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cs.LG2026
From Machine Learning to Large-Scale EO Products: Best Practices for Making Maps
Ghjulia Sialelli, Robin Young, Yuchang Jiang +9
Recent years have seen a rapid expansion in the production of large-scale geospatial maps derived from Earth observation (EO) data, driven largely by advances in machine learning (…
cs.LG2026
Neural Processes Maintain Calibrated Biomass Estimates Across Spatiotemporal Gaps and Disturbance
Robin Young, Srinivasan Keshav
Monitoring deforestation-driven carbon emissions requires both spatially explicit and temporally continuous estimates of aboveground biomass density (AGBD) with calibrated uncertai…
cs.LG2026
Below-ground Fungal Biodiversity Can be Monitored Using Self-Supervised Learning Satellite Features
Robin Young, Michael E. Van Nuland, E. Toby Kiers +4
Mycorrhizal fungi are vital to terrestrial ecosystem functioning. Yet monitoring their biodiversity at landscape scales is often unfeasible due to time and cost constraints. Curren…