Ryan Kunde is a winemaker whose family’s picture-perfect vineyard nestles in the Sonoma Valley north of San Francisco. But Kunde is not your average farmer. He’s also a drone operator—and he’s not alone. He’s part of the vanguard of farmers who are using what was once military aviation technology to grow better grapes using pictures from the air, part of a broader trend of using sensors and robotics to bring big data to precision agriculture.
- BreakthroughEasy-to-use agricultural drones equipped with cameras, for less than $1,000.
- Why It MattersClose monitoring of crops could improve water use and pest management.
- Key Players3D Robotics
What “drones” means to Kunde and the growing number of farmers like him is simply a low-cost aerial camera platform: either miniature fixed-wing airplanes or, more commonly, quadcopters and other multibladed small helicopters. These aircraft are equipped with an autopilot using GPS and a standard point-and-shoot camera controlled by the autopilot; software on the ground can stitch aerial shots into a high-resolution mosaic map. Whereas a traditional radio-controlled aircraft needs to be flown by a pilot on the ground, in Kunde’s drone the autopilot (made by my company, 3D Robotics) does all the flying, from auto takeoff to landing. Its software plans the flight path, aiming for maximum coverage of the vineyards, and controls the camera to optimize the images for later analysis.
This low-altitude view (from a few meters above the plants to around 120 meters, which is the regulatory ceiling in the United States for unmanned aircraft operating without special clearance from the Federal Aviation Administration) gives a perspective that farmers have rarely had before. Compared with satellite imagery, it’s much cheaper and offers higher resolution. Because it’s taken under the clouds, it’s unobstructed and available anytime. It’s also much cheaper than crop imaging with a manned aircraft, which can run $1,000 an hour. Farmers can buy the drones outright for less than $1,000 each.
The advent of drones this small, cheap, and easy to use is due largely to remarkable advances in technology: tiny MEMS sensors (accelerometers, gyros, magnetometers, and often pressure sensors), small GPS modules, incredibly powerful processors, and a range of digital radios. All those components are now getting better and cheaper at an unprecedented rate, thanks to their use in smartphones and the extraordinary economies of scale of that industry. At the heart of a drone, the autopilot runs specialized software—often open-source programs created by communities such as DIY Drones, which I founded, rather than costly code from the aerospace industry.
Drones can provide farmers with three types of detailed views. First, seeing a crop from the air can reveal patterns that expose everything from irrigation problems to soil variation and even pest and fungal infestations that aren’t apparent at eye level. Second, airborne cameras can take multispectral images, capturing data from the infrared as well as the visual spectrum, which can be combined to create a view of the crop that highlights differences between healthy and distressed plants in a way that can’t be seen with the naked eye. Finally, a drone can survey a crop every week, every day, or even every hour. Combined to create a time-series animation, that imagery can show changes in the crop, revealing trouble spots or opportunities for better crop management.
It’s part of a trend toward increasingly data-driven agriculture. Farms today are bursting with engineering marvels, the result of years of automation and other innovations designed to grow more food with less labor. Tractors autonomously plant seeds within a few centimeters of their target locations, and GPS-guided harvesters reap the crops with equal accuracy. Extensive wireless networks backhaul data on soil hydration and environmental factors to faraway servers for analysis. But what if we could add to these capabilities the ability to more comprehensively assess the water content of soil, become more rigorous in our ability to spot irrigation and pest problems, and get a general sense of the state of the farm, every day or even every hour? The implications cannot be stressed enough. We expect 9.6 billion people to call Earth home by 2050. All of them need to be fed. Farming is an input-output problem. If we can reduce the inputs—water and pesticides—and maintain the same output, we will be overcoming a central challenge.
Agricultural drones are becoming a tool like any other consumer device, and we’re starting to talk about what we can do with them. Ryan Kunde wants to irrigate less, use less pesticide, and ultimately produce better wine. More and better data can reduce water use and lower the chemical load in our environment and our food. Seen this way, what started as a military technology may end up better known as a green-tech tool, and our kids will grow up used to flying robots buzzing over farms like tiny crop dusters.
—Chris Anderson, the former editor in chief of Wired, is the cofounder and CEO of 3D Robotics and founder of DIY Drones.
One of the most common questions I get asked in grower presentations or at ag shows is: “How do I get started in precision ag?” Perhaps a better question is: “What do I need to do to be successful in precision agriculture?”
The precision success stories in this issue provide good examples of individuals who have been successful over the years. But it is sometimes helpful to think back on what are the steps to this success. This thought process is especially instructive to folks who are getting their feet wet for the first time in precision agriculture.
The first step to success is determining whether there is a need for precision agriculture in your enterprise. Just running out and getting a bunch of software or going online may be more of a liability than an asset if there is no well-defined need for the effort. This need can be in the form of expected efficiency in operations or in having better records of decisions made and actions taken in production. The need could be driven by regulatory demands or a proactive position to be in the lead with new ideas in the industry. Whatever the reason, it is important to recognize why one gets involved in precision agriculture.
The second step is determining the specific requirements that will fulfill the identified need or needs. Requirements can be synonymous with technology tools. For example, if I have a need to map my farm, I may require geographic information systems (GIS) software to make boundaries of my fields. If better records are my need, I may require an on-line record keeping program. If I need to report my production practices to buyers, a tracking program may be in order.
Once the requirements have been enumerated, the third step is to identify the personnel within your organization who are going to use IT tools. If you do not have the right people, the tools will be of little or no value. While everyone wishes for a program with a “magic” button that gives an answer, the truth is a user must have a minimum understanding of how a tool works. Before making an investment in tools or education, it is important to find the right individual(s) for the job.
The fourth step to success is training and support, whether from within an organization or outside. Handing someone a set of tools without training can be both frustrating and costly to all involved. Furthermore, the lack of follow-up support for a program can waste untold hours and leave participants feeling abandoned at the most inopportune time. Support is probably one of the most important but least appreciated aspects of any precision agriculture effort.
The fifth step is back-up, whether in the form of an alternate plan to do something or just archiving important information. Back-up also pertains to people. At least two individuals should be trained to perform the same skills. There should be at least two computers with similar configurations to ensure a possible failure of one. Back-up is more than just an insurance policy; it provides added capability in times of short-term, high demand.
Some Steps Beyond
The five steps for success in precision agriculture — determine need, specify requirements, identify personnel, train and support, and provide back-up — must be accompanied by other common sense practices. One such practice is allowing for adequate time to incorporate a precision agriculture technology into an existing enterprise. Whatever time was planned for adding a tool, you should double it. Everything takes longer because of integration issues, resistance to change, and just normal feedback during installation.
Another common sense practice is constant communication during the step-by-step process for incorporating precision agriculture tools. Communication in the form of documentation, check-off lists, and periodic updates on progress keeps everyone focused and on the same page. Lastly, common sense dictates that you never take on more than you can handle. It is better to have one small tool delivered and working, than a number of them incomplete and behind schedule. The careful planning and allocation of resources in any application always pays off in time and savings.
As a final note, precision agriculture is about harnessing technologies to improve decision making and production practices. New technologies, by their nature, are going to be disruptive to an existing operation. But this disruption can be for the betterment of the enterprise if the right steps are taken in combination with a common sense approach.