The implementation of vegetation indices reveals what the human eye cannot catch and help to identify crop threats before serious damage occurs. It is a precious solution for contemporary agriculture. They VIs help farmers to monitor fields and obtain accurate data from a distance. It is a tool to control critical factors in crop production.
VIs are commonly used in remote sensing applications across various airborne and satellite platforms and, more recently, unmanned aerial vehicles. A simple and effective algorithm enables the evaluation of the density and, for instance, dynamics of greenery development.
There is no single mathematical expression for all VIs, as the combinations of light spectra, instruments, platforms, and resolutions are complex. Customized algorithms and invisible spectra combining visible light emission, predominantly in the green part of the spectrum, have been developed and tested to provide indirect quantitative estimates of land cover. In real-world applications, calculations are optimized according to specific requirements and applications are combined with appropriate on-site verification tools and methodologies.
Many growers today know that they can use NDVI index for vegetation state check. However, more than 40 vegetation indices have been created to improve foliage response and minimize the effects of spatial and temporal variations of the atmosphere, soil brightness and moisture, shade and environmental influences.
How it Works
Optical satellite sensors measure solar radiation reflected from the objects on the ground. Multispectral sensors have several bands, each sensitive to a narrow range of wavelengths like blue, green, red, near-infrared, or short-wave infrared. They do not cover the entire spectrum but different parts of the electromagnetic spectrum, typical for different vegetation types.
Light reflected by vegetation has low values in the blue and red ranges and slightly higher values in the green range. However, depending on the wavelength, it shows very high values in the near-infrared and low to high values in the short-wave infrared. A distinctive feature of vegetation’s spectral signature is a sharp increase in reflectivity from the red to near-infrared region, known as the “red edge”.
How to choose the proper formula? It depends on the purpose of the application, but the optical ranges in which they operate differ in color. Most commonly, near-infrared reflectivity is utilized to establish a connection with healthy vegetation development.
Different remote sensing methods enable the calculation of various parameters
- green cover percentage
- green biomass
- chlorophyll content
- leaf area index
- absorbed photosynthetically active radiation
The design of multispectral sensors differs depending on the intended application. The RapidEye sensor, featuring a unique red edge band, was designed for vegetation studies and agriculture. Similarly, the MSi sensor onboard Sentinel-2 will have three new bands in the red-edge region.
NDVI Index
The Normalized Difference Vegetation Index is generally utilized to follow every step of crop development. The obtained values indicate the activity of photosynthesis process. NDVI is a helpful tool throughout the growing season, but its effectiveness depends on vegetation density. The reason is that the spectral reflectivity decreases when dealing with sparse vegetation.
Healthy vegetation contains a high chlorophyll concentration and reflects mainly infrared (NIR) and green light while absorbing red and blue light. This is why we see plants green. If NIR is used to decipher color, the vegetation will be brightly colored. Satellite sensors are equipped with the necessary ranges with near-infrared and red.
The formula for NDVI calculation looks like this:
NDVI = (NIR – RED) / (NIR + RED)
Overall, the application of Normalized Difference Vegetation Index is a reliable way to estimate healthy foliage. High values prove healthy plants; low values indicate less or no vegetation. Atmospheric correction can help to observe changes in vegetation over time. The use of the NDVI formula can also become a reliable indicator of drought.
How Vegetation Indices Change Farming
Integration of remote sensing technologies into agricultural businesses is a proper step on the way to effective resource allocation, high and sustainable productivity. It can change the game completely. Considering climate change and the environmental damage that the farming lands expansion causes, the best option today is not to increase the area under crops, but to increase the productivity of existing fields. This is where vegetation indices come to the rescue.
VI calculations provide producers with a wide range of options. Monitoring of physicochemical parameters is one of them. Obtaining data on evapotranspiration, greenness, soil moisture, proxy chlorophyll, and temperature can be critical to ensuring optimal growth.
Innovative approaches can enrich the experience and skills of agricultural producers by providing valuable data about an area or region in almost real-time. This is the key to monitoring the condition of fields without physically visiting. What does this mean for farmers? Guided by comprehensive information about the health of plants and the condition of the fields, it is possible to set scouting tasks more accurately and take measures to protect the crop or revise management on time.
NDVI images are combined with other indices. This combination provides greater insight into plant health and nutrient availability. This helps producers accurately determine the impact of weather, the environment, diseases and pests on their fields, as well as identify areas of low fertility.
VIs can enhance the farmland management and transform the whole decision-making process. Reliable data helps to create an effective schedule and irrigation system and determine the timing of sowing, harvesting, and other vital field activities. Vegetation index mapping, including the NDVI map, is quite valuable as a source of future reference information to note periodic changes over time.
