About Spectral Vegetation Indices
Related page: Why NIR Calculating Spectral Indices
Information on this page serves as a very brief, beginning introduction to spectral vegetation indices (SVIs). An SVI is a value based on an equation that includes different spectral bands and is meant to better reveal vegetation condition. SVIs can be generally grouped into normalized and ratio or difference indices. Normalized indices that include visible bands are more effective earlier on (but after the canopy is full enough) then become ineffective as the canopy becomes too dense (because visible bands become too insensitive to variability), at that point ratio indices (e.g. NIR/Red) or difference indices (e.g. NIR - Red) are more effective. IT IS IMPORTANT TO UNDERSTAND THAT THERE IS A VAST AMOUNT OF SVIs, THE FOLLOWING LIST OF 71 VSIs IS ONLY A MODEST PORTION OF THE TOTAL VSIs THAT EXIST:
List of 71 Spectral Vegetation Indices for Broad or Narrow Band Sensors
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NDVI - When to Use and Not Use It
The most known (and one of the earliest) SVIs is Normalized Difference Vegetation Index (NDVI; see equation below) (Rouse et al., 1973). NDVI is useful only after soil has been covered enough by vegetation and before the canopy is too dense - after that, NDVI is overall too insensitive to change (due to lack of variability of the red band) and a non-normalized index (such as Difference Vegetation Index or Simple Ratio) should be used (NDVI can still distinguish significantly lower condition areas in a dense canopy, but cannot effectively distinguish moderate to minor differences well enough). The graphic below shows a comparison late in year when NDVI should not be used; the comparison shows that solely using NIR reflectance is superior not only because it has about 5 times more variability, but it also produces a much more coherent and realistic crop condition (as well as yield prediction) map. Click here to view a publication that describes in more details when NDVI should and should not be used (PDF; opens in new tab).
Comparison Showing that NIR Solely is Superior to NDVI Later in Season
NIR surface reflectance (SR) solely can be effectively used later in the season for types of crops with high SR (>55 percent), such as soybeans, and is much more effective than NDVI. Simple Ratio (NIR/Red) or Difference Vegetation Index (NIR-Red) maps would both look similar to the NIR solely map, and also be more effective than NDVI. It is important to note that corn NIR SR is too low (due to the structure of the plant) and that it is difficult to map corn well later in season with any index.
If applied at the proper time, NDVI is able to take advantage of the fact that healthier green vegetation has higher near infrared surface reflectance and lower red surface reflectance (NDVI has a value between -1.0 and 1.0). Different indices have been designed for different situations and purposes, including assessing dense canopies.
NDVI is written as follows: (all values are in surface reflectance): (NIR - Red) / (NIR + Red)
(When vegetation becomes too dense, red reflectance is virtually the same throughout even if condition varies and, as a result, the NDVI value is virtually 1.0 throughout because the equation essentially equals NIR/NIR; a different index should be used at that point).
(For Sentinel-2, use Band 8a NIR [as opposed to band 8], which is more similar to Landsat 8 band 5 NIR).
MODIFIED NDVI
Earlier in the season when it is appropriate to use a normalized index (after the canopy is full enough, yet not too dense), NIR surface reflectance (SR) is much higher than red SR, which reduces the impact of red SR variability (which is very important at that time of the season). A VSI that corrects for this is Wide Dynamic Randge Vegetation Index (WDRVI) (Gitelson, 2004). WDRVI more equally weights red and NIR surface reflectance. For healthy green vegetation at this time of the season, NIR surface reflectance is roughly 10 times greater than red surface reflectance (multiplying NIR by a 0.1 factor helps produce more equal NIR and red values; a 0.2 factor can also be used).
WDRVI (using a 0.1 factor) can be written as follows (all bands are in surface reflectance): ([NIR * 0.1] - Red) / ([NIR * 0.1] + Red)
For Sentinel-2, use Band 8a NIR.
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RED EDGE (available with Sentinel-2 imagery)
The red edge is the spectral region where vegetation reflectance abruptly increases from red to NIR. Clevers and Gitelson (2013) found there would be a high correlation between total crop and grass chlorophyll and nitrogen content based on the Sentinel-2 red edge Band 6:Band 5 ratio (research was completed prior to Sentinel-2 acquiring imagery by deriving information based on another satellite platform).
Use an equation from the publication accessed through the previous link or get started by simply dividing (in surface reflectance) Sentinel-2 Band 6 by Band 5 with the Raster Calculator; also try Band 7 divided by Band 5. The value of red edge applied to vegetation is quite well-documented.
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SOIL ADJUSTED VEGETATION INDICES
Numerous vegetation indices have been developed to counter the effects of soil reflectance background that averages into pixel values. These indices have been shown to reduce the effects of soil and improve crop condition assessment, though no index eliminates the effect. Wu et al., (2007; pdf) showed that MSAVI (a soil adjusted vegetation index) is better at detecting leaf area index for corn and potatoes than NDVI and other indices.
The List of 71 SVIs above includes soil-adjusted vegetation indices.
Reference
Gitelson, A.A. 2004. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation. Journal of Plant Physiology 161; pp. 165–173.
Rouse, J.W., R.H. Haas, J.A. Schell, and D.W. Deering. 1973. Monitoring vegetation systems in the Great Plains with ERTS. Third ERTS Symposium, NASA SP-351 I: 309-317.
Wu, J., Wang, D, and M.E. Bauer. 2007. Assessing broadband vegetation indices and QuickBird data in estimating leaf area index of corn and potato canopies. Field Crops Research 102 (2007) 33–42.