2026

NDVI (Normalized Difference Vegetation Index) is a numerical indicator that measures vegetation health by comparing how much near-infrared (NIR) light plants reflect versus how much visible red light they absorb. The formula is simple: NDVI = (NIR - Red) / (NIR + Red). Values range from -1 to 1, where healthy vegetation typically scores 0.3-0.9 and bare soil or water scores below 0.2.

Why NDVI Works

Healthy plants absorb red light for photosynthesis and strongly reflect near-infrared light. Stressed or sparse vegetation absorbs less red and reflects less NIR, producing a lower NDVI value. This makes NDVI a reliable proxy for canopy density, chlorophyll content, and overall crop vigor — measurable from hundreds of kilometers away via satellite.

Data Sources

NDVI imagery reaches agricultural platforms through several channels:

• Satellite — Sentinel-2 (ESA, free, 10m resolution, 5-day revisit) and Landsat (NASA/USGS, free, 30m resolution) are the most common sources. Commercial providers offer higher resolution.
• Drone — Multispectral cameras on UAVs capture field-level NDVI at centimeter resolution. Higher quality but labor-intensive.
• Aerial — Manned aircraft with multispectral sensors, used for regional surveys.

How Developers Use NDVI

Through FieldMCP, NDVI data is accessible as georeferenced raster or zonal summary data. Common applications include:

• In-season scouting prioritization — Identify low-NDVI zones that need physical inspection. See crop scouting.
• Variable rate nitrogen — NDVI correlates with nitrogen uptake, enabling mid-season VRT top-dress prescriptions.
• Yield prediction — Mid-season NDVI is a strong predictor of final yield, especially during grain fill.
• Anomaly detection — Compare current NDVI against historical baselines to flag emerging problems.

Accessing NDVI Data

FieldMCP's imagery tools provide NDVI data through the MCP interface. See the tools reference for available imagery operations.