CoverGuard is a 4-satellite SmallSat constellation that diagnoses cover-crop failure from orbit, delivering field-specific prescriptions to farmers. On the ground, NASA OPERA and Harmonized Landsat Sentinel-2 datasets are fused into health signals per crop-region, prioritizing highest-risk crop failure parcels for uplink. Onboard, a multispectral imager adaptively images only over flagged parcels (saving power), and a LightGBM AI classifier identifies the specific cause of cover crop failure: moisture stress, nutrient deficit, poor establishment, excess wetness, or pest pressure. Inference runs at under 1 ms per pixel entirely onboard, delivering results to farmers within 95 minutes of imaging, which is 50x faster than conventional satellite workflows with 96% accuracy. At $0.75 per acre per season, CoverGuard targets a $30 million U.S. precision-agriculture market. Unlike existing tools that flag low vegetation without explanation, CoverGuard introduces the first full-stack onboard crop-failure classification CubeSat architecture, delivering diagnosis directly from orbit.
Priyanka Supraja Balaji, Marcus King, Parnika Singh