Calculation of the Normalized Difference Vegetation Index (NDVI), which is available on-the-fly, comes first. In addition, NDVI is often used around the world to monitor drought, forecast agricultural production, assist in forecasting fire zones and desert offensive maps. NDVI is preferable for global vegetation monitoring since it helps to compensate for changes in lighting conditions, surface slope, exposure, and other external factors.
NDVI is calculated in accordance with the formula:
NIR - reflection in the near-infrared spectrum
RED - reflection in the red range of the spectrum
According to this formula, the density of vegetation (NDVI) at a certain point of the image is equal to the difference in the intensities of reflected light in the red and infrared range divided by the sum of these intensities.
This index defines values from -1.0 to 1.0, basically representing greens, where negative values are mainly formed from clouds, water and snow, and values close to zero are primarily formed from rocks and bare soil. Very small values (0.1 or less) of the NDVI function correspond to empty areas of rocks, sand or snow. Moderate values (from 0.2 to 0.3) represent shrubs and meadows, while large values (from 0.6 to 0.8) indicate temperate and tropical forests.
Put simply, NDVI is a measure of the state of plant health based on how the plant reflects light at certain frequencies (some waves are absorbed and others are reflected).
Chlorophyll (a health indicator) strongly absorbs visible light, and the cellular structure of the leaves strongly reflect near-infrared light. When the plant becomes dehydrated, sick, afflicted with disease, etc., the spongy layer deteriorates, and the plant absorbs more of the near-infrared light, rather than reflecting it. Thus, observing how NIR changes compared to red light provides an accurate indication of the presence of chlorophyll, which correlates with plant health.
LandViewer allows you to monitor the health of plants and calculate the NDVI index on-the-fly. You simply select one of the satellites, load the necessary area of interest, choose the time for monitoring the status of your field, and get instant maps of plant health.