Using data mining to model and interpret soil diffuse reflectance spectra.

1,151 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Estimating the soil clay content and organic matter by means of different calibration methods of vis-NIR diffuse reflectance spectroscopy (2016, positive): “SVR has gained extensive application in soil spectroscopy, because of its advantages and high performance (Viscarra Rossel and Behrens, 2010; Vohland et al., 2011).”
Biological indicators of soil quality and soil organic matter characteristics in an agricultural management continuum (2013, background): “These signals are much weaker than fundamental bands in the mid-infrared region, and therefore, interpretation of the VNIR spectra require more advanced statistical techniques (Viscarra Rossel and Behrens 2010).”
Two preprocessing techniques to reduce model covariables in soil property predictions by Vis-NIR spectroscopy (2017, methodology): “Higher performances to predict clay content using SVM were achieved by Viscarra Rossel and Behrens (2010) (R2 = 0.84, RMSE = 7.63%).”