Understand what UAVs actually see

To understand the possibilities for unmanned aerial vehicles in agriculture, we must first understand the term “normal difference vegetation index,” or NDVI. It is a measure of how plants reflect light. Corn and soybeans are green because their leaves and tissue reflect the color green while absorbing all other colors in the visible light spectrum, such as

Understand what UAVs actually see

To understand the possibilities for unmanned aerial vehicles in agriculture, we must first understand the term “normal difference vegetation index,” or NDVI. It is a measure of how plants reflect light. Corn and soybeans are green because their leaves and tissue reflect the color green while absorbing all other colors in the visible light spectrum, such as red and blue. The plants use the light energy to create carbohydrates. Plants also reflect near infrared, or NIR, light, which we cannot see. The amount of NIR light that is reflected is substantially more than that of the green light (see Figure 1, right). As plants begin to stress, they stop absorbing red and blue light to use for energy. Instead, stressed plants begin to reflect all colors in the visible light spectrum, which gives the plants a yellow or brown color. This is important because stressed plants reflect considerably less NIR light compared to healthy plants. Since we cannot see NIR light, if we can use sensors to measure the large drop of NIR reflectance due to a stressed plant, we can potentially detect a stressed plant before the stress is visible to our eyes. And that is the potential for UAVs. Imagine the day when you will know your plants are stressed before you can see it.

The components in the NDVI equation are shown in Figure 2 on Page 37. Notice that there is a minus sign on top of the equation and a plus sign on the bottom. This ensures that no matter the inputs for NIR or red, the result will always be a number between -1 and 1, creating an index. Healthy green tissue will be closer to 1, with bare soil and water resulting in a number around zero or lower. This gives us definitive numbers for areas of the field, and these numbers can be used to determine zones of interest.

Goals

Creating zones is the ultimate goal of using NDVI maps from UAVs. If the UAV detects crop stress before the human eye can, and we can actively do something to reverse that stress, we will be on track to increase our yields and efficiency. For example, we could fly a field and develop an NDVI map to show areas of the field that are nitrogen-deficient. We could then create a variable-rate sidedressing map to target those areas low in nitrogen.

Roadblocks

As with any new technology, there are a few issues to work through — specifically, light quality during flights. Spotty clouds will skew light reflectance in areas of shade during the flight. Also, light will differ between flights at different times of the day.

For this reason, it is difficult to compare the NDVI values for multiple flights, but we can still compare values within one single flight.

Future

The UAV industry will push technology very quickly in the next few years, and we will see refinements in the NDVI process. The industry will use a variety of sensors: multispectral, thermal and elevation.

As sensors become more accurate, we will also be able to detect many other stresses, including weeds, insects, diseases and herbicide drift damage.

Berg is a precision systems specialist with Peterson Farms Seed, Harwood, N.D. For more information, contact him at 866-481-7333 or n[email protected]

02151248AA.tif

Figure 1

NDVI =

( NIR-Red )

( NIR+Red )

Figure 2

This article published in the February, 2015 edition of DAKOTA FARMER.

All rights reserved. Copyright Farm Progress Cos. 2015.

Crop Management

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