基于SVR算法的林地土壤氮含量高光谱测定

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Abstract

A new method was put forward to measure the total N by hyperspectra technology. 148 fir soil samples were collected using a FieldSpec®3 spectrometer. All samples were divided randomly into 2 groups, one group with 100 samples used as calibrated set, and the other with 48 samples used as validated set. The original spectra were pretreated by different methods, and then the PLS model was established with the spectra in the range of 350-2350 nm to compare the different pretreated methods. It was found that the background information and noise of the spectra could be eliminated by the method of wavelet denoising combined with multiplicative scatter correction effectively, with the calibration R-square (C-R²) Prediction R-square (P-R²) 0.891 and 0.885, respectively. In order to optimize the result, the pretreated spectra were analyzed using the principal component analysis(PCA), and the top 4 principal components were used as the input variables for the least square support vector regression( LS-SVR) model. The C-R²and P-R² of LS-SVR model increased to 0.921 and 0.917, respectively, higher than those of PLS model, which indicated LS-SVR algorithm was more accurate. The result showed that it is feasible to estimate the nitrogen content of fir soil with hyperspectra technology, and the estimation model can be improved by the pretreatment method of wavelet denoising combined with multiplicative scatter correction and the modeling algorithm of LS-SVR.

Key words： hyperspectra nitrogen soil fertility PLS LS-SVR

Received: 25 February 2013

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	LIU Yan-shu
	PAN Yong

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LIU Yan-shu,PAN Yong. Forest soil nitrogen content estimation using hyperspectra technology based on SVR algorithm[J]. , 2013, 32(1): 84-89.

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http://www.ecolsci.com/EN/ OR http://www.ecolsci.com/EN/Y2013/V32/I1/84

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