AI-Powered Soil Quality Prediction
A team project combining satellite imagery, field sampling, and interpretable machine learning to estimate soil degradation risk earlier.
This group project studies whether satellite imagery, weather histories, and field observations can be combined into a transparent early-warning model for soil degradation risk.
The team is prioritizing interpretable modeling and field validation instead of black-box prediction claims.
The current research question is whether a smaller but carefully assembled dataset can support useful site-specific calibration.