PMID- 25881431
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20150817
LR  - 20150417
IS  - 1000-0593 (Print)
IS  - 1000-0593 (Linking)
VI  - 34
IP  - 12
DP  - 2014 Dec
TI  - Estimation of heavy metal concentrations in reclaimed mining soils using 
      reflectance spectroscopy.
PG  - 3317-22
AB  - A selection of soil samples from reclaimed mining areas were prepared to 
      establish the quantitative inversion models of the soil heavy metal (As, Zn, Cu, 
      Cr, and Pb) concentrations. The concentrations of the soil heavy metals and the 
      visible and near-infrared spectra of the soil samples were obtained in a 
      darkroom. Firstly, smoothing processing was used to smooth the noise in the 
      original spectra, and the spectral transformation techniques of first derivative 
      (FD), continuum removal (CR), and standard normal variate (SNV) were used to 
      promote the model stability and the accuracy of the prediction. Through 
      correlation analysis, the feature bands of the different transformed spectra were 
      extracted. Finally, three different inversion models were adopted and compared, 
      i. e., traditional multiple linear regression (MLR), partial least squares 
      regression (PLSR), and least squares support vector machines (LS-SVM) modeling. 
      The results indicated that: (1) the stability and accuracy of the inversion 
      models established by the different transformed spectra was high, in which LS-SVM 
      was better than PLSR, and PLSR was better than MLR (except for a few cases); and 
      (2) the spectral features extracted from the different transformed spectra had a 
      certain influence on the inversion model, in which the results based on CR 
      transformation and SNV transformation were better than the FD transformation. 
      Therefore, the quantitative estimation of heavy metal concentrations by the use 
      of reflectance spectroscopy is feasible, and the pre-processing is essential to 
      improve the accuracy of the model.
FAU - Tan, Kun
AU  - Tan K
FAU - Ye, Yuan-yuan
AU  - Ye YY
FAU - Du, Pei-jun
AU  - Du PJ
FAU - Zhang, Qian-qian
AU  - Zhang QQ
LA  - eng
PT  - Journal Article
PL  - China
TA  - Guang Pu Xue Yu Guang Pu Fen Xi
JT  - Guang pu xue yu guang pu fen xi = Guang pu
JID - 9424805
EDAT- 2015/04/18 06:00
MHDA- 2015/04/18 06:01
CRDT- 2015/04/18 06:00
PHST- 2015/04/18 06:00 [entrez]
PHST- 2015/04/18 06:00 [pubmed]
PHST- 2015/04/18 06:01 [medline]
PST - ppublish
SO  - Guang Pu Xue Yu Guang Pu Fen Xi. 2014 Dec;34(12):3317-22.