Visual Precision Agriculture

Jeff White, an associate professor in the Department of Soil Science at North Carolina State University (NCSU), hopes to make farming more cost-effective and environmentally sound in North Carolina and across the country, with help from the Renaissance Computing Institute (RENCI) and its visualization resources.
White studies site-specific nitrogen management in agricultural fields in collaboration with scientists from NCSU’s Department of Crop Science. Nitrogen, the main chemical used in agricultural fertilizers, is a mixed blessing. On the one hand, it can help farmers increase crop yields and profit. On the other, nitrogen fertilizers can leach into the groundwater, contaminate water supplies and enter surface waters and degrade their quality. High nitrate levels in well water, rivers, lakes, and streams can harm humans,  fish, and wildlife.

White’s research team is developing strategies for minimizing the amount of nitrogen that farmers use by pinpointing what areas need to be fertilized (and by how much) and what areas don’t. It is part of a growing agricultural research field called precision agriculture, which seeks to use agricultural pesticides and fertilizers more efficiently by applying them at appropriate rates when and where necessary to optimize productivity and profit. Precision agriculture practices are good for the environment and also for the farmer’s pocketbook, since expensive applications of fertilizers and pesticides are used more efficiently.

White’s research, funded by U.S. Department of Agriculture Initiative for Future Agricultural Systems grant no. 00-52103-9644, uses remote sensing in the form of aerial color-infrared photography to determine the nitrogen needs of wheat and corn and develop fertilizer application maps in geographic information systems (GIS) mapping software.  To assess the environmental consequences of the site-specific nitrogen management in comparison to traditional uniform nitrogen management, the researchers monitored groundwater nitrate levels in numerous wells installed in an experimental field. The process provided data that helped determine groundwater quality, how the different crops responded to site-specific management, and how and where nitrates concentrate over time.

White’s data was in the form of tables, graphs, maps, and spreadsheets until he connected with visualization specialists at RENCI at NC State, the RENCI engagement center on NC State’s Centennial campus. Several months ago, he began working with Jeff Heard, a RENCI senior data software developer at RENCI at NC State, to turn his research data into visual models. Steve Chall, a senior visualization software developer at the NC State center, has also joined the project.
“RENCI created a visualization, which we can view on a large tiled display wall, that shows very clearly the nitrate levels in the groundwater over time,” said White. “We can graphically view how groundwater nitrate concentrations change in conjunction with the rise and fall of the water table and see what is happening underground, which is something we couldn’t do just by looking at our data.”

The visualization wall at the RENCI engagement center allows White to observe changes in the nitrate levels in groundwater over time. He can stop the motion and move forward and backwards in time and he can easily observe the relationship between precipitation and the groundwater nitrate levels. The visual data is helpful not only to White and his research team; it could also be used to help farmers understand how nitrates behave in the soil and in groundwater and pinpoint problem areas in their fields.

“Nitrates can get into water supplies and surface waters, and the more we can control that, the better,” said White.
White and his research team gathered data for five years from a 30-acre test field at the Lower Coastal Plain Tobacco Research Station in Kinston, NC. Some plots received uniform applications of nitrogen—a common practice, which doesn’t take into account how much fertilizer might actually be needed. Other plots received site-specific applications, using the remote sensing data that monitored the nitrogen requirements of the crops.  Groundwater samples were taken as available from 0- to 12-feet deep from 60 wells in the field to measure the nitrate level in the groundwater. Water table depths were also determined.

Once RENCI at NCSU received White’s data, Heard worked to port it into a visual format in order to see the changes in the groundwater nitrate and water table levels over time beneath the field.

“This is an example of how the resources of RENCI—in this case our ability to visualize complicated datasets—can benefit a research team and help them solve important problems,” said Theresa Marie Rhyne, director of RENCI at NC State. “When researchers visualize their data, they are able to look at it in a much more dynamic and realistic way. Often, this new view of the data gives them new insights into its meaning.”

The next stage of the study for White and his team will be to continue collaborating with RENCI experts to run the visualization at different speeds and view it from different angles so the data can be better interpreted. For more information, see Jeff White’s homepage.