Using autoencoders to compress soil VNIR–SWIR spectra for more robust prediction of soil properties

•The autoencoder framework is applied in VNIR-SWIR soil spectroscopy.•It maps the input data into a new compressed latent space in an unsupervised way.•This compressed information leads to enhanced accuracy of prediction.•A multi-input autoencoder utilizing multiple spectral pre-treatments is also presented.•The proposed methodologies outperform their counterparts.