What is NDVI? (Normalized Difference Vegetation Index)
What is NDVI?
NDVI is the most widely used satellite index for measuring vegetation health. It boils the answer to “is my field okay?” down to a single number between −1 and 1 — derived from how your crops reflect light. If you have ever seen a satellite map where healthy fields glow green and bare soil looks brown, you have seen NDVI. It is the number behind almost every “crop health” map in agriculture, forestry, and climate science.
Leaves do two predictable things with light: they absorb red light (chlorophyll uses it to photosynthesize) and they strongly reflect near-infrared light (their internal cell structure scatters it). A healthy, leafy canopy therefore shows a big gap between red and near-infrared reflectance. A stressed or sparse canopy does not.
How it’s calculated
NDVI turns that reflectance gap into a single number using a normalized ratio:
NDVI = (NIR − Red) / (NIR + Red)On Sentinel-2 satellites (which photograph every field on Earth every five days), these are Band 8 (NIR) and Band 4 (Red). Because the formula is a ratio, it cancels out the raw brightness of the image — so NDVI means the same thing whether the scene was captured on a bright or hazy day. When a crop is healthy, red stays low and NIR stays high, so NDVI climbs toward 1. When vegetation dries, thins, or dies, the two reflectances converge and NDVI falls toward 0.
Typical value ranges
There is no single “good” NDVI — it depends on the crop and the season. Use the table as a starting point, then compare against what’s normal for your crop and time of year.
| NDVI range | Meaning | Typical for |
|---|---|---|
| 0.6 – 1.0 | Dense, healthy vegetation | Peak-season crops, mature forest, closed canopy |
| 0.4 – 0.6 | Moderate vegetation | Developing crops, vineyards at full canopy |
| 0.2 – 0.4 | Sparse or stressed | Early growth, drought stress, poor establishment |
| 0.0 – 0.2 | Bare soil or severe stress | Plowed field, senesced vegetation |
| Below 0 | Water, snow, or cloud | Lakes, snow cover, cloud shadow |
The most useful reading is almost never a single number — it is how your NDVI compares to previous months and to the same period last year. A field dropping from 0.7 to 0.5 in two weeks tells you something is wrong, even though 0.5 alone looks acceptable.
When to use it
NDVI is the universal default for crop monitoring. Use it for general canopy health assessment, tracking seasonal growth curves, and comparing field performance year-over-year. The canonical NDVI pattern for a seasonal crop is a bell curve: low while the field is bare or newly sown, climbing through vegetative growth, peaking at canopy closure, then declining as the crop ripens and senesces. A healthy season looks smooth; stress events show up as dips that break the curve’s expected shape.
It works best for moderate-to-dense canopies of annual crops, pastures, and deciduous forest. For very dense canopies (where NDVI saturates above ~0.8), switch to EVI. For sparse or young crops (where soil shows through), use SAVI or MSAVI2. For water stress specifically, NDMI gives days-to-weeks of earlier warning.
Comparison with other indices
NDVI is the universal baseline — simpler and more widely calibrated than any other index. EVI resists saturation over dense canopies and corrects for atmospheric haze, at the cost of added complexity and sensitivity to image quality. SAVI and MSAVI2 correct for soil background that drags NDVI down in sparse vegetation. NDMI catches drought stress before NDVI, while NDRE detects nitrogen status that NDVI cannot. For most crops through most of the season, NDVI is the right starting point.
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Frequently asked questions
What is a good NDVI value?
It depends on the crop and season. For most annual crops at peak growth, 0.6 to 0.8 indicates a healthy, dense canopy. Vineyards and orchards run lower (0.4–0.6 is normal) because rows and management keep the canopy open. Always compare against your own field’s history rather than an absolute threshold.
How often is NDVI updated?
The two Sentinel-2 satellites revisit every location on Earth every five days, weather permitting. Clouds can block the view for longer, which is why reports use cloud-free composites and trends rather than a single image.
Can NDVI detect crop disease?
NDVI detects the stress that disease causes — a drop in green, leafy canopy — but it cannot name the pathogen. A falling NDVI tells you something is wrong and where to look; it does not replace walking the field. Disease, drought, nutrient deficiency, and pest damage all depress NDVI similarly.
Why is my field's NDVI negative?
Negative NDVI usually means the satellite saw water, snow, or cloud rather than vegetation. If your field is not a lake, a persistent negative reading almost always means cloud cover or shadow is contaminating the image. A good report filters this out and tells you when the data is unreliable instead of showing a meaningless number.