Sabine Grunwald, PhD 

​Grunwald's research studies focus on the change of soil-ecosystems - agricultural, forest, terrestrial and aquatic systems - across a variety of temporal and spatial scales (field to global scale). 

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Grunwald's specific research interests and expertise: 

• Artificial intelligence (AI): machine learning and deep learning algorithms in soil, water and ecosystem sciences. AI applied to agriculture management.

• GeoAI and Earth Observation (EO) geospatial modeling.

• Pedometrics, pedo-econometrics and digital soil mapping.

• Soil and terrestrial carbon modeling.

• Best management practices; conversation management; sensor-informed agricultural management.

• Regenerative agriculture.

• Soil health, soil security, and soil processes and dynamics.

• Soil proximal sensing (visible-near-infrared, mid-infrared spectroscopy; FTIR)

• Remote sensing and geospatial analysis.

• Understand the impact of environmental stressors (e.g., land use and global climate change) on soil and terrestrial carbon dynamics.

• Develop multi-scale predictive models of soil and environmental properties across various spatial and temporal scales.

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