| 光谱学与光谱分析 |
|
|
|
|
|
| Analysis of Visible and Near-Infrared Spectra of As-Contaminated Soil in Croplands Beside Mines |
| REN Hong-yan1, 2, 3,ZHUANG Da-fang1, 2*,QIU Dong-sheng2, 3,PAN Jian-jun1 |
1. College of Resource and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
2. Resource and Environmental Science Data Center, Chinese Academy of Sciences, Beijing 100101, China
3. Key Laboratory of Resources Remote Sensing & Digital Agriculture, Ministry of Agriculture, Beijing 100081, China |
|
|
|
|
Abstract Soil 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 R2). 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 nm. 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.
|
|
Received: 2007-09-22
Accepted: 2007-12-26
|
|
|
|
Corresponding Authors:
ZHUANG Da-fang
E-mail: zhuangdf@lreis.ac.cn
|
|
[1] CHEN Huai-man (陈怀满). Heavy Metal in the Soil-Plant System(土壤—植物系统中的重金属污染). Bejing: Science Press(北京: 科学出版社), 1996. 210.
[2] Koppnen S M, Brezonik P L, Olmanson L G, et al. Remote Sensing of Environment, 2002, 82: 38.
[3] CHI Guang-yu, LIU Xin-hui, LIU Su-hong, et al(迟光宇，刘新会，刘素红，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2006, 26(7): 1272.
[4] Ben-Dor Inbar Y, Chen Y. Remote Sensing of Environment, 1997, 61: 1.
[5] Mars J C, Crowley J K. Remote Sensing of Environment, 2003, 84: 422.
[6] Kemper T, Sommer S. Environmental Science and Technology, 2002, 36: 2742.
[7] Kooistra L, Wehren R, Buydens L M C, et al. Journal of Applied Geophysics, 2001, 3(4): 337.
[8] LIAO Xiao-yong, CHEN Tong-bin, XIE Hua, et al. Environment International, 2005, 31: 791.
[9] BAO Shi-dan(鲍士旦). Agrochemical Analysis of Soil (土壤农化分析). Beijing: Agriculture Press(北京: 农业出版社), 2000. 12.
[10] WANG Ai-ping(王爱平).Chinese Journal of Soil Science(土壤通报), 2004, 35(3): 383.
[11] United States Environmental Protection Agency (USEPA). Method 3050B: Acid Digestion of Sediments, Sludges and Soils(Rev.2). Washington: DC, 1996.
[12] Clark R N, Roush T L J. Geophys. Res. 1984, 89: 6329.
[13] WU Yun-zhao, Chen Jun, Ji Jun-feng, et al. Environmental Science and Technology, 2005, 39(3): 873.
[14] JIANG Huan-yu, YING Yi-bin(蒋焕煜, 应义斌). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2007, 27(3): 499.
[15] Kooistra L, Wehrens R, Leuven R S E W, et al. Analytica Chimica Acta, 2001, 446: 97. |
| [1] |
YANG Lin-yu1, 2, 3, DING Yu1, 2, 3*, ZHAN Ye4, ZHU Shao-nong1, 2, 3, CHEN Yu-juan1, 2, 3, DENG Fan1, 2, 3, ZHAO Xing-qiang1, 2, 3. Quantitative Analysis of Mn and Ni Elements in Steel Based on LIBS and GA-PLS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1804-1808. |
| [2] |
ZHU Meng-yuan1, 2, LÜ Bin1, 2*, GUO Ying2. Comparison of Haematite and Goethite Contents in Aeolian Deposits in Different Climate Zones Based on Diffuse Reflectance Spectroscopy and Chromaticity Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(06): 1684-1690. |
| [3] |
WENG Shi-zhuang*, CHU Zhao-jie, WANG Man-qin, WANG Nian. Reflectance Spectroscopy for Accurate and Fast Analysis of Saturated
Fatty Acid of Edible Oil Using Spectroscopy-Based 2D Convolution
Regression Network[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1490-1496. |
| [4] |
SHI Pei1, JIN Zhi-wei1, WANG Fen1*, LUO Hong-jie1, 2, ZHU Jian-feng1, YE Guo-zhen3, ZHANG Yu-feng4. Influence Mechanism of the Iron-Rich Raw Material on the Iron-Based Crystalline Glazes[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1628-1633. |
| [5] |
YI Shi-wen1, LI Jie1, 2*, WU Jing-xuan1, ZHANG Wen-hao1, ZU Peng1, LI Min1, LIN Jia-wei1. Infrared Spectral Fitting Analysis of Barium Ferrite Precursor in High Energy Ball Milling Process[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1634-1641. |
| [6] |
BAI Lu1, 2, XU Xiong1, LIU Quan-zhen1, 2, DU Yan-jun1, 2, 3, WANG Dong-hong1, 2*. Characterization and Analysis of Dissolved Organic Matter in Different
Types of Natural Water in Wuhan by Three-Dimensional
Fluorescence Spectra[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(05): 1642-1647. |
| [7] |
SHENG Liang1, YUAN Liang-jing2*, LI Dong-ling2, ZHANG Xiao-fen3, ZHANG Qiao-chu2, YU Lei2, JIA Yun-hai1*. Determination on Complex Inclusions of High-Speed Railway Wheel Using Spark Source Original Position Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1122-1128. |
| [8] |
Yumiti Maiming1, WANG Xue-mei1, 2*. Hyperspectral Estimation of Soil Organic Matter Content Based on Continuous Wavelet Transformation[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(04): 1278-1284. |
| [9] |
YANG En1, WANG Shi-bo2*. Study on Directional Near-Infrared Reflectance Spectra of Typical Types of Coal[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 847-858. |
| [10] |
ZHAO Rui1, SONG Hai-yan1*, ZHAO Yao2, SU Qin1, LI Wei1, SUN Yi-shu1, CHEN Ying-min1. Research on Anti-Moisture Interference Soil Organic Matter ModelBased on Characteristic Wavelength Integration Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 984-989. |
| [11] |
WANG Chun-juan1, 2, ZHOU Bin1, 2*, ZHENG Yao-yao3, YU Zhi-feng1, 2. Navigation Observation of Reflectance Spectrum of Water Surface in Inland Rivers[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 878-883. |
| [12] |
YANG Xin1, 2, WU Zhi-hang3, YE Yin1, 2*, CHEN Xiao-fang1, 2, YUAN Zi-ran1, 2, WANG Jing1, 2. Parallel Factor Analysis of Fluorescence Excitation Emission Matrix Spectroscopy of DOM in Waters of Agricultural Watershed of Dianbu River[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(03): 978-983. |
| [13] |
SHI Chuan-qi1, 2, LI Yan3, 4, YU Shao-peng1*, HU Bao-zhong1, 2, WANG Hui1, JIN Liang4. Study on the Effect of Foundation Pit Drainage on Water Dissolved Organic Matter in Urban River[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 498-504. |
| [14] |
JIANG Jie1, YU Quan-zhou1, 2, 3*, LIANG Tian-quan1, 2, TANG Qing-xin1, 2, 3, ZHANG Ying-hao1, 3, ZHANG Huai-zhen1, 2, 3. Analysis of Spectral Characteristics of Different Wetland Landscapes Based on EO-1 Hyperion[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 517-523. |
| [15] |
FAN Chun-hui1,2, ZHENG Jin-huan3, WANG Yu-fei3, SU Zhe3, LIN Long-jian3, YANG Chen3. Adsorption of Cadmium on Fe-Mn Nodules Derived From Soil by Spectral Methods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2022, 42(02): 616-621. |
|
|
|
|
