heavy metal, The regression equations of Pb, Cu, Zn heavy metals had high correlation coefficient. The red valley area and the water absorption area with the Zn content in leaves had a high linear correlation, the red valley depth and the water absorption depth with the Cu content in leaves had a high linear correlation.
Keywords
regression analysis; soil pollution; spectral analysis; vegetation; China; Cr; Cu; Ni; Pb; Zn; correlation coefficient; heavy metal content; inverse heavy metal content; linear correlation; mine vegetation; plant leaves; red valley area; regression equations; regression model; soil pollution; spectral features; spectral parameters; vegetation reflectance spectra; water absorption area; water absorption depth; Absorption; Pollution measurement; Reflectivity; Sampling methods; Spectral analysis; Spectroscopy; Testing; Vegetation; Water pollution; Zinc; heavy metal; hyperspectral; regression model; spectral parameters;
fLanguage
English
Publisher
ieee
Conference_Titel
Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-6388-6
Type
conf
DOI
10.1109/ETCS.2010.398
Filename
5460018
Link To Document