Compositional modelling of soil organic carbon fractions with deep learning and spectra

Presented on the modelling of soil organic carbon (C) fractions compositionally with deep learning. C fractions are compositional by nature, i.e. Soil C = sum(C fractions). This has largely been ignored in previous approaches. This study investigated log ratio transformation for the modeling and used deep learning for better accuracy.