Eye in the sky

The octocopter is an enabling technology. It can be controlled manually or fly itself via GPS, and is fitted with special cameras that can image crop height, growth and biomass, and in the future much more.

The craft has a regular RGB (red blue green) imager as in a conventional digital camera. It also has a TIR (thermal infrared) camera which can be used to monitor the crop canopy or soil temperature. The canopy temperature can give an indication of crop stress, because when plants experience drought for example their temperature rises as they stop evaporating water from their leaves.

The thermal infrared (TIR) camera can capture information about plant stress. Image: Rothamsted Research

The octocopter also carries a NIR (near infrared, also called multispectral) camera that takes images from which a measure called the Normalised Difference Vegetation Index (NDVI) can be calculated. NDVI gives an estimate of crop biomass, which is essentially the growth that scientists want to know when comparing different plant varieties or growing systems.

“We have found that we can measure crop height accurately from the images. We can also measure NDVI from images, usually we take these measurements on the ground, but the octocopter should be much quicker,” says Riche.

Besides speed, other advantages include measurements that will be more accurate and consistent than if done by the human eye; it also frees up time for research assistants to tackle other projects — 16 minutes flight time could collect maturity data that would take four hours to collect in the normal way. However, some time is spent preparing for flying and then downloading and extracting data post-flight.

The near infrared camera (NIR) can take images from which a measure of crop growth can be calculated. Image: Rothamsted Research

Crunch time

The process by which individual photographs taken on the copter’s boom are translated into growth data demonstrates just how far imaging technology has developed since the advent of the first digital cameras.

In the first step, images are fed into software that aligns them to be geometrically uniform and true to scale in a process called orthorectification. “This means it makes them appear that they were taken parallel to the ground even if the camera was at an angle when the picture was taken,” Riche explains.

Over 500 photos from one octocopter flight can be made into this type of orthomosaic image. Image: Rothamsted Research

The images are then added around each other into a large mosaic. With up to 500 images of a single experiment, there’s a lot of overlap and the software (Agisoft Photoscan) stitches the images together to make one large orthomosaic. Next, the image is geolocated so it is located in real space and has proper scale, and this means meaningful measurements can now be taken from the image. The geolocation uses permanent markers (‘ground control points’) located within the experimental area, and accurately located by precision GPS — accurate to an astonishing 1cm.

“Finally the software produces a three dimensional model of the imaged area, using the large amount of individual images to build the 3D model,” says Riche. “From the 3D model the height of the crop can be extracted, with different values for each individual plot.”

Computer software can make up a mosaic from which growth data can be extracted. Image: Rothamsted Research

Legislating for the future

Besides data on growth, crop colour could also be an important indicator. Plant pathogens such as wheat rusts and certain viruses cause a characteristic yellowing of the crop. In the future, analysis of images could pinpoint areas for treatment with pesticides or biological agents like natural predators.

There are many other uses for drones in agriculture. In other countries farmers are using them to sow seeds and apply pesticides, and in forestry and national parks there are many applications, particularly in essential monitoring over very large areas.

Andrew Riche of Rothamsted Research inspects the octocopter’s rotors before flight. Image: BBSRC

It’s not too hard to see a future where an automated drone could search fields for areas of crop damage from pests, or see nutrient- or water-stressed plants from above that the human eye would miss. The drone could then feed the GPS co-ordinates to a farm worker, who could then manage the appropriate response. As the physical capability of drones increases, as well as reliability, you have to wonder if the drones themselves could not spray pesticides and drop fertilizer pellets in the right space and in ultra-low quantities, negating the need to treat entire fields with heavy tractors that can compact the ground and damage soil.

But Riche doesn’t think all these uses are likely to happen too soon, at least in the UK. “There are currently companies offering a service to farmers for monitoring fields by UAV, however this is a specialist area at present, as current legislation makes it difficult to operate UAVs over a large area,” he says. “And I think we are a long way from seeing seeds or pesticides being applied by UAV, however I think they have an important role in monitoring field experiments.”