Estimation of Organic Matter Content of North Fluvo-Aquic Soil Based on the Coupling Model of Wavelet Transform and Partial Least Squares
WANG Yan-cang1, 2, 3, YANG Gui-jun2, 3, ZHU Jin-shan1, GU Xiao-he2, 3*, XU Peng2, LIAO Qin-hong2
1. College of Geometrics, Shandong University of Science and Technology, Qindao 266590, China 2. National Engineering Research Center for Information Technology in Agriculture, Beijing 100097, China 3. Key Laboratory of Information Technology in Agriculture Ministry of Agriculture, Beijing 100097, China
Abstract：For improving the estimation accuracy of soil organic matter content of the north fluvo-aquic soil, wavelet transform technology is introduced. The soil samples were collected from Tongzhou district and Shunyi district in Beijing city. And the data source is from soil hyperspectral data obtained under laboratory condition. First, discrete wavelet transform efficiently decomposes hyperspectral into approximate coefficients and detail coefficients. Then, the correlation between approximate coefficients, detail coefficients and organic matter content was analyzed, and the sensitive bands of the organic matter were screened. Finally, models were established to estimate the soil organic content by using the partial least squares regression (PLSR). Results show that the NIR bands made more contributions than the visible band in estimating organic matter content models; the ability of approximate coefficients to estimate organic matter content is better than that of detail coefficients; The estimation precision of the detail coefficients fir soil organic matter content decreases with the spectral resolution being lower; Compared with the commonly used three types of soil spectral reflectance transforms, the wavelet transform can improve the estimation ability of soil spectral fir organic content; The accuracy of the best model established by the approximate coefficients or detail coefficients is higher, and the coefficient of determination (R2) and the root mean square error (RMSE) of the best model for approximate coefficients are 0.722 and 0.221, respectively. The R2 and RMSE of the best model for detail coefficients are 0.670 and 0.255, respectively.
Key words：Organic matter;Discrete wavelet;Hyperspectral;Partial least squares regression
王延仓1, 2, 3，杨贵军2，3，朱金山1，顾晓鹤2, 3*，徐 鹏2，廖钦洪2 . 基于小波变换与偏最小二乘耦合模型估测北方潮土有机质含量 [J]. 光谱学与光谱分析, 2014, 34(07): 1922-1926.
WANG Yan-cang1, 2, 3, YANG Gui-jun2, 3, ZHU Jin-shan1, GU Xiao-he2, 3*, XU Peng2, LIAO Qin-hong2 . Estimation of Organic Matter Content of North Fluvo-Aquic Soil Based on the Coupling Model of Wavelet Transform and Partial Least Squares . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2014, 34(07): 1922-1926.
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