Below-ground Fungal Biodiversity Can be Monitored Using Self-Supervised Learning Satellite Features

arXiv:2604.09818 · cs.LG, cs.CE · Submitted 2026-04-10 · Read on arXiv

cs.LG, cs.CE

Submitted: 2026-04-10

Updated: 2026-09-24

Code: https://github.com/-barnes/richdem

Terminology

• Embeddings — 14× in this paper · explained in 2 episodes
• Foundation Model — 10× in this paper · explained in 3 episodes
• Self-Supervised Learning — 8× in this paper · explained in 8 episodes
• Foundation Models — 7× in this paper · explained in 7 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Clustering — 4× in this paper · explained in 2 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Feature Extraction — 3× in this paper · explained in 2 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Redundancy — 3× in this paper · explained in 2 episodes
• Spectral Signature — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Feature Engineering — 2× in this paper · explained in 3 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Regularization — 2× in this paper · explained in 3 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Self-Supervised Learning (SSL) — 2× in this paper · explained in 4 episodes
• Systematic Bias — 2× in this paper · explained in 3 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Activation Function — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Aperture — 1× in this paper · explained in 1 episode
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• On the Opportunities and Risks of Foundation Models
• Foundation Models for Generalist Geospatial Artificial Intelligence
• TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis
• Interpolation of GEDI Biomass Estimates with Calibrated Uncertainty Quantification
• Guarding Barlow Twins Against Overfitting with Mixed Samples

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