A Model on Extracting the Pollution Information of Heavy Metal Copper Ion Based on the Soil Spectra Analyzed by HHT in Time-Frequency
YANG Ke-ming1, WANG Guo-ping1，2, FU Ping-jie1, ZHANG Wei1, WANG Xiao-feng1
1. College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083，China
2. Beijing PIESAT Information Technology Co., Ltd., Beijing 100195, China
Abstract：The amount of information that the different Cu2+ contents in soil are mapped to the soil spectra is very weak, and the noises in the hyperspectral data are also very difficult to avoid. Thus the sky point of the research would be how to extract the weak Cu2+ information from the complex noise environment of soil spectra. The empirical mode decomposition (EMD) algorithm can effectively remove the noise in hyperspectral data. Further more, the EMD is the premise of Hilbert transform that is a kind of time-frequency analysis on nonlinear and unstable signal. Therefore the time-frequency analysis algorithm on Hilbert-Huang transform (HHT) could be used for de-noise processing and information extracting of the soil spectra after the Huang transform is introduced. In this paper, through the HHT was applied in time-frequency to analyze the soil spectra polluted by different Cu2+ concentrations, and the information mining of Cu2+ pollution in soil spectra was achieved based on the curves such as envelope, modulation signal and frequency spectrum of each intrinsic mode function (IMF) component that could be decomposed out from the original soil spectra by EMD. The study results showed that, the analyzing results of soil spectra were identical based on the time-frequency HHT when the soil was polluted by same Cu2+ concentrations, but non-identical when polluted by different Cu2+ concentrations, so that the Cu2+ content in soil can be also retrieved based on the IMF components. Accordingly, the HHT analysis in time-frequency provides a new method and idea for information extracting, spectral diagnosing and Cu2+ content retrieving of soil spectra.
Key words：Heavy metal copper pollution; Soil spectra; Empirical mode decomposition; Hilbert-Huang transform; Weak information detection; Time-frequency analysis
杨可明，汪国平，付萍杰，张 伟，王晓峰. HHT时频分析土壤光谱的重金属铜离子污染信息提取模型[J]. 光谱学与光谱分析, 2018, 38(02): 564-569.
YANG Ke-ming, WANG Guo-ping, FU Ping-jie, ZHANG Wei, WANG Xiao-feng. A Model on Extracting the Pollution Information of Heavy Metal Copper Ion Based on the Soil Spectra Analyzed by HHT in Time-Frequency. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(02): 564-569.
[1] Conforti M, Buttafuoco G, Leone A P, et al. Catena, 2013, 110(11): 44.
[2] Koppnen S M, Brezonik P L, Olmanson L G, et al. Remote Sensing of Environment, 2002, 82: 38.
[3] Koppnen S, Pulliainen J. Remote Sensing of Environment, 2002, 79: 51.
[4] Pablo H Rosso, James C Pushnik, Mui Lay, et al. Environmental Pollution, 2005, 137: 241.
[5] LIU Mei-ling, LIU Xiang-nan, LI Ting, et al(刘美玲，刘湘南，李 婷，等). Transactions of the Chinese Society of Agricultural Engineering(农业工程学报), 2010, 26(3): 191.
[6] ZHANG Long, PAN Jia-rong, ZHU Cheng(张 龙，潘家荣，朱 诚). Journal of Zhejiang University·Agric. & Life Sci.(浙江大学学报·农业与生命科学版), 2013, 39(1): 50.
[7] ZHU Ye-qing, QU Yong-hua, LIU Su-hong, et al(朱叶青，屈永华，刘素红，等). Journal of Remote Sensing(遥感学报), 2014, 18(2): 335.
[8] LI Cheng-wu, DONG Li-hui, WANG Qi-fei, et al(李成武，董利辉，王启飞，等). Journal of China Coal Society(煤炭学报), 2016, 41(8): 1933.
[9] YU Lei, HONG Yong-sheng, ZHOU Yong, et al(于 雷，洪永胜，周 勇，等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2016, 36(5): 1428.
[10] Liao Q H, Wang J H, Yang G J, et al. Journal of Applied Remote Sensing, 2013, 7(1): 1.
[11] PANG Cun-suo, LIU Lei, SHAN Tao(庞存锁，刘 磊，单 涛). Acta Electronica Sinica(电子学报), 2014, 42(2): 347.
[12] Jakubauskas M E, Legates D R, Kastens J H. Photogrammetric Engineering and Remote Sensing, 2001, 4: 461.
[13] Huang N E, Shen Z, Long S R, et al. Proc. R. Soc. Lond, 1998, A: 903.
[14] Xue Yajuan, Cao Junxing, Tian Renfei. J. Appl. Geophys., 2013, 89: 108.
[15] Xu Chuanlong, Liang Cai, Zhou Bin, et al. Chemical Engineering Science, 2010, 65(4): 1334.
