Carbonate content in soil is an important basis for soil classification and fertility evaluation. Based on an analysis of calcium carbonate content, the authors chose 78 soil samples from Loess Plateau of Shaanxi Province as the research objects. The visible near infrared hyperspectral reflectance (350~2 500 nm) data of soil samples were obtained by hyperspectral imager. Three mathematical transformations, i.e., first-order differentiation, second-order differentiation and continuum removal, were carried out on the original spectral curve, and correlation analysis was used. The method and the continuous projection algorithm were used to select the sensitive band respectively, and the Stochastic Forest regression was used to establish the estimation model of soil calcium carbonate. According to the results obtained, the spectral curve characteristics of Huangmian soil are almost the same, there are obvious absorption characteristics at 1 440 nm, 1 900 nm, 2 200 nm and so on, and the calcium carbonate content and spectral reflectance show a positive correlation trend; the accuracy of random forest estimation model based on the second-order differential and continuous projection algorithm is the highest, the validation set R2 is 0.82, and the PRD value is 2.37.
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2021, Vol. 33 
), 姜琦刚(
