Normalized Difference Vegetation Index In Agriculture: Benefits And Features are elaborately discussed in this article.
Spectral analysis of high-resolution satellite imagery helps track plant development dynamics. This technology in agriculture is called crop monitoring.
It is highly beneficial for farmers who want to improve management and strengthen the health of crops. Making decisions based on reliable data, it’s also possible to increase productivity and save inputs.
It is possible to obtain a vegetation index by processing satellite data and different spectral bands. This indicator is associated with vegetation parameters in a particular image pixel.
The reflection characteristics determine the effectiveness of such indices. Most calculations are based on the two most stable sections of the plant spectral reflectance curve.
The NDVI or greenery index, measures vegetation’s degree of greenness, density, and health in each satellite image pixel. It was introduced in the 1970s and has become one of the most commonly used indicators of crop health since that time.
Today it is also one of the key tools of digital farming and precision agriculture. Thanks to the NDVI use, growers can assess vigor during the entire growing season based on how crops reflect particular electromagnetic spectrum ranges.
The spongy layer of a plant is destroyed when the plant is dehydrated or suffers from disease. In this state, cultures absorb more infrared light instead of reflecting it.
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By observing the changes in the near-infrared range compared to red light, the presence of chlorophyll can be determined, which will be high in healthy plants.
How to Calculate the Greenery Index
NDVI calculation involves comparing red and near-infrared light’s absorption and reflection values. The reflection coefficient in the entire red spectral range must be subtracted from the reflection coefficient in the whole near-IR range. The resulting value is divided by the total reflectivity of the near-infrared and red wavelengths.
A simple mathematical formula helps to understand how healthy a plant is by converting raw satellite data into vegetation indices.
NDVI formula looks like this:
(NIR – R) / (NIR + R)
NDVI values from -1 to 0 indicate a dead plant or inorganic objects such as rocks, roads, and buildings. The values of this index are from 0 to 1, where 1 is the healthiest plant, and 0 is the most unhealthy plant.
There are some limitations in applying the normalized difference vegetation index. Sometimes the level of pigment in leaves reaches a critical point. It is called saturation, and it reduces the sensitivity of NDVI.
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The greenery index data become less reliable in the later stages of crop development as the NIR reflectance increases and its value rises.
How NDVI Benefits Agriculture
Thanks to NDVI imagery, building models to predict biomass and yields has become possible. They also make it possible to control irrigation and rationally apply nitrogen fertilizers based on reliable data on the deficiency of this component.
In several plants, including corn and rice, NDVI in agriculture and leaf nitrogen concentrations are correlated. The amount of absorbed light depends on the nitrogen in the leaves. N is a vital component of the chlorophyll molecule that determines leaf color.
Studies of various farming systems have shown that there is a relationship between NDVI values in the early stages of growth and final yields. It is especially true for maize production, as this crop is most vulnerable to nitrogen stress.
The values of this index help to determine yield potential because the green leaf area represents the light energy that enables photosynthesis, which directly causes grain filling and growth.
The calculation of the greenness index is also used to detect diseases at an early stage. It enables taking the necessary protective measures before crop damage occurs.
Infected areas of the field will have low values. Farmers can save a lot of time by directing stingrays to problem areas instead of having to explore the entire field.
What is the NDVI advantage for irrigation? This index can help farmers use water more efficiently by applying it in a targeted way based on data about the needs of plants. It can help to reduce the risk of over-irrigation and to prevent soil degradation or nutrient leaching.
NDVI Index on EOSDA Crop Monitoring
EOS Data Analytics provides satellite analytics for various industries. The company also has agricultural and forestry software products that provide valuable data to improve sustainability and make effective decisions in these sectors.
EOSDA Crop Monitoring is an online satellite platform developed by the company for field monitoring. This solution combines many valuable data types. Users get access to information about field activities, plant health, weather, and soil moisture on a single platform.
This tool is perfect for remote field health monitoring using Normalized Difference Vegetation Index calculations. EOSDA Crop Monitoring users can simply add fields to the system and configure NDVI settings to be notified and monitor changes in index scores and vegetation status.
On the platform, vegetation indices are visualized as convenient graphs. Tracking changes in greenness index indicators during the season helps to track the historical productivity of fields and evaluate the effectiveness of crop rotation.
The Zoning feature available on the platform enables the creation of maps for the variable application of seeds and fertilizers based on NDVI indicators.
With this feature, users can identify areas of high and low productivity measured over long periods. And with vegetation maps, farmers identify areas that need nitrogen fertilization.
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NDVI also assists in scouting operations. Thanks to the platform data, agronomists can direct scouts to a specific place where problems have already been detected, which saves time.