Understanding the Normalized Difference Vegetation Index

By Laura Williams, Data Scientist

Understanding the Normalized Difference Vegetation Index

Using vegetation indices to assess plant health remotely

In our article introducing how satellite imagery can be used to track plant health, we discussed the value of vegetation indices derived from satellite imagery. In this post, we are going to expand on one of the most commonly used1 vegetation indices to remotely assess plant health, the normalized difference vegetation index (NDVI).

What is multispectral imagery?

Vegetation indices (VIs) use the reflectance (measure of light energy reflected) of land cover at different wavelengths captured via satellite imagery to differentiate land cover type and characterize plant health and growth. Multispectral imagery, a collection of images of the same scene taken at different wavelengths of light, is used to measure the reflectance of land cover via the color of the images captured at different wavelengths1. Multispectral imagery can be captured via satellite, drones, or other unmanned aerial vehicles (UAVs).

The different wavelengths of light are typically referred to by their spectral band, a continuous wavelength range defined on the electromagnetic spectrum, and the number of spectral bands available depends on the instrument used to capture the imagery. A few of the spectral bands are in the visible spectrum, the blue, green, and red bands, and the rest are outside the visible spectrum, including the red-edge (wavelengths between visible red and infrared) and near-infrared (NIR) bands commonly used in vegetation indices. VIs combine reflectance information from multiple bands to gleam insight into a variety of plant-based characteristics, such as how the NDVI combines the red and NIR bands to assess plant health.

How does the NDVI provide a quantitative assessment of plant health?

The characteristic color green we associate with plant life is a result of the cellular structure of plant leaves and the photosynthetic pigment chlorophyll. Since chlorophyll strongly absorbs visible light (red is most strongly absorbed) and the cellular structure of plants strongly reflect NIR light3, low reflectance (high absorbance) in the red band and high reflectance in NIR band indicate healthy, strong vegetation2. Taking advantage of these properties, the NDVI provides a quantitative representation of plant health using the spectral reflectance in the red and NIR bands by taking the ratio of their difference to their sum as follows1:

The photo below provides an example of this formula in action by using sample reflectance values representative of actual reflectance and how its use identifies healthy vegetation.

Understanding NDVI, Data Science Solutions, Keiter Technologies

Source: NASA2

Due to the nature of the calculation, NDVI values fall in the range from -1 to 1. So – what do these values tell us? Typically, negative values indicate bodies of water, values close to zero indicate rocks, sand, concrete, or bare soil, moderate values (0.2-0.3) indicate shrubbery and meadows, and large values (0.6-0.8) indicate dense green areas, such as healthy crops or dense forest2.

How reliable is NDVI?

Though very useful as an indicator of crop health, the NDVI becomes a less reliable assessor of plant health towards the end of the growing season as plants are reaching maturation and may have several leafy layers. During this time, the reflectance in the red band reaches a maximum while the reflectance in the NIR band continues to increase4, causing NDVI values to become more representative of the overall area of leafy growth rather than overall health. Typically, other vegetation indices are used during the end of the growing season to assess plant health.

The NDVI has been used in many studies in a variety of applications within the agricultural industry for remotely analyzing plant health and biomass. It has been used alone and along with site-collected data in a variety of applications to estimate plant biomass, chlorophyll concentration, plant stress, and enables monitoring changes in these factors over time1.

Interested in learning how NDVI can help your agriculture business? Contact the Keiter Technologies team. We are here to provide innovative data solutions to help your business improve processes and drive growth.



  1. A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing
  2. Measuring Vegetation (NDVI & EVI) (nasa.gov)
  3. Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation
  4. Evaluation of the saturation property of vegetation indices derived from sentinel-2 in mixed crop-forest ecosystem


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About the Author

Laura Williams

Laura Williams, Data Scientist

Laura leverages her education and experience in statistics, mathematics, and research to tackle a variety of business problems with data-driven solutions. Her client service approach includes forming a thorough understanding of a client’s project goals and data to provide well-informed insights and solutions.

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The information contained within this article is provided for informational purposes only and is current as of the date published. Online readers are advised not to act upon this information without seeking the service of a professional accountant, as this article is not a substitute for obtaining accounting, tax, or financial advice from a professional accountant.


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