Using deep learning to predict soil properties from regional spectral data

• Published in: Geoderma Regional Vol. 16; p. e00198
• Main Authors: Padarian, J., Minasny, B., McBratney, A.B.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2019
• Subjects: algorithms; artificial intelligence; clay; Convolutional Neural Networks; data analysis; data collection; Europe; infrared spectroscopy; Multi-task learning; neural networks; prediction; reflectance; regression analysis; sand; Simultaneous prediction; soil organic carbon; soil properties; spectral analysis; Spectrograms; topsoil; wavelengths; Europe; Convolutional Neural Networks; Multi-task learning; Spectrograms; Simultaneous prediction

Diffuse reflectance infrared spectroscopy allows the rapid acquisition of soil information in the field or the laboratory. The vis-NIR spectroscopy research enthusiasm around the world has created regional to global soil spectral libraries. While machine learning methods have been utilised in proces...