GNDVI (Green NDVI)
Definition
The Green Normalized Difference Vegetation Index (GNDVI) is a modification of the standard NDVI that replaces the red band with the green band in its calculation. It leverages the fact that healthy vegetation strongly reflects near-infrared light while absorbing green light for photosynthesis, though less strongly than red light.
Application
GNDVI is particularly sensitive to chlorophyll concentration and is extensively used for monitoring crop nitrogen status, assessing plant stress before visible symptoms appear, and estimating photosynthetic activity. It's valuable in precision agriculture for guiding variable-rate nitrogen application and in ecological studies for assessing vegetation health and productivity.
FAQ
What is the formula for GNDVI?
GNDVI is calculated as: GNDVI = (NIR - Green) / (NIR + Green), where Green is the reflectance in the green visible band (typically around 550 nm) and NIR is the near-infrared reflectance. Like NDVI, values range from -1 to 1, with higher values indicating healthier vegetation.
What is the main advantage of GNDVI over standard NDVI?
The main advantage is its higher sensitivity to chlorophyll concentration and leaf area index in moderate to dense canopies. GNDVI is less susceptible to saturation under high biomass conditions compared to NDVI and can detect subtle changes in vegetation health that might not be apparent with NDVI.
Why is GNDVI more sensitive to chlorophyll than NDVI?
GNDVI is more sensitive because the green band (around 550 nm) corresponds to the chlorophyll reflectance peak (the "green bump" in vegetation spectra), while the red band corresponds to the chlorophyll absorption minimum. Changes in chlorophyll content affect green reflectance more directly, making GNDVI a better indicator of photosynthetic pigment concentration.
What are the limitations of GNDVI?
Limitations include:
1) Greater sensitivity to atmospheric effects than NDVI due to shorter wavelength of green light;
2) Potentially higher susceptibility to soil background effects in sparse vegetation;
3) Not as widely studied or validated as NDVI for some applications;
4) Requires sensors with a green band, which most modern multispectral sensors have, but some historical datasets may lack.
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