For example, some fields are equipped with soil moisture sensors or cameras that detect changes in crop appearance, but there aren't enough sensors to provide accurate information. Satellites can monitor vegetation from space; however, the spatial and temporal resolutions of satellite images are often too large to accurately assist decision-making at the field scale.
"Based on remote sensing fusion technology and advanced modeling, we can help farmers get a fully scalable solution remotely," said Kaiyu Guan, project lead on the study. "It can potentially be a revolutionary technology for farmers, not only in the U.S., but also for smallholder farmers in developing countries."
With modern satellite technology and Guan's fusion model, data acquisition won't be a limiting factor in future precision irrigation products. But it's still important to define plant water stress appropriately, the researchers said.
Historically, irrigation decisions were based solely on measures of soil moisture. Recently, Guan's team called for the agricultural industry to redefine drought, based not on soil moisture alone, but also on interaction with atmospheric dryness.
"Managing water use is a major challenge for future water sustainability," said Bruce Hamilton, a program director in NSF's Directorate for Engineering. "This research will help meet that challenge."
Source : nsf.gov