IGSNRR OpenIR
analysisofvisibleandnearinfraredspectraofascontaminatedsoilincroplandsbesidemines
Ren HY(任红艳)1; Zhuang DF(庄大方)1; Qiu DS(邱冬生)2; Pan JJ(潘剑君)1
2009
Source Publicationspectroscopyandspectralanalysis
ISSN1000-0593
Volume29Issue:1Pages:114
AbstractSoil samples in the depth from 0 to 20 cm were scooped from agricultural region beside mines and prepared for determination of As concentration, Fe concentrations and organic matter content. At the same time they were scanned by mobile hyperspectral radiometer for visible and near-infrared spectra. Savitzky-Golay filter was used to smooth noises in spectrum curve because of some low signal-to-noise ratios in some regions of visible and near-infrared light, and all the spectra were resampled with the spectral interval of 10 nm Before principal component regression and partial least square regression models were constructed for predicting As concentration, Fe concentrations and OM content, several spectral preprocessing techniques like first/second derivative (F/SD), baseline correction (B), standard normalized variate (SNV), multiplicative scatter correction (MSC) and continuum removal (CR) were used for promotion of models' robustness and predicting performance. For limited samples, cross validation was carried out by repeated leave-one-out procedure, and root mean square error of prediction (RMSEP) was used for validating the prediction ability of constructed models. In this study principal component regression models behave better than partial least square regression models in representing regressing ability, reducing risk of over-fitting with less factors and ensuring models' accuracy and pertinences (relative RMSEP and R-2). Preprocessing techniques of SNV, MSC and CR improve obviously the prediction ability of models for As concentration, Fe concentrations and OM content with relative RMSEP equal to 0.304 0, 0.144 3 and 0.171 2, with number of factors equal to 5, 3 and 3, respectively. The analysis of regression vectors of selected optimal PCR models shows that several important wavelengths are simultaneously taken and helpful for prediction performance: 450, 1 000, 1 400, 1 900, 2 050, 2 200, 2 250, 2 400 and 2 470 rim. Application of the calibrated models to soil contamination of croplands is promising. Concentrations of soil contaminants and contents of other matter can be determined by reflectance spectroscopy with high spectra resolution, which would provide potent reference for remote sensing monitoring of soil and environmental quality.
Language英语
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/103252
Collection中国科学院地理科学与资源研究所
Affiliation1.南京农业大学
2.中国科学院资源环境科学数据中心
Recommended Citation
GB/T 7714
Ren HY,Zhuang DF,Qiu DS,et al. analysisofvisibleandnearinfraredspectraofascontaminatedsoilincroplandsbesidemines[J]. spectroscopyandspectralanalysis,2009,29(1):114.
APA 任红艳,庄大方,邱冬生,&潘剑君.(2009).analysisofvisibleandnearinfraredspectraofascontaminatedsoilincroplandsbesidemines.spectroscopyandspectralanalysis,29(1),114.
MLA 任红艳,et al."analysisofvisibleandnearinfraredspectraofascontaminatedsoilincroplandsbesidemines".spectroscopyandspectralanalysis 29.1(2009):114.
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