The Potential of Drones in Research
Someday soon, multi-rotors will execute pre-programmed flight paths over several hundred research plots collecting daily data and sending it back to a computer while researchers sip their morning coffee. Researchers and growers won’t need to know anything about flying: the drones will fly themselves. This is the dream.
One UAV (unmanned air vehicle) industry leader at the above drone demonstration commented, “The truth is that this is where agriculture (and research) is going, and I don’t mean ‘Tomorrowland’ going–I mean it’s pretty much there. The only thing that’s holding us back is a permit from the FAA for autonomy, and that’s because the FAA is slowly backing into this UAV piece because we have the busiest general aviation sky in the world. But really, what you should have in your mind is multiple units operating with a single operator in a control vehicle.” The above UAV was extensively tested in California’s NAPA valley with results soon to be published online.
In this blog, a METER scientist and an instrumentation engineer give their perspectives on what needs to happen before drones reach their full research potential.
What are the advantages of drones for researchers?
Dr. Colin Campbell, research scientist-
One of the biggest challenges of work in the field is variability: low spots, high spots, sandy soil, clay soil, hard pans beneath the surface in some areas and not in others. This results in highly variable performance in crops. In addition to that, even when you have good homogeneity in a field, you might have differences due to irrigation or rainfall. If we want to improve agriculture, one thing that we have to do is be able to come out with better tools to be able to visualize the field in more than a single dimension. In order to do this right now, students go out and take plant measurements all day, every day, all summer long. The advantage of a drone is that you could do flyovers of a field, monitoring the traits that you’re interested in using reflectance indices that would normally take days of work.
What are the obstacles to progress?
Greg Kelley, mechanical engineer, and drone hobbyist-
Recently, the FAA has come out with a set of guidelines for the industrial use of drones: flying machines have to stay under a certain ceiling (500 ft; 150 m), and they have to be flown in the line of sight of the operator. The naive thing about those policies is: how much control does the operator have over the drone anyway? It used to be that with your remote control, you were moving the control surfaces (flaps, rudder, etc) on the aircraft, but this is changing. The onboard computer performs things like holding a stable altitude, maintaining a GPS location, or auto-stabilization (it keeps the aircraft level, even when a gust of wind comes). Those are degrees of control that have been taken away from the operator. Thus, according to the level of automation that the operator has built into the system, he may not be in direct control at all times. In fact, these machines are being developed so that they can fly themselves. From my perspective, the FAA regulations are going to have to evolve along with the automation of drones in order to allow the development of this technology in an appropriate way.
What needs to happen before drones reach their full potential?
Dr. Colin Campbell–
Even if we get the flexibility required with drones, we’ve got to get the right sensor on the drone. On the surface, this seems relatively simple. Sensors to measure spectral reflectance are available in a package size that should easily mount on a drone platform. But, there are still many challenges. First, current spectral reflectance sensors make a passive reflectance measurement, meaning we’re at the mercy of the reflected sunlight. Clouds, sun angle, and leaf orientation, among other things, will all affect the measurement. There are several groups working on this (just search “drone NDVI” on the internet), but it’s a difficult problem to solve. Second, drones create a spectral reflectance “map” of a field that needs to be geo-referenced to features on the ground to match measurements with position. Once data are collected, the behavior of “plot A” can only be determined by matching the location and spectral reflectance of “plot A.” Different from the first challenge, this is more related to programming than science but is still a major hurdle.
Despite these challenges, drones promise incredible benefits as an agricultural and environmental measurement tool. As one industry leader at the drone demonstration put it, “the complexity of the problems that agriculture faces and the opportunities for efficiencies are vast. It will require ongoing engagement, next year and the year after that. There are a lot of questions to be answered and the efficacy is yet to be determined, but it’s exciting to watch the UAV helicopter and where it’s going.” Both Campbell and Kelley agree that significant advances will be made within the next few years.
Read about an ROI calculator that’s been created to help growers quantify whether the benefits of using a drone will exceed their costs.
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