Development of a national VNIR soil-spectral library for soil classification and prediction of organic matter concentrations
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Soil visible-near infrared diffuse reflectance spectroscopy (vis-NIR DRS) has become an important area of research in the fields of remote and proximal soil sensing. The technique is considered to be particularly useful for acquiring data for soil digital mapping, precision agriculture and soil survey. In this study, 1581 soil samples were collected from 14 provinces in China, including Tibet, Xinjiang, Heilongjiang, and Hainan. The samples represent 16 soil groups of the Genetic Soil Classification of China. After air-drying and sieving, the diffuse reflectance spectra of the samples were measured under laboratory conditions in the range between 350 and 2500 nm using a portable vis-NIR spectrometer. All the soil spectra were smoothed using the Savitzky-Golay method with first derivatives before performing multivariate data analyses. The spectra were compressed using principal components analysis and the fuzzy k-means method was used to calculate the optimal soil spectral classification. The scores of the principal component analyses were classified into five clusters that describe the mineral and organic composition of the soils. The results on the classification of the spectra are comparable to the results of other similar research. Spectroscopic predictions of soil organic matter concentrations used a combination of the soil spectral classification with multivariate calibration using partial least squares regression (PLSR). This combination significantly improved the predictions of soil organic matter (R 2 = 0.899; RPD = 3.158) compared with using PLSR alone (R 2 = 0.697; RPD = 1.817). © 2014 Science China Press and Springer-Verlag Berlin Heidelberg.
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Terra, F.; Viscarra Rossel, Raphael; Demattê, J. (2019)© 2018 Soil organic carbon (C) is an important indicator of agricultural and environmental quality. It improves soil fertility and helps to mitigate greenhouse gas emissions. Soil spectroscopy with either vis–NIR (350–2500 ...
Accounting for the effects of water and the environment on proximally sensed vis-NIR soil spectra and their calibrationsJi, W.; Viscarra Rossel, Raphael; Shi, Z. (2015)© 2015 British Society of Soil Science. Visible-near infrared (vis-NIR) spectroscopy can be used to estimate soil properties effectively using spectroscopic calibrations derived from data contained in spectroscopic ...
Prediction of soil attributes using the Chinese soil spectral library and standardized spectra recorded at field conditionsJi, W.; Li, S.; Chen, S.; Shi, Z.; Viscarra Rossel, Raphael; Mouazen, A. (2016)© 2015 Elsevier B.V. Organic matter (OM), total nitrogen (TN), and pH are essential soil properties for assessing the fertility of paddy soils. They can be measured with visible and near infrared (vis-NIR) spectroscopy ...