It’s been 64 years since the Defense Department launched Transit, the world’s first global positioning satellite, allowing the Navy to track surface ships and submarines. Since then, the U.S., other countries, and private entities have launched hundreds of satellites that support everything from automatic guidance and variable-rate seeding to automatic sprayer shutoff. So it’s little wonder that farmers and researchers have irrigation scheduling, based on satellite images, in their sights.
“The trend toward the use of satellites to predict irrigation scheduling is definitely there,” says Andrew “Andy” French, a retired USDA/ARS research physical scientist, based in Arizona. “The obstacles have been … that the satellites haven’t been frequent enough in overpasses and they haven’t had the spatial resolution. A third obstacle is … that much of the country has more cloud cover than the western part of the U.S.”
French, who does research for the University of Arizona, believes those problems will be addressed within the next several years, as more satellites come online. “The cloud-cover problem will be addressed by a combination of more frequent, high-resolution [30-foot] images; improved crop water-use models using artificial intelligence; and, to some extent, the use of radar,” he says.
That solution may come sooner than later: India is poised to launch its NISAR satellite early next year. Developed in partnership with the U.S., the satellite will provide all-weather, day/night imaging of nearly all land masses on the Earth four to six times per month. Hydrosat, a climate tech company that uses satellite imagery and data analytics to measure water stress, has partnered with the climate satellite company Muon Space to launch a craft that will integrate thermal infrared (IR) imaging. This should further improve agricultural water-use efficiency.
Solutions Available Today
Farmers can use pre-existing satellite data to schedule irrigation amounts and frequency. The free website OpenET provides satellite-based evapotranspiration (ET) data for improved water management across the western United States.
Developed by a consortium of universities, NASA, Google Earth, the USDA/ARS, and others, the program relies entirely on publicly available data to measure patterns in land surface temperature, vegetation extent, and condition at individual-field scale. OpenET collects data from Landsat, Sentinel-2, GOES, and other satellites along with established ET models; weather station networks and models; and field boundary and crop-type datasets.
Unfortunately, ET data alone isn’t enough to schedule irrigation on most fields; it provides more history than prediction. In response, a growing number of companies are combining ET data with other factors to provide those schedules. For example, Godsey Precision Ag offers WaterCheck, part of the VariMax Platform that includes satellite-based nitrogen recommendations.
“We’ve really moved away from soil moisture probes for irrigation scheduling due to the cost and scalability,” says co-owner Chad Godsey, one of Water-Check’s developers.
“In contrast, satellite imagery does a better job of estimating the biomass or size of the crop vegetation, which directly affects transpiration. Satellites also give you a better snapshot of the whole field. We rely on our own source of satellite data and combine that with soil samples, local weather data, planting dates, crop type, and maturity, etc., to come up with a crop water algorithm.”
Though Godsey admits cloud cover can be an issue, he says their crop models are sufficiently accurate, with satellite images that are a week to 10 days old. In the meantime, customers need only look at their cell phones or computers for a water recommendation.
Learn More Visit openetdata.org.