A hybrid multi-modal DL model for soil property (SOC) prediction has been presented. The training consists of two phases: 1) Self-supervised contrastive learning and 2) supervised fine-tuning via ground truth for our downstream task, which is regression.
Our model has been trained via two different datasets:
- LUCAS: To access the LUCAS topsoil dataset (ground truth), visit: LUCAS Topsoil Dataset
- RaCA: To access the RaCA dataset (ground truth), visit: RaCA Dataset