What is NDVI?

A brief summary of the popular crop analysis tool

Overview:

A normal, healthy, plant will absorb visible blue and red light and reflect green visible light, which is why they appear green to our eyes.  In addition to green visible light, plants also reflect Near-Infrared (NIR) as this type of light isn’t actively used for the photosynthesis process.  When a plant is weak or diseased, reflection of this NIR light is greatly decreased.  Since red light is still being absorbed the same as a healthy plant, a mathematical algorithm can calculate the difference in what is being reflected across a field of crops. Once calibrated and processed, it will become clear which plants are thriving and which are struggling.

By using a special camera that detects Near-Infrared wavelengths (750-1400 nanometers) as well as regular red wavelengths, comparisons are made by a computer of the two different channels, resulting in a “normalized difference” through post-processing.  NDVI has become a very successful method of calculating data, and remains one of the most popular reports today.

NDVI - Definition

Normalized Difference Vegetation Index, or NDVI, is a color-coded graphical representation of plants in a field or elsewhere.

NDVI information can be used for:

  • Determine level of Chlorophyll
  • Plant health and stress level
  • Optimal fertilizer use
  • Nitrogen Management
  • Identify insects and pest in crop
  • Analyze plant disease
  • Plant or weed identification
  • Farm plan development
  • Cultivation planning
  • Harvest planning according to vigor

Technical details:

ENDVI (Enhanced Normalized Difference Vegetation) has been introduced as a newer technique and produces more robust reports.  ENDVI differs from the earlier NDVI calculations as it uses blue/green visible light instead of the red-only method.  This allows for better isolation of plant health indicators and produces a False Color Mapping to indicate the value of Vegetation Index at that pixel.

Agriculture producers typically use these remotely-captured measurements to assess the presence and health of a crop.  Depending on the specific type of report produced, healthy crops will appear green, and weak or poor areas will appear yellow to red.

 

Example images: