5.2 Plant Health

Healthy plants reflect light differently than diseased plants. Plants that are in good health tend to reflect more green light than red light, which is why they appear green. Plants also emit near-infrared light, which is invisible to the naked eye but detectable by near-infrared sensors.

Plant health algorithms such as NDVI and VARI assess the proportions of light collected across different bands (red, green, blue, and occasionally near-infrared) to compute numerical values for each pixel or area in a given drone map. Maps with plant health algorithms are then colored based on those numerical values, making it easy to distinguish between healthy and unhealthy areas.

5.2.1 NDVI image (Normalized Difference Vegetation Index)

NDVI or greenness index is an indicator that shows the greenness, density, and health of vegetation in each pixel of a satellite image.

NDVI is a widely and commonly used remote sensing technology for identifying vegetation and assessing plant health. NDVI has been the industry standard for understanding plant health from many years. To quantify healthy plant life under a variety of situations, NDVI compares near infrared light.

Value	Indication
< 0	Inanimate / dead material such as roads, buildings, soils, or dead plants
0 to 0.33	Unhealthy plant material
0.33 to 0.66	Healthy Plant Material
> 0.66	Very Healthy Plant Material

NDVI index Value

You can see the NDVI image by clicking on the NDVI tab at the center bottom of the screen. A plant health popup will be seen.

Image after applying NDVI

The user can select any one of the algorithm provided. DroneNaksha support the following algorithms:

5.2.2 vNDVI

A genetic algorithm that is used to create a new visible index (visible NDVI; vNDVI) to calculate NDVI values from RGB cameras installed on UAVs that have not been calibrated.

5.2.3 Visible Atmospherically Resistant (VARI) Index

An index of vegetation originally developed for satellite images is called the Visual Atmospheric Resistance Index. It is minimally affected by atmospheric effects, allowing it to estimate vegetation in a wide range of environments.

$$VARI=((Green-Red))/((Green+Red-Blue) )$$

Image after applying VARI

• Excess Green (EXG)

5.2.4 Triangular Greenness Index (TGI)

It uses the area of a triangle in the spectral features of the chlorophyll region. Triangular Greenness Index (TGI) is an RGB indicator for chlorophyll sensitivity.

$$TGI=((Green-(0.39*Red)-(0.61*Blue)))/((Normalized to max value of RGB bands))$$

After Applying TGI Algorithm

5.2.5 Green Leaf Index (GLI)

If the value is positive, it is either green leaves or stems; if it is negative, soil or another nonliving object.

$$GLI=(2Green-Red-Blue)/(2Green+Red+Blue)$$

After Applying GLI Algorithm