AI & ML Practical Magic

We are now mapping the invisible networks of underground fungi across entire continents using satellites.

April 14, 2026

Original Paper

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

Robin Young, Michael E. Van Nuland, E. Toby Kiers, Tomáš Větrovský, Petr Kohout, Petr Baldrian, Srinivasan Keshav

arXiv · 2604.09818

The Takeaway

This uses satellite imagery and AI to 'see' 10,000 times more detail about underground soil health than previous methods allowed. It turns space technology into a microscope for the hidden organisms that keep our forests and crops alive.

From the abstract

Mycorrhizal fungi are vital to terrestrial ecosystem functioning. Yet monitoring their biodiversity at landscape scales is often unfeasible due to time and cost constraints. Current predictions suggest that 90\% of mycorrhizal diversity hotspots remain unprotected, opening questions of how to broadly and effectively map underground fungal communities. Here, we show that self-supervised learning (SSL) applied to satellite imagery can predict below-ground ectomycorrhizal fungal richness across div