How drones see crop health with NDVI

Healthy leaves absorb most red light for photosynthesis but strongly reflect near-infrared light, which our eyes cannot see, because of the way their internal cell structure scatters it. Stressed or sparse plants reflect more red and less near-infrared. A drone or satellite camera measures both bands, and the Normalized Difference Vegetation Index turns that contrast into a single number from about 0 for bare soil to near 0.9 for dense, vigorous crops.

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Plant vigor

0 is dead or severely stressed, 100 is fully vigorous.

Canopy cover

Step through it

Sunlight inSunlight contains visible colors and near-infrared light. All of it lands on the canopy.
Leaves eat redChlorophyll absorbs red light to power photosynthesis, so a healthy canopy reflects very little red.
Leaves bounce near-infraredThe spongy cells inside a leaf scatter near-infrared strongly. A thick, healthy canopy glows bright in this band.
Stress shows firstAs plants weaken, red reflection rises and near-infrared falls, often before the change is visible to the eye.
The camera does the mathThe drone records both bands for every pixel, and software computes NDVI to map strong and weak areas of the field.

The index

NDVI = (NIR minus Red) / (NIR plus Red), where NIR and Red are the fractions of each band reflected. Dividing by the sum normalizes away overall brightness, so the index is fairly stable as clouds or sun angle change. Values range from minus 1 to plus 1; water is negative, bare soil sits near 0.1 to 0.2, and dense green crops reach about 0.8 to 0.9.

The reflectance numbers here come from a simplified teaching model that blends typical values for vigorous leaves, stressed leaves and bare soil by canopy cover. Real reflectance depends on crop, growth stage, soil color and sensor calibration.

Try it: leave vigor at 80 percent and slide canopy cover from 100 down to 20. NDVI falls from about 0.76 to about 0.26 even though the individual plants are just as healthy, which is why early season NDVI mostly tracks how much ground is covered.

Using the map

NDVI maps point scouts to the weak spots, help vary fertilizer or irrigation across a field, and track crops from week to week. They show where something is wrong, not what: low NDVI can mean drought, disease, pests, nutrient shortage or poor emergence, so someone still checks on the ground.

Where Avid uses this

Aerial crop sensing like this is the kind of job Avid's HydroVzn autonomous drone agrobotics platform is built for.

Sources

Remote Sensing Imagery in Agriculture: Image Conversion to NDVI (MF2857)Kansas State University Research and Extension
Monitoring vegetation systems in the Great Plains with ERTSNASA Technical Reports Server
Measuring VegetationNASA Earth Observatory

How to cite this model

Avid Solutions International. (2026, November 11). How drones see crop health with NDVI [Interactive 3D model]. Avid Field Lab. https://avidsolutionsintl.com/explore/ndvi-crop-sensing

Last updated November 11, 2026

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