Understanding your crops’ health status isn’t the easiest thing to do. Sure, you can use the “eye test”, and a number of foliar contact and direct measurement techniques. But, what if there was an easy, fast and efficient way to see the health of plants and their status and progress over time? That’s where Normalized Difference Vegetation Index (NDVI) data comes in.


In simple terms, NDVI is a measurement of plant health based on how a plant reflects light (usually sunlight) at specific frequencies. To be more specific, NDVI is a measurement of the reflectivity of plants expressed as the ratio of near-infrared reflectivity (NIR) minus red reflectivity (VIS) over NIR plus VIS.

The equation for NDVI was developed several decades ago to make use of satellite imagery in agriculture. The way the equation is built makes it insensitive to overall brightness or darkness of light — it essentially tracks the ratio of NIR to red reflectivity, which doesn’t change with overall brightness.

NDVI works because when sunlight reaches a plant, certain wavelengths are absorbed while others are reflected. Chlorophyll strongly absorbs visible light while the cell structure of leaves strongly reflects near-infrared light. A spongy layer along the bottom of a plant causes these reflections. When a plant becomes dehydrated, sick, affected by disease, etc. this spongy layer deteriorates and the plant absorbs more of that near-infrared light rather than reflecting it. Conversely, when near-infrared light hits a leaf on a healthy plant, it is reflected back. So, looking at how NIR varies compared to red light provides an accurate indication of chlorophyll, which correlates to plant health.

The equation explained above will always result in a NDVI plant health value between -1 and +1. A number between -1 and 0 suggests an inanimate or dead object, like roads, buildings, or dead plants. A NDVI plant health rating between 0 and 0.33 indicates unhealthy or stressed plant material, 0.33 to 0.66 is moderately healthy, and 0.66 to 1 is very healthy. These numbers are just rules of thumb, and vary based on type of plant and other conditions. But that’s enough science for now.



As mentioned, NDVI plant health values are between -1.0 and +1.0 But how does this translate to the colorful NDVI maps you’ve probably seen? Basically, certain ranges of NDVI values are mapped to a set of colors. One of the most common color maps is the “red-green” NDVI color map. In this map, NDVI plant health values from -1 to 0 range appear red, 0.0 to 0.33 are orange-ish red or yellow, 0.33 to 0.66 tint green, and above 0.66 appear green. There isn’t a “standard” color map. Some people don’t like these colors, some people want more colors and some want fewer.



Here we see a stitched plant health map showing various NDVI values. The large red areas along each side are inanimate material (roads, dirt, etc.). Focusing on the outlined portion of the field, we notice NDVI plant health values ranging from green (good) to red (bad). By navigating to the two areas of concern within the field, the grower was able to identify weeds and washout. As a result, he applied the appropriate herbicide and adjusted irrigation measures to avoid yield loss. He was also able to identify thriving areas of his field (green) and reallocate inputs to boost his ROI.


Overall, NDVI is a way to measure plant health. Multispectral sensors detect indicators invisible to the naked eye, utilising light reflections and absorptions to calculate an NDVI score. Healthy plants absorb most of the visible light while reflecting a large amount of the near-infrared light. Unhealthy plants do the opposite. NDVI is an extremely helpful tool to assess plant health, and understanding it is important. Stratus Imaging can work with you to unlock even more value, by incorporating high-precision NDVI data right into most digital agriculture platforms.


  • Canopy coverage & density detection
  • Produces accurate growth trending with frequent use
  • Frost Damage Detection
  • Large Scale Pest Outbreaks
  • Optimizing crop rotation times
  • Ecological Benefits
  • Vegetation dynamics or plant seasonal changes over time
  • Biomass production
  • Grazing management & impacts (e.g., stocking rates)
  • Changes in range land condition
  • Vegetation or land cover classification
  • Moisture content in the soil
  • Carbon sequestration or CO2 flux

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