Case Study: Getting Actionable Crop Data From Drone to Application
We can tell a lot from looking at your field from above but the true value of aerial data comes from taking action. Providing farmers with crop data and showing them problem areas in their fields is great but now what? This is a common question people often ask when they begin working with aerial crop data collected from multispectral sensors and drones. There are many ways to take action with the right information. Translating this data into actionable insights for the farmer is the key in delivering value when using remote sensing technology.
Stu Adam, the director of Agronomeye, mentioned he learned this first hand when we spoke with him about the inception of his company. Agronomeye helps agronomists and growers facilitate a fully functional management decision process. They provide high-resolution maps while using SlantRange multispectral sensor technology to aid in target testing while a proprietary data conversion tool enables the valuable information to be put to work through custom management zone shapefiles.
Agronomeye, on average, will cover 600 hectares a day with their team’s custom fixed-wing drone. They’re helping farmers view the variability of their crops in the field. The farmers were originally excited to see things that weren’t visible to the human eye but they struggled to put the data into action. In order for Agronomeye’s new business venture to be successful, they needed to better understand how this type of technology could help the farmers solve real problems.
They Started Out By Talking to Farmers
Since Stu and his other partners have strong backgrounds in aviation and aerospace avionics they wanted to use their experiences and this technology as a tool and not to just paint “pretty pictures”. Before they got started, they would visit with farmers at the pub and find out what problems they were having and determining if they could help them. Instead of solely relying on what the technology can do they wanted to know about the realistic elements of farming. They understand that farmers have been farming for generations without drones so they wanted to make sure they were providing information in a way that the farmer could understand.
“There was a bit of a roadblock in the workflow because while the farmers could interact with it in terms of doing targeted testing they couldn’t act on the data. They couldn’t put it into their farm management software easily, assign zones, and transfer it over to a controller for a variable rate application according to the needs of the crop.”
While technology can excite those that are new to it and are curious about its capabilities, Agronomeye also understood that in order to be successful within the agriculture sector you needed to understand what the farmers' needs are.
“That was the message we were getting, it was a limiting factor for us to get adoption because it’s okay to tell them it’s a problem but if you can’t fix that problem then they’re no better off.”
The SlantRange system was exactly what Agronomeye was yearning for. After looking at several options, they recognized that our technology would provide greater resolution, quick in-field processing, and calibrated data. Farmers have been exposed to previous types of imagery, satellite for example, and they grow weary of another technological presence in their fields since they have not provided an adequate amount of value beforehand.
How They Provided Actionable Data
The way Agronomeye were able to successfully transform an idea of working with drones into a scalable business was by translating the data they collected into an understandable solution for the farmers they were working with directly.
Working with the University of New South Wales, Agronomeye devised a process to take the highly detailed data from the SlantRange software and shape it before loading it to the farm management software. Once loaded, the files are then able to directly feed into precision ag machinery. Using this process, Agronomeye creates files of varying resolutions as needed by aerial sprayers, tractors, or anything else the growers may use for their precision agriculture application.
They are now working with farmers that have hundreds of hectares of various crops. The most common crop they engage with is cotton. Now they are growing the vineyard side of their business since they have discovered that flying the drone over rows can help determine which parts of the vineyard have grapes that are mature enough for picking.
Farmers finally found value in this technology when they were engaging with high-value crops in the region. They knew they could be doing things differently but they weren’t aware of what was available to them until Stu and his team entered the picture 4 years ago. Agronomeye pilots plan flights with farmers the day before an agronomist will be on site so they can map the field and quickly process the data prior to their arrival. On the back end, they would use the technology in a customized way to suit their needs for variable-rate applications.
“It was really building the data into their workflow in a way that they could manage and make it into a custom fashion...so the farmer being able to really handle his data in his own way for his own purpose was the message we were hearing from them in a big way. That was what convinced us that there was a gap in the market and if we could do it on a large scale.”
Variable Rate Prescription in Cotton
Using the data Agronomeye collected, they created a variable rate prescription to apply an optimal amount of growth regulator instead of doing a traditional blanket application. This saved the grower on input costs and made sure the right amount of chemical was being inputted into specific parts of the field.
Identifying Mature Grapes in Vineyard
A vineyard wanted to be able to locate grapes that were ready for harvest. By identifying the more mature grapes, the grower can streamline their harvest. It also ensures the highest quality grapes are going to market at the optimal time. By collecting data and converting it into variable zones, the grower was able to do just that.
Farmers Want Solutions, Not Just Data
The value wasn’t determined to be entirely economical or time-based but rather a combination of the two. Emphasizing the workflow that is created by combining high-resolution multispectral data and variable rate application allowed his customers to see the bigger picture: that this workflow, when it is understood by the user, will help them transform the way they work in the field.
The initial high-resolution maps are an essential ingredient for Agronomeye’s success. They feed into their custom algorithm and they result in files the growers’ farm management software can use to direct the precision ag machinery. They also provide excellent maps to the grower for conducting ground-truth sessions against the initial data. By providing them, along with sending them through their custom processing, they save growers the time and effort required to re-interpret maps for their machinery.
The Agronomeye team’s algorithm has been designed to be open-ended and enabled to communicate with varying farm management systems. Their goal is to spread this workflow to other growers in their current market and beyond.
Bridging the gap of this multispectral technology to the actual application was what allowed Agronomeye to take off 5 years ago and now they are recognized as one of the three Aussie innovative startups to watch according to CeBIT.
Finishing up our conversation with Stu, we wanted to learn if he had any takeaways for those wanting to enter precision ag and he had a practical response, “You don’t know what you don’t know until you go out there.” The emphasis of educating yourself before entering into this space is critical, whether you’re evaluating multispectral sensors, analytics software, or which drone to invest in, there’s always a learning curve.