Agronomy on the fly

GroundCover Live and online, stay up to date with daily grains industry news online, click here to read more

Key points

  • Unmanned aerial vehicles may have a role in precision agriculture
  • Industry encouraged to focus on sensors and data-processing systems rather than ‘platforms’
  • New generation of multi-spectral sensors on the way 

Ben Boughton recently visited the US and Canada to research how unmanned aerial vehicles might benefit Australian grain growers

Nuffield Scholar Ben Boughton says unmanned aerial vehicles (UAVs) capture useful data, but the sensors and processing systems need further research.

The 27-year-old, who operates a 2200-hectare property near Moree, New South Wales, with his wife Olivia, father Randall and mother Donna, investigated (with GRDC-support) UAV technology applications for precision farming.

Image of Ben Boughton with UAV

GRDC-supported Nuffield Scholar Ben Boughton built his own unmanned aerial vehicle (UAV) as a learning tool. The UAV was built with a 3DR Pixhawk with APM:Plane 3.0.2 autopilot, Finwing Penguin 2815 fixed wing air frame, S100 Canon camera sensor and RFD900 radio. He uses Mission Planner software, which runs on a laptop on the ground and allows the UAV flight path to be programmed and monitored.

PHOTO: Nicole Baxter

He says UAVs have potential, but require work to process the images captured and make sense of the data for use on farms. To this end, companies have emerged in the US and Canada to provide UAV services and products to growers, Ben says.

“They are using UAVs for crop scouting, site-specific weed control, variable-rate applications, identifying varietal differences, right through to three-dimensional elevation modelling to determine where water will flow and counting the number of corn plants in a paddock,” he says.

“The number of corn plants is a predictor of yield so growers in the US Midwest are investigating this area and learning a lot from the information.”

Ben says while some Australian growers have bought quad copter UAVs and video recorders, he argues fixed-wing planes are better suited to precision agriculture because they can cover a larger area in one flight.

But these ‘platforms’ are the simplest part of UAVs, he says. More complex is the camera or sensor used to collect images and the processing software and workflows needed to turn data into useful information.

For growers with little time or capacity to develop the specialised skills required to process and interpret UAV data, Ben says the ‘go-to people’ are agronomists or specialist UAV service providers.

The data has to be given a function, such as linking biomass readings to nitrogen management.

For use as a learning tool, Ben built two UAVs for about $1500 each (the second had to be built because he crashed the first one).

He says problems, such as the consequences of poor machinery settings in crops, show up better with UAV imagery than with satellite biomass imagery because UAV imagery provides more detail. Flown at 120 metres, a Canon S100 camera sensor can provide a ground resolution of 3.5 centimetres, he says.

Problems he has noticed since collecting UAV imagery include strips of crops given low fertiliser rates, areas of poor establishment and old harvester wheel tracks impossible to see with the naked eye.

“We have quantified the damage that random traffic is causing, which has given us more confidence we’re on the right track with controlled traffic,” he says.

His UAV has also been used to detect weed problems. Ben says image quality is high enough to identify individual weeds, a helpful aid for spraying.

However, in comparison with satellite imagery, he says collecting UAV imagery is relatively expensive because it requires a certified operator on the ground at all times keeping the UAV within sight.

“The Civil Aviation Safety Authority (CASA) is reviewing its policy for UAVs in Australia, but currently operators either operate commercially or as a hobby,” he says.

Sensor shortcomings

Going forward, Ben says further research is needed to evaluate the available sensors.

He says the most common sensor used for UAVs is a compact Canon camera modified to capture near-infrared light.

However, repeatability and a common standard are challenges. Two different UAVs collecting data, even at the same time and place, will deliver different data.

If algorithms are to be developed to count plants or calculate fertiliser rates, the cameras or sensors have to operate to a uniform standard.

Ben says the next generation of multi-spectral sensors will be purpose-built for UAVs, although research will still be required to evaluate the reliability of their data.

Other aspects that warrant research, Ben says, are the software and workflows required to turn aerial imagery into useable information.

Using data

Ben says a typical UAV workflow involves flying over a crop to collect 400 to 600 images. These are then ‘stitched together’ with data-processing software on a powerful computer to create a ‘mosaic’ image that can be used as a basis for decision-making.

“Every picture has a GPS point and when stitched together every pixel can be quickly found in the paddock,” he says.

And while a GoPro video camera fitted to a quad copter can capture “cool footage” he says it is not geo-referenced and a quad copter cannot cover as much area as a fixed-wing plane.

Generally, Ben says fixed-wing planes can fly for 45 to 60 minutes and can cover more than 200ha flying at a height of 120m.

And even with this advance, he says, ground-truthing remains crucial: “UAV crop scouting will never replace boots on the ground,” he says. “The UAV just tells you where to look.”

For example, it is possible to load aerial imagery onto a tablet that is GPS-enabled so areas within a paddock can be visited quickly to verify the cause of crop variability or growth issues.

The future beckons

Ben sees huge potential for UAV technology. For example, aerial imagery allowed the Boughtons to discover that their new planter and aircart did not apply pre-plant urea evenly and the problem has since been rectified.

“Our farm has already benefited from the technology,” he says. “As the industry moves forward it’s a matter of making sure we’re capitalising on any new technologies as they are released.”

Scholar starts satellite service

Nuffield Scholar and New South Wales grain grower Ben Boughton recently started a company to provide a platform for accessing satellite imagery over large areas.

Satamap ( is a web-based subscription application designed to work on iPad and desktop computers. Users subscribe in ‘one tile’ units, each equivalent to three million hectares, which provide satellite imagery updated in a 16-day cycle.

The service provides a regular colour image alongside a new vegetation index that shows the biomass variation throughout a district with the ability to zoom down to the micro scale into growers’ individual paddocks. All imagery is archived and recent imagery can be exported for further analysis or offline use.

“There was no easy way to access satellite imagery and I wanted to fix that,” Ben says.

“You can see variation within a paddock because one pixel represents a 30-metre square on the ground. It’s not as precise as an unmanned aerial vehicle (UAV) image because one pixel on a UAV image represents about 3.5 centimetres, but the advantage of a satellite image is it provides a district-wide view and is more cost-effective.”

He says the technology is useful for growers and agronomists who wish to inspect paddocks before putting boots on the ground, and other agribusiness professionals who value up-to-date spatial information over all cropping regions of Australia.


More information:

Ben Boughton
0428 548 688

Details about operating UAVs in Australia are available at the CASA website. CASA expects the rules to be updated in 2016.


New centre aims to boost grains quality


Nitrogen genetics open a new efficiency frontier

GRDC Project Code NUF00010

Region National, Overseas, South, North