Agricultural and Life Sciences (IFAS)
Grunwald Lab
Led by Sabine Grunwald · Soil, Water, and Ecosystem Sciences
What we study
The Grunwald Lab studies soil, water, and ecosystem changes using AI, remote sensing, and geospatial modeling. They develop predictive models to understand carbon dynamics and land use impacts.
What working here is like
- Computational
- No organisms (data only)
- Coding required
- Papers
- 5
Recent papers, explained
- Integrating deep learning with digital soil core sensing for subsurface soil image segmentation
2026 · Frontiers in Soil Science
Uses deep learning to analyze soil images for porosity and color.
- Deep learning-based downscaling of SMAP data for surface and root-zone soil moisture mapping
2026 · Journal of Hydrology
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- AI for science: Progress, challenges, and perspectives
2026 · The Innovation
- Spatiotemporal controls on soil organic carbon stocks in subtropical grazing lands: An uncertainty-aware digital soil mapping approach
2026 · Geoderma
Maps soil carbon stocks in Florida grazing lands using a new digital tool.
- Transformer‐Based Digital Soil Mapping Reveals Land‐Use Legacy Effects on (Sub)Tropical Soil Carbon
2026 · Earth s Future
Used satellite data to predict soil carbon in tropical areas, showing land-use effects.
Plain-language summaries are AI-written and reviewed by us; check the paper for details.
How to reach out
Sabine Grunwald hasn't set up this page yet. You can also look them up in the UF directory (search “Sabine Grunwald”).