NDVI Explained: Understanding the Normalized Difference Vegetation Index

The Normalized Difference Vegetation Index (NDVI) is a measure of vegetation health. The index measures how plants reflect and absorb light in the near-infrared spectrum and is an indirect measure of the amount of chlorophyll. Farmers can use it to monitor plant growth and estimate plant health.

The result is normalized and NDVI is a measurement farmers can exploit for precision agriculture. It lets them figure out the best time to irrigate, fertilize, or apply pesticides to their crops, as well as predict crop yields. In addition, NDVI gives insight into other factors such as plant disease or a lack of water.

What Is NDVI?

NDVI is one of the most common indexes for measuring crop biomass. It measures the difference between the amount of near-infrared light (NIR) plants reflect compared to that of red light. Healthy vegetation reflects NIR, while sickly or poor biomass absorbs a significant amount of near-infrared light.

NDVI values range between +1 and -1.

A high positive value reflects dense and healthy leaf cover, while lower figures suggest sparse foliage. Bare soil and rocks absorb near-infrared light and have an NDVI value close to zero. Negative values indicate water, snow, or clouds that reflect red light.

Other vegetation indexes include:

• Enhanced Vegetation Index. EVI is more sensitive to differences in high biomass vegetation.
• Soil Adjusted Vegetation Index. SAVI adjusts for soil brightness for better measurements in regions with sparse vegetation.
• Normalized Difference Water Index. NDWI measures changes in the water content in leaves.

How NDVI Works: The Science Behind It  

NDVI is the ratio of the reflectance of red light compared to near-infrared light. The formula is:

Where:

• NIR is the reflectance of near-infrared light.
• Red is the reflectance of red light in the spectrum.

As mentioned above, the possible range of values for NDVI are from +1 to -1.

Research has shown that plants with healthy vegetation reflect near-infrared and green light, but absorb more blue and red light. Many satellites measure light in the NDVI spectrum.

Some typical values for NDVI include:

NDVI Applications in Agriculture

Farmers and agricultural scientists use NDVI scans and images to monitor crops, manage the application of fertilizers, optimize irrigation, and improve crop selection.

Crop Health Monitoring

NDVI values for healthy vegetation are consistently higher than for stressed plants. If you notice a sudden drop in the index, this may be a symptom of chlorophyll shortage as a result of disease, pest infestation, or lack of moisture. A reduction may also show that the plants are stressed and need nutrients or fertilizer.

On a broader scale, the index is useful for managing forests and understanding desertification. Fire services can use the index to determine fire risk areas that need clearing.

Precision Fertilization and Input Optimization

Farmers can exploit NDVI mapping in agriculture to predict the right time to irrigate and apply fertilizer optimally according to crop needs, be it different fields or varying requirements within a single field. Also, by continually monitoring crops, you get an early warning of a pest infestation or crop disease, which allows you to timely take corrective action. This type of information helps reduce waste and improve ROI.

Yield Prediction and Crop Management

NDVI monitoring through drones or local cameras helps to compile NDVI scans collected over time and during different growth stages to estimate crop yields. This information improves the closer management of crops and gives early warning of unexpected changes in crop health.

Soil and Irrigation Management

By monitoring NDVI trends, it's possible to monitor soil moisture levels and optimize irrigation needed at different stages of growth and in different fields. NDVI data helps you figure out the best time to start reducing irrigation for crops such as tomatoes that benefit from such practices.

Another benefit is the ability to identify clay-rich soils that are retaining excessive moisture and to improve drainage to prevent root damage.

Seed Selection and Breeding

Research institutions and agricultural universities use NDVI to support studies into seed varieties and discover types that perform better in certain conditions. They experiment to assess how different varieties respond to heat stress and drought conditions. This information helps develop higher-yield crops and improve the understanding of agricultural practices in different regions of the country, especially those that are drier, with less abundant rainfall.

How to Access NDVI Data

You can obtain NDVI data from satellite imagery, drones, or localized sensors and cameras.

Satellites

Many satellites incorporate near-infrared filters and NDVI imagery, such as:

• Landsat
• Sentinel 2
• Spot
• Pleiades

A specific benefit of satellite imagery is that it provides a consistent record over time, helping you make informed comparisons.

Drones

Drone imaging lets you create NDVI maps and closely monitor crops in high-resolution detail. By using pre-programmed flight plans, it's possible to cover the same area to monitor crop health with higher precision.

Field Cameras and Hand Sensors

Carefully positioned agricultural cameras provide a continuous record of plant health. Handheld NDVI sensors provide similar information and are easily moved from field to field.

NDVI Software

You can download satellite data into platforms such as Cropler's web platform. These software platforms let you monitor individual crops and compare yields and crop health on your farms.

When you have questions, we'll help you find the answers you need to take control of your fields and the harvest you care about. Contact Cropler to discover more about our products and the ways we help you proactively protect your operations from the effects of crop diseases. Learn More

Limitations & Best Practices

There are limitations to NDVI technology, including:

• Saturation. NDVI images saturate in dense foliage, making comparisons difficult.
• Inconsistency. NDVI values aren't consistent across different satellites and platforms.
• Atmospheric interference. Cloud and haze affect NDVI satellite readings.

Resolution. Satellite images may not be of sufficient resolution.

You can overcome these limitations through a comprehensive approach. For example, you could use one satellite and supplement that data with drone or camera imagery (a specific benefit of satellite imagery is that you create a consistent record over time). Also, the combination of different techniques such as EVI, SAVI, and NDWI provides better resolution. Finally, capture images at the same time and in sunny weather to avoid lighting variations.

Conclusion

NDVI mapping supports precision agriculture and can help you improve crop yields and increase profitability. With detailed NDVI data, you can optimize irrigation and the use of fertilizers and herbicides, as well as notice early signs of crop diseases and other threats.

Cropler offers convenient solutions for field monitoring, including NDVI imagery. Explore the features of our agri-cameras, web platform, technologies used, and other aspects on the FAQ page, or contact us to learn how Cropler can help in your unique situation.