[Spectral Response and Inversion Models for Prediction of Total Copper Content in Soil of Xifanping Mining Area].

In order to solve the problem of high cost and low efficiency by using the traditional soil geochemical survey methods, this paper studied the simple detection method of soil heavy metal content with visible and near-infrared reflectance spectroscopy. The study collected visible and near-infrared reflectance spectroscopy of soil samples in Xifanping mining area; then treated the reflectance spectroscopy with six mathematic changes such as differentials and continuum removal in advance; the next step was to select characteristic wavelengths that were sensitive to soil copper content by using stepwise regression method and Pearson correlation coefficient as set of comprehensive characteristic variables; finally, utilized different methods and parameters of characteristic variable selection to build the soil total copper content models and tested them. Results showed that: to extract the information of copper content in soil, the performance of different spectral transform methods varied, and each spectrum transform method corresponded to its certain sensitive spectral ranges; the inversion models based on the integrated spectrum transform information were better than that based on only one kind of spectrum transform information; as for establishing the prediction model of soil copper content by using the integrated spectrum transform information, backward elimination was better than forward selection and stepwise selection, and when the Removal is 0.20, the optimum model was obtained, its coefficients of determination(R(2))and determination coefficients of prediction(R(2)(pre))reached 0.851 and 0.830, root mean square error of calibration(RMSEC)and root mean square error of prediction(RMSEP)were 0.349 and 0.468 mg·kg(-1). The model has a good precision, and it provides a train of thought for the detection of other soil heavy metal elements with visible and near-infrared reflectance spectroscopy.