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遥感技术与应用  2019, Vol. 34 Issue (4): 807-815    DOI: 10.11873/j.issn.1004-0323.2019.4.0807
数据与图像处理     
结合EEMD和比值导数的岩石-植物混合波谱分解
曾雅琦(),王正海(),秦昊洋,周桃勇
中山大学地球科学与工程学院,广东 广州 510275
Unmixing of Mixed Spectrum of Rocks and Vegetation Using EEMD and Derivative of Ratio Spectroscopy
Yaqi Zeng(),Zhenghai Wang(),Haoyang Qin,Taoyong Zhou
School of Earth Science and Engineering,Sun Yat-Sen University,Guangzhou 510275,China
 全文: PDF(1844 KB)   HTML
摘要:

由于混合像元的影响,野外实测波谱或从遥感影像提取的像元波谱多为混合波谱。针对高光谱遥感应用中混合像元导致的混合波谱问题,提出了一种改进的比值导数混合波谱分解方法。首先,对野外实测的岩石与植被的混合波谱预处理,消除水汽噪声;其次,使用总体平均经验模态分解法(Ensemble Empirical Mode Decomposition,EEMD)进行IMF分解,获取r分量波谱;然后,利用比值导数方法对r分量波谱进行解混;最后,选取岩石面积比为自变量,近红外波谱的特征波段反射率值为因变量,利用回归分析定量反演野外混合波谱中岩石面积比。结果表明:①基于EEMD分解获取r分量波谱消除了环境干扰,反映了混合波谱总体趋势,体现了混合波谱中的主要地物波谱特征;②对EEMD分解获取的r分量波谱进行比值导数处理,抑制植被端元组分的同时,突出岩石组分对于混合光谱的影响;③结合EEMD和比值导数法处理后的特征波谱,提高了岩石—植物混合波谱反演精度。

关键词: EEMD混合光谱比值导数定量反演    
Abstract:

The spectra field measured or from remote sensing images are mostly mixed spectra because of the influence of mixed pixel. An improved derivative of ratio spectroscopy was proposed in order to solve it in hyperspectral remote sensing applications. Firstly, the measured mixed spectra of rocks and vegetation were preprocessed, reduce moisture noise. Secondly, it was decomposed by EEMD (Ensemble Empirical Mode Decomposition) to get r component spectra. Thirdly, r component spectra were unmixed by derivative of ratio spectroscopy. Finally, the area ratio of rocks of mixed spectra can be calculated through regression analysis using the area ratio of rocks as independent variable and characteristic band reflectivity of near infrared spectroscopy as dependent variable.

Conclusions

(1) It is feasible to use EEMD to decompose spectra to get r component spectra, managing to eliminate environmental interference, get overall trend and reflect the spectral characteristics of the main features in the mixed spectra. (2) R component spectra were unmixed by derivative of ratio spectroscopy, which inhibits the influence of vegetation and highlights the influence of the rocks. (3) The inversion accuracy of mixed spectra of rocks and vegetation is improved using EEMD and derivative of ratio spectroscopy.

Key words: EEMD    Mixed spectrum    Derivative of ratio spectroscopy    Quantitative retrieval
收稿日期: 2018-06-23 出版日期: 2019-10-16
ZTFLH:  TP79  
基金资助: 国家自然科学基金项目(41572316)
通讯作者: 王正海     E-mail: z1y2q300@sina.com;wzhengh@ mail.sysu.edu.cn
作者简介: 曾雅琦(1995-),女,湖南娄底人,硕士研究生,主要从事遥感地质应用研究。E?mail:z1y2q300@sina.com
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引用本文:

曾雅琦,王正海,秦昊洋,周桃勇. 结合EEMD和比值导数的岩石-植物混合波谱分解[J]. 遥感技术与应用, 2019, 34(4): 807-815.

Yaqi Zeng,Zhenghai Wang,Haoyang Qin,Taoyong Zhou. Unmixing of Mixed Spectrum of Rocks and Vegetation Using EEMD and Derivative of Ratio Spectroscopy. Remote Sensing Technology and Application, 2019, 34(4): 807-815.

链接本文:

http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.4.0807        http://www.rsta.ac.cn/CN/Y2019/V34/I4/807

图1  波谱数据获取示意图
波谱名称 岩石面积比/% t 波谱名称 岩石面积比/% t 波谱名称 岩石面积比/% t
B1_deriv 100 42.30 B10_deriv 65.75 37.68 B19_deriv 19.55 32.97
B2_deriv 98.57 30.87 B11_deriv 60.56 38.15 B20_deriv 15.09 35.93
B3_deriv 96.02 36.77 B12_deriv 55.30 36.49 B21_deriv 10.96 28.70
B4_deriv 92.79 39.34 B13_deriv 50 35.71 B22_deriv 7.21 27.89
B5_deriv 89.04 38.41 B14_deriv 44.70 29.77 B23_deriv 3.98 24.16
B6_deriv 84.91 35.41 B15_deriv 39.44 32.52 B24_deriv 1.42 24.71
B7_deriv 80.45 32.77 B16_deriv 34.25 38.04 B25_deriv 0 3.05E-05
B8_deriv 75.74 34.45 B17_deriv 29.18 35.91
B9_deriv 70.82 30.94 B18_deriv 24.26 32.98
表1  比值导数光谱图中1.97~2.25 μm谷值提取
图2  算法流程
图3  波谱数据EEMD处理结果
图4  比值光谱图(以植被光谱为除数)
图5  比值导数光谱图
方程 模型汇总 参数估计值

R 2

(判定系数)

F

(统计量)

df1

(自由度1)

df2

(自由度2)

P

(显著值)

常数

b1

(系数1)

b2

(系数2)

b3

(系数3)

线性 0.55 19.69 1 16 0.00* 22.91 0.19
二次 0.64 13.38 2 15 0.00* 19.22 0.51 -0.01
三次 0.74 13.42 3 14 0.00* 15.42 1.19 -0.02 1.33×10-4
表2  模型汇总与参数估计值
图6  曲线拟合(线性、二次项、三次项)
图7  反演模型的验证结果
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