NDVI Dashboard for Crop Health Monitoring
The primary objective was turning raw NDVI time-series data into something a non-technical stakeholder—such as a farm manager or an agronomy student—could actually read and act on, moving beyond complex research workflows into practical field management.
The pipeline pulled Sentinel-2 imagery across the study area, calculated NDVI metrics over multiple acquisition dates, reconstructed a clean seasonal trajectory, flagged negative deviations as early crop stress indicators, and surfaced results in a simple chart interface.
Key Project Features
Seasonal NDVI Curve View
Anomaly Flagging
Per-Plot Comparison
Reconstructs smooth vegetation index trajectories across time, tracking seasonal growth stages across designated agricultural field plots.
Automatically highlights unexpected dips below baseline expected trajectories, signaling early moisture deficits or pest stress.
Enables side-by-side performance analytics between neighboring plots to evaluate crop varieties, soil treatments, and irrigation efficiency.