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Finding a place for drones in your toolbox

Extension Crop Connection: The newest member in the remote-sensing family can fill gaps when conventional satellite and manned-aircraft imagery lack details.

By Yeyin Shi

As the 2019 growing season approaches, think about using a drone as a handy tool for in-season scouting, management and growth information documentation.

Drone-based aerial imagery is the newest member in the remote-sensing family. In-season satellite and aerial imagery are known to be a great complement to the end-of-season yield maps by providing in-season information to help explain yield variability.

Drone imagery fills the gap when conventional satellite and manned-aircraft imagery are not available or lack details. One of the biggest advantages of drones is that they are easy and flexible enough to be operated whenever desired, either regularly throughout the growing season or intensively at critical times.

The ability to quickly view a field from above in real time can be an invaluable scouting resource to identify areas of concern. With an inexpensive consumer-grade drone and a standard natural-color camera, videos or imagery can be displayed in real time on the flight controller in the hands of the remote pilot or viewed with virtual reality goggles by another person. A rotary-wing drone can be easily maneuvered to descend and hover over the areas of interest for close examination. For example, the drone can be used to check irrigation issues or crop stresses in crop production, and the pasture forage availability or fence conditions in livestock production.

Drones also can be used to generate field maps during the season. These field maps can be used to see spatial variation for in-season management, such as nitrogen sidedressing or fertigation, or to evaluate cover crop biomass production and vitality to determine termination timing and effectiveness.

They also can provide an objective documentation of temporal changes within and between growing seasons for long-term observations, such as how a crop responds to a hail damage, the effects of cover crops on soil and cash crops, and the spatial progression of soilborne disease or herbicide-resistance weeds. In many of these cases, vegetation index maps derived from a multispectral camera with near-infrared spectral bands or a thermal camera can provide better prescriptions than regular natural-color maps. To create vegetative maps of an entire field, images automatically are triggered along a preplanned flight path and stored with GPS coordinates to be stitched to a map later by commercial software on a local computer or with cloud-based services.

Drone imagery also is highly detailed, allowing users to catch stresses early. The finest element, or pixel, in a drone image often corresponds to a 3-by-3-inch or smaller block area on the ground. The level of detail you will be able to see depends on how high you fly and what camera you use. For comparison, a typical manned-aircraft image would be 3 by 3 feet, and a typical satellite image would be 30 by 30 feet. These systems provide far less detail. With drones, however, we can clearly see the difference between rows in an image. This feature is critical to diagnose problems precisely and quickly to minimize potential losses.

Extension programs at the University of Nebraska-Lincoln have been conducted on the topics of using drones for agriculture, including regulations by the Federal Aviation Administration, how to select drones and sensors based on the applications and budget, how to design and operate the flights, how to process, visualize, interpret and manage the data, and how to control the data quality throughout.

You can access a free NebGuide, “Getting Started with Drones in Agriculture,” at go.unl.edu/drone. Research is ongoing to study remote-sensing imagery for various agronomic applications. Some of these projects are conducted on producers’ farms with the UNL On-Farm Research Program.

Whether you are a producer, a consultant or a service provider, we hope to provide useful information regarding drone technology and welcome your suggestions and feedback. You can contact Yeyin Shi at yshi18@unl.edu. As sensor, data computing and networking technologies quickly advance, drone-based aerial imagery will become a handy, economical and indispensable tool for every producer.

Shi is an assistant professor and agricultural information systems specialist in the Department of Biological Systems at the University of Nebraska-Lincoln.

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