Data fusion of vis–NIR and PXRF spectra to predict soil physical and chemical properties

• Published in: European journal of soil science Vol. 71; no. 3; pp. 316 - 333
• Main Authors: Zhang, Yakun, Hartemink, Alfred E.
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.05.2020; Wiley Subscription Services, Inc
• Subjects: air drying; Alfisols; Algorithms; carbon; Chemical properties; Chemicophysical properties; Clay; cubist model; Data; data collection; data fusion; Data integration; Fluorescence; Methods; Mollisols; pH effects; prediction; Prediction models; Preprocessing; principal component analysis; Principal components analysis; PXRF spectra; Regression analysis; sand; silt fraction; Smoothing; Soil analysis; Soil chemistry; soil elements; Soil investigations; Soil pH; Soil properties; Soil texture; Soils; Spectra; Spectrometers; Texture; total nitrogen; vis–NIR spectra; Wisconsin; X-radiation; Wisconsin

We tested one front‐end data fusion method to combine visible near‐infrared (vis–NIR) and portable X‐ray fluorescence (PXRF) spectra for predicting different soil properties and investigated the contribution of different sensor data. A total of 197 soil samples were collected from 25 Alfisols and Mo...