The selection of sensors (link) depends on your objectives. I.e., what do you wish to know from the image? Is it a stress level? If so, what type of stress? Below are some common examples of vegetative indices used to monitor crop health.

Vegetation indices are crucial for assessing the health and growth of vegetation. The Visible Atmospherically Resistant Index (VARI) and the Normalized Difference Vegetation Index (NDVI) are two widely used vegetation indices. VARI is specifically designed to work with RGB data and measures the “greenness” of an image. It is useful when working with imagery that does not include near-infrared (NIR) data. (i.e., you can use a regular camera on a drone.) VARI also provides information about the reflectance of vegetation and soil. On the other hand, NDVI is a more traditional index that compares Near Infrared and Red light. It is a powerful tool for measuring the health of green vegetation under different conditions. The NDVI can also be used to estimate drought stress.

Another essential index is Normalized Difference Red Edge (NDRE), which is sensitive to chlorophyll content in leaves against the soil background effects. This index requires the red edge band to be available for computation. Furthermore, the Triangular Greenness Index (TGI) is a chlorophyll-sensitive RGB index that relies on reflectance values at visible wavelengths. It is a helpful proxy for chlorophyll content in areas with high leaf cover.

Vegetation Index	Purpose	Advantages	Limitations
NDVI (Normalized Difference Vegetation Index)	Compares Near Infrared and Red light. Powerful tool for measuring the health of green vegetation under different conditions.	Provides evidence for plant disease, environmental stressors, pest or nutrient problems potentially affecting the crop yield early in plant growth.	The crop health may affected by other factors than vegetation, like soil condition/moisture
NDRE (Normalized Difference Red Edge)	An index that is sensitive to chlorophyll content in leaves against the soil background effects. It analyzes the narrow band of visible light where red turns into NIR.	It is excellent for determining the health of crops in the mid to late growing season. It can also show the relative nitrogen content of crops separate from the nitrogen content of the soil.	It requires the red edge band to be available for computation.
EVI (Enhanced Vegetation Index)	A Red, Green, and Blue (RGB) visible light band vegetation index. Indicates the chlorophyll production of a plant by indicating the greenness of the leafy plant surface.	EVI is very similar to NDVI but can be more robust because it can correct for atmospheric conditions, canopy background noise, and has more sensitive results for dense vegetation areas.	Either extremes of a very bright areas or a very dark areas may result in anomalous pixel values in the EVI image.
LAI (Leaf Area Index)	A Red, Green, and Blue (RGB) visible light band vegetation index. Indicates the chlorophyll production of a plant by indicating the greenness of the leafy plant surface.	can use a regular visibility camera on a drone. It is important for monitoring crop health. It can be focused down to a singular plant or scale up to a whole region.	is more delayed in detecting phenotype information of vegetation because it requires detection from the visible light range.
VARI (Visible Atmospherically Resistant Index)	Designed to work with RGB data and measures the “greenness” of an image. Provides information about the reflectance of vegetation and soil	can use a regular visibility camera on a drone.	Requires detection from the visible light range.
TGI (Triangular Greenness Index)	A chlorophyll-sensitive RGB index that relies on reflectance values at visible wavelengths.	It is a helpful proxy for chlorophyll content in areas with high leaf cover.	Requires detection from the visible light range.
GRVI (Green Red Vegetation Index)	A Red, Green, and Blue (RGB) visible light band vegetation index. Indicates the chlorophyll production of a plant by indicating the greenness of the leafy plant surface.	can use a regular visibility camera on a drone.	Requires detection from the visible light range.
GLI (Green Leaf Index)	A Red, Green, and Blue (RGB) visible light band index. Indicates the chlorophyll production of a plant by indicating the greenness of the leafy plant surface.	can use a regular visibility camera on a drone.	Requires detection from the visible light range.
SAVI (Soil Adjusted Vegetation Index)	corrects for soil line disparities Analyzes the affect weather has had throughout the growing season. and	Allows one to make a plan or do an adjustment for irrigation needs.	SAVI uses a trial and error method to calculate soil brightness for the correction L factor in its calculation for the index.
MSAVI (Modified Soil Adjusted Vegetation Index)	Like SAVI, it is used to mitigate the effect of soil on light analysis. Specifically, it minimizes the effect of bare soil on the SAVI It is ideal for monitoring plants directly following planting.	It is more sensitive to areas where there is more soil and very little vegetation very small amounts of chlorophyll. it produces better measurements for these conditions than NDVI Index.
Soil Line	it defines the location of soil vs. the location of vegetation	It is a way to quantify the distribution of bare soil and vegetation in	Sometimes it can be hard to capture a true line because the captured data is actually reflecting a curve.
TCARI/OSAVI (Chlorophyll Absorption Reflectance Index/Soil Adjusted Vegetation Index)	It can generate a predictive equation to estimate chlorophyll content of a leaf from the combined optical index created from canopy reflectance.	Very sensitive to chlorophyll content variations and very resistant to variations of LAI and solar zentih angle.	Data can be very complex and challenging to interpret.
Crop Water Stress Index (CWSI)	It uses surface temperature of the canopy, ambient air temperature, and soil/water characteristics to express the degree of water deprivation the plants are experiencing. It is an excellent way to manage irrigation needs.	Taking daily CWSI readings leading up to a day of rainfall or low sun exposure can be used to indicate water stress levels as it shows increase or decrease in the calculations depending on the weather event.	CWSI index may not have the same predictive accuracy weather conditions and climates across the board for all growing regions.

Scholarly Articles

Using Vegetation Indices in Viticulture

Differences between SAVI (Soil Adjusted Vegetation Index) and MSAVI (Modified Soil Adjusted Vegetation Index)

TCARI/OSAVI (Chlorophyll Absorption Reflectance Index/Soil Adjusted Vegetation Index)