Whether you call them UAVs (Unmanned Aerial Vehicles), UAS (Unmanned Aerial System), Drones, or something less polite – people are more familiar than ever with them. We’ll call them drones, and we’re not talking about the remote-controlled toy kind – we’re talking about the flying robot kind. They have sensors (GPS and more), can be given a Flight Plan (instructions on where to go), and can follow that plan autonomously while carrying out other instructions – no human pilot required. Many high-end tractors are already in service with this kind of automation and we’ve even seen automated harvesting assistance. But flying drones are small and they don’t plant seeds or pull weeds, so what exactly do they have to do with agriculture?
There are certain things that drones are very good at, and there are things in agriculture that are important but troublesome to do or get. Some of these things overlap, and in those spaces is where a budding industry has arisen.
Let’s cover what drones can offer and what growers can use, then dig into what is out there and happening over some fields right now.
These Things are Important to Farmers, but are Limited or Troublesome
- Confirmation: Verifying that plants are growing where and when they should, and checking this as early and often as possible.
- Early Detection of Problems: Detecting areas of poor growth and crop damage as early as possible, limiting impact and maximizing the chances of doing something about it.
- Fertilizer Planning: A crop will never grow completely evenly, and choosing where to put fertilizer and how much to use based on plant density and health (instead of spreading it uniformly) can save significant money. This is called Variable Rate Application and anything that helps it get done more accurately saves money and increases crop yield.
The common thread here is knowledge of what is actually going on, right there in the ground. The term for this is “ground truth”. The usual way to obtain ground truth is by putting your feet on the dirt and using your eyes. But this doesn’t scale well, since crops can cover very large areas. Eyeballing things from a vehicle doesn’t help much, because if there are areas of poor growth mixed throughout a field, it’s very hard to perceive that visually. One part of a field looks pretty much like any other when you’re at anything near eye level. You don’t have the right perspective. That is where drones come in.
What Drones Do
The kinds of drones that have a use in agriculture might look like toys but they are much more obedient. They have capabilities that include:
- Carrying cameras and taking pictures tirelessly, consistently, and with precision.
- Having an unobstructed bird’s-eye view of things, thanks to being airborne.
- Being fast; they are able to cover large areas quickly without needing roads or paths.
Those abilities are used, along with some back-end software processing, to quickly get a depth of information on crops that simply wasn’t accessible before.
Here is what happens: a human gives a drone a flight plan that covers a field. The drone flies over the field in a pattern while taking pictures with one or more special cameras. These pictures are geotagged and overlap each other. After landing, software is used to stitch the photos together into a large mosaic, and processing is done to interpret the amount of light reflected in different wavelengths. Generally speaking, the healthier the plants, the more they reflect in near-infrared – a higher wavelength than visible light not normally perceptible to humans, but can be captured by cameras. Processing this data makes areas of healthy growth stand out compared to everything else, and makes areas of poor growth or stressed plants easy to identify. Having this data generated nearly on demand opens the door to all kinds of better decision-making for growers. Problems are detected earlier and more accurately, and no time is wasted checking on areas where all is well.
How Plant Health Gets Measured
Plant leaves – technically their main pigment, chlorophyll – strongly absorb visible light for use in photosynthesis. But healthy plant leaves also strongly reflect near-infrared (NIR). Different species of plants reflect somewhat differently, but non-plant material does not reflect in this way at all. Gathering this data and processing it in a way that makes it useful is how remote imaging detects plant health.
In the 70’s a method called Normalized Difference Vegetation Index (NDVI) was developed. It was a method of using the NIR reflection phenomenon to quickly and simply identify vegetated areas and their overall condition from satellite imagery that received infrared and near-infrared wavelengths. The principle is well understood and can be observed and experimented with by modifying modern digital cameras to allow them to pick up the correct wavelengths. A number of projects on Hackaday.io explore NDVI, and we covered a “seeing plant health in infrared” project that now provides an open-source tool for NDVI processing and experimentation.
NDVI isn’t quite enough by itself, however. It has practical limitations, and the issues satellite imaging has had to solve are different from the challenges drone imagery faces. Applying the concept to drone imagery has had its own quirks, as this blog entry by startup Agribotix explains in some detail. But fundamentally the NDVI principle is still what allows modern drones to take pictures of a crop with specialized cameras, use computers to process that data, and turn it into a color-coded aerial map that is easily understood.
What’s Around the Next Corner
Providing growth maps and health reports in a timely fashion is currently the most mature application of drones in agriculture, but it is not the only one. Other applications are on the map – such as using drones to not only plan fertilizer application, but to dispense fertilizer directly. In areas where irrigation farming is common, managing a large amount of irrigation hardware is a big job that could be helped by airborne observation. Anything that puts more complete information into grower’s hands faster is a potential for growth, and drones allow more ways to do that than ever before.
Of Course, There are Things in the Way
Implementation issues for emerging industries aside, there are still plenty of other challenges to drone usage. Drone usage outdoors is highly weather dependent. Flying can be limited by weather, but changing conditions like varying sunlight and cloud cover can make data harder to process. Most crops are in rural areas with limited internet access and cellular infrastructure. Limited flight time is a factor, especially for multirotor aircraft. Drones and their cameras are expensive. They might be capable of autonomous flight, but they still require maintenance and skilled operators. Drones are not very good at carrying payloads – we will probably see package delivery by drone before fertilizer application by drone is common. And of course, there’s uncertain government regulation.
There are plenty of variables in agriculture and drone usage only applies to a small number of them, but it’s a budding industry that seems to be growing as quickly as it can – and the world of agriculture is certainly no stranger to high-tech solutions and expensive equipment. But the devil is always in the details, and even when you have all the pieces available, implementation can be rocky. Have any of you been involved this growing industry? Let us know in the comments – we want to hear from you!