Texas A&M Researchers Using UAVs to ‘Read the Weeds’

Texas A&M AgriLife Research is deploying unmanned aerial vehicles (UAVs) as part of a project to determine the right tools for early identification and control of weeds.

Dr. Muthu Bagavathiannan, an AgriLife Research weed scientist at Texas A&M’s College Station, is using drones to “read the weeds,” says the university.

“Our goal is to use advanced sensor technology to detect weeds from above the ground and implement precision weed management,” Bagavathiannan says.

The current practice is to have field scouts walk the large fields to look for weed issues, he explains. However, this is a tedious, time-consuming task that can be inaccurate, and bad weather conditions can prevent timely assessments of weed problems.

“But the UAV technology would provide the ability to fly over large fields and collect reliable information in a short time period that can be directly relayed into actionable information,” Bagavathiannan says. “We need this technology to make that identification sooner than the naked eye can.”

“The ultimate goal is to identify the weed species, the areas of the field they appear, and in what densities so precision herbicide applications can be made or a herbicide program developed that better suits what is in the field,” adds Dr. Vijay Singh, an AgriLife Research assistant research scientist working with Bagavathiannan in College Station. “Geotagged maps would allow coordinates to be fed to a ground vehicle or an aerial applicator to treat specific areas.”

Members of the Texas A&M team that Bagavathiannan works with in College Station, among others, include Dr. Nithya Rajan, AgriLife Research crop physiologist; Drs. Michael Bishop and Anthony Philippi at the Center for Geospatial Sciences, Applications and Technology (GEOSAT); and Dr. Dale Cope, associate professor in the department of mechanical engineering.

According to the university, the GEOSAT scientists are creating algorithms and indices that can one day be used by crop consultants to help producers identify weeds earlier, achieve greater control and use less chemical overall – and thus be more economical and environmentally friendly.

“Putting this information into the hands of a consultant will be more cost-effective, as they can fly multiple fields in a short time,” Bagavathiannan says.

“We started working on weed and crop species differentiation in 2015, and over the past two years, we’ve collected a good amount of preliminary data to be able to look at images and conduct analysis,” he adds.

The project is not without its challenges, though, Bagavathiannan notes.

“We have to be able to detect weeds when they are very small and treatable, and that is only achievable by flying very low or using very high-resolution cameras,” Singh says. “We have found the rotary-wing aircraft to be more useful than fixed-wing because they can hover at lower altitudes and perform agile maneuvering, which makes them well-suited for field inspections.”

For instance, he says the current cameras are able to achieve a pixel size of 2 centimeters, but a size of a few millimeters is ideal for capturing more details of the weed.

Singh says a simple RGB image analysis was sufficient to differentiate some weeds, such as morning glories, devil’s claw and cocklebur, which can be done based on color, shape and textural features. They are also using multispectral and hyperspectral imagery, both useful in distinguishing several species.

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