Support vector machines estimation model of soil organic carbon content in lakeside oasis
[Objective]To study rapid estimation of soil organic carbon content using hyperspectral data in the hope of providing scientific basis for rational development of land resources in lakeside oases in arid re-gions.[Methods]The north lakeside oasis of Bosten Lake was taken as the study area and the measured soil organic carbon content data were combined with the hyperspectral data.Successive Projections Algorithm(SPA)was used to screen the successive bands after SG smoothing(SG),Continuum Removal(CR)and Continuous Wavelet Transform(CWT)pre-processing for the original spectra.Support Vector Machines(SVM)models were used to estimate soil organic carbon content.[Results]Soil organic carbon content in the study area ranged from 0.69 g/kg to 50.32 g/kg,with an average value of 14.15 g/kg and a standard de-viation of 9.51 g/kg,showing moderate variability and coefficient of variation of 67.20％.The original spec-tral reflectance of soil changed with the increase of wavelength,at 350-750 nm,the spectral reflectance in-creased,at 750-2,150 nm,the spectral reflectance showed a relatively stable trend;from 2,150 nm to 2,500 nm,the spectral reflectance gradually decreased.With the increase of decomposition scale,the local characteristics of the original spectrum of soil after pretreatment by continuous wavelet transform became more and more obvious,and the absorption and reflection peaks were becoming smoother and smoother.The feature bands selected by the continuous projection algorithm were concentrated in 350-952,1,007-1,742 and 2,082-2,381 nm,and the feature bands only accounted for 0.30％of the Vis-NIR spectrum.The training set and verification set of the SVM model constructed by continuous wavelet transform and continuous projec-tion algorithm were R2=0.76,RMSE=4.78 and R2=0.94,RMSE=3.30,RPD=2.50,respectively.[Conclusion]The CWT-SPA-SVM could be effectively estimate soil organic carbon content in the study area.
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