NDVI: It is useful to determine the density of green on a patch of land. This index combines information available in the red and near-infrared band into a single representative value and goes from -1 to 1. To understand this index we need to check the wavelengths of the visible and near-infrared sunlight (“colors”). Why? because when the light of the sun strikes vegetation, these wavelengths are absorbed or reflected. It is important to know that pigment of leaves, chlorophyll, absorbs visible light (red region of the spectrum) which goes from 0.4-0.7um for use in photosynthesis. The cell structure of the leaves has different behavior and reflects the near-infrared light. So, the more leaves a plant has, which we can say are healthier reflect more in the NIR but less in the red, and the other unhealthy vegetation reflects more red than NIR. I find this video helpful to understand how this works, and this text.
VARI for leaf coverage Areas with abundant leaf coverage indicate that the biosphere is actively using hydrosphere for plant growth which is good. Therefore the higher the value the better.
TGI for chlorophyll sensitivity Chlorophyll is a pigment that gives plants their green color, and it helps plants create their own food through photosynthesis. Therefore higher values mean healthier, than lower values.
VARI AND TGI indexes are useful for example when you do not have a multispectral camera. The multispectral camera has the NIR band, but an RGB camera not. However, you can still observe if the plant is healthier or not using the TGI and VARI indexes
So your understanding is correct with the VARI you check the leaf coverage “how green is the plant”, and higher values the higher the possibility plants are healthy, and TGI can be alternative when using RGB sensors Here more studies..
We would like you to be aware that there are many publications avaliable to read about indices, comparisons between them, and explaining that the results and the use of vegetation indices in general depend on many factors. For example, the results that you will get depend on the crop growth stages, crop density, crop type, etc.
Let’s take the NDVI as an example (but will work similarly to the other indices), sparse vegetation such as shrubs and grasslands or senescence crops may result in moderate NDVI values (approximately 0.2 to 0.5). Very high NDVI values (approximately 0.6 to 0.9) correspond to dense vegetation such as that found in temperate and tropical forests or crops at their peak growth stage.
Those indices in general help us to focus on the problematic areas, because you might see the low values, so we know that something is happening there, and for example some of our users instead of taking a soil sample of their whole field, they just take a soil sample of the areas where we know there is a problem. Also, most of our users do not choose one single index to analyze their field. In this case for example, now we know that the VARI will give us insights about the leaf coverage and the TGI about chlorophyll so that I would use both, but if I have a multispectral camera I get the NDVI directly and maybe look into other indices as well such as the NDRE.
Let me know if this helps.