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Effect of the Continuum Removal in Predicting Soil Organic Carbon with Near Infrared Spectroscopy (NIRS) in the Senegal Sahelian Soils

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Document pages: 14 pages

Abstract: Spectroscopyplays a major role in the access of the analytical parameters of the soil. Ittends to substitute the conventional laboratory analysis because hyperspectraldata were least expensive and easier to obtain. The objective of this study wasto evaluate the effect of the continuum removal (CR) in the validation of theaccurate prediction model of the soil properties with Vis-NIR spectroscopy data. Few studiesusing Vis-NIR reflectance spectroscopy have well focused the calculation of theCR method; its effect in the calibration of the accurate models was also notwell emphasized. In this study, we used the remote sensing software ENVI 4.7 to compute the CR function where the value of the continuum foreach sample and for each spectral wavelength was obtained by dividing thereflectance values of the full spectrum (FS) with those of the continuum curve(CC). The partial least square regression (PLSR) model was applied in thespectral data from the soil of the Senegal Sahelian region. It was calibrated withboth data from the full spectrum (FS) and those obtained after the applicationof the continuum removal. With the application of the CR, ultravioletwavelengths (350 - 429 nm) and those of near infrared (2491 - 2500 nm) wereremoved from the explanatory variables of PLSR model. With the FS, allwavelengths between 350 and 2500 nm were taken into account in predicting soilproperties. Our findings show a positive effect of the application of CR in theestimation of soil organic carbon. In calibration, the R2 increased up to 10 with the continuum removal in the model of 12 components (CP). In terms ofvalidation, it’s the 15-component model which is the most accurate with thesame range in calibration between the FS and the CR. The lowest RMSE ranged from0.04 with the FS to 0.03 with the application of the CR in calibration andvalidation. These results show that the interest of this study as soil organiccarbon is recognized as a key indicator of fertility of the soil in Sahelian-Africanregions. For future studies, it’s important to apply the model of neuralnetworks to better evaluate the effect of continuum removal in predicting soilproperties from the spectral data and other methods of preprocessing like themultiplicative scatter correction (msc).

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