By Kevin Tu, PhD of LandFlux.org
I'm coming across more people that are using your modified cameras for NDVI applications and I'm also finding that they are using your formula for ENDVI without any information about how the two compare. I think its important to know what they're looking at when they do that. I did a comparison the ENDVI with standard NDVI, as well as some other vegetation indices that are known to be differentially sensitive to LAI and Chl. All the data are from the MODIS satellites and come from different vegetation types with a wide range of canopy structures and leaf chlorophyll contents (semi-arid woodland, corn crop, soybean crop, boreal evergreen needleleaf forest, subalpine evergreen needleleaf forest, tropical broadleaf forest, and temperate broadleaf forest).
Below is a comparison of ENDVI to standard NDVI. ENDVI tracks variation in NDVI but with significant scatter. One should be careful in assuming they are the same. ENVDI provides similar information as NDVI at high values of NDVI, but somewhat different information at low values of NDVI.
Below are graphs showing that both NDVI and ENDVI are similarly driven by variation in visible reflectance, represented by red reflectance below. This is unlike soil adjusted vegetation indices (for example SAVI and EVI, EVI2) which are driven by variation in NIR reflectance.
Rather than NDVI, ENDVI is more closely related to the Green NDVI = (NIR-G)/(NIR+G), as shown in the figure below.
Both ENDVI and Green NDVI are driven by visible reflectance but lack information in red reflectance. Like other NDVI-class vegetation indices that are driven by visible reflectance, Green NDVI and ENDVI are better indicators of total leaf area index (LAI) rather than green LAI (gLAI) like SAVI-class vegetation indices that are driven by NIR reflectance. NDVI, ENDVI is poorly related to both SAVI and EVI, as shown below.
Thought this might be useful info for people to know in case you wanted to include it or some version of it on your website.