Many people are jumping on the unmanned aerial vehicle bandwagon, but that is mainly because of how cool, new and interesting it is to fly the things around.
However, what farmers need to worry about the most is imagery.
Of course, drones are not the only way to get imagery of a field. Everything discussed in this column also applies to imagery from manned flights and satellites.
First of all, imagery from a drone is similar but not the same thing as the picture you take with your digital camera.
A quick lesson is needed on the electromagnetic spectrum (EMS), which are all the energy waves that are coming from the sun.
What is normally thought of as sunlight is actually a whole range of different wavelengths of energy. These wavelengths range from really short wavelengths such as gamma rays to really long wavelengths such as radio waves.
Gamma rays are measured in millionths of a metre, while radio waves can be measured in kilo-metres, with a whole spectrum of wavelengths in between.
Not all of the waves coming from the sun reach to the Earth’s surface, which is a good thing because they would fry us if they did. Fortunately, they are filtered out by the atmosphere and the ozone layer.
What does get through is visible light and a few other invisible light waves such as ultraviolet and infrared. Three things happen to those light waves when they reach an object on the Earth’s surface: they are absorbed, reflected or pass through the object.
Each wavelength reacts differently to the objects they hit. Using a plant as an example, some wave-lengths will reflect off plant tissue and others will be absorbed by it.
Many of the wavelengths that are reflected are seen as green. Red and blue wavelengths are mostly absorbed by the plant and are used for photosynthesis and growth. Reflectance is what we see and, most importantly, what is captured by a camera.
However, it’s not the red, blue and green light waves that make crop imagery so valuable. Instead, it’s those invisible infrared (IR) waves.
Even though the human eye cannot see IR waves, we have cameras or, more properly, sensors that can.
In the same way that the reflectance of visible light waves is captured by a camera, sensors capture the reflectance of IR radiation from plants.
Knowing how red, green, blue and IR wavelengths reflect differently from different plants is useful when identifying crops in imagery. This technique has been used since the 1950s to determine acreage and estimate the yield of different crops in foreign countries.
When I was growing up in Iowa in the 1970s, we had a neighbour who did double cropping in his corn. The problem was that the secondary crop was illegal, and prompted the Drug Enforcement Agency to make regular low altitude manned flights over his cornfield.
The imagery would have shown the illegal crop growing next to the corn.
Even more valuable than identifying a type of crop, IR waves also reflect differently based on a plant’s stress level.
IR waves are mostly reflected in healthy plant tissue but absorbed in plant tissue that is stressed or unhealthy. In fact, the more stressed the plant is, the more IR is absorbed.
IR waves are displayed as red because we can’t see them. The redder the false colour image, the healthier the plants. Pink or light red would indicate stressed plants. This stress will show up in an IR image before a person’s naked eye can see it.
However, an IR image does not give a reason why the plant is stressed. It could be because of pest, drought or lack of fertility.
Because computers see these images as a series of numbers, we can take IR imagery one step further and calculate a normalized differential vegetative index.
If red light is absorbed by vigorous growing plants and infrared is reflected from healthy plants, then NDVI is a calculated index between the two.
The result is a number between plus one, which indicates healthy vigorous growing plants, and minus one, which is pretty much dead.
Including the red light with the IR in the NDVI calculations gives the grower a slightly different result than an IR by itself, which includes plant growth and vigour.
Some people use the NDVI for determining nitrogen use and water for irrigation.
The bottom line is to know how to make use of this imagery.
Focused scouting is one way. Most images from drones are georeferenced, which means that location co-ordinates are known for every pixel in the image.
The location of a stressed crop area can be given to a field scout, who can find the stressed area using a GPS receiver and check it out. The scout may not see the stress in the plants, but an investigation of the area may determine the likely cause of the stress.
Instead of randomly walking through the field, scouts can focus on stressed areas and be more efficient.
Imagery also helps with data analysis because growers can see the result of their crop production practices by comparing a variety planting map, a nutrient application map or pest problem areas to a NDVI map.
For example, a grower may have applied a specific nutrient product at variable rates in a field. An NDVI map would show how vigorously the crop is growing in that field and allow the grower to make decisions about crop response to that product in the future or even within the current crop year.
Comparing NDVI to actual yield maps allows a grower to target areas where yield did not match potential.
Terry A. Brase is an educational consultant, former precision agriculture educator and author. BrASE LLC. Contact him at firstname.lastname@example.org