In the past, agriculture mapping technology focused on appearances and taxonomy. Satellite and aerial data showed topographical features and the color of the topsoil hinted at the composition of what lay underneath. But appearances only run skin deep.
Purdue scientists have developed algorithms that account for how soil in specific locations interact with landscape features like streams and water catchments. These algorithms provide farmers with differences in soils and the minimum number of places required to properly sample field soil. Working from these patterns and soil samples, Dr. Phillip Owens and his team then produce maps with three-dimensional modelling.
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