Descartes Labs, the Los Alamos, N.M.-based startup that used satellite imagery to analyze crop conditions and project yields last summer, just raised another $5 million in investor funding to grow its business.
In a statement, Descartes CEO Mark Johnson said he and his colleagues planned to continue their emphasis on agriculture in their satellite imagery collection and analysis business.
“Why ag? Global agriculture is a trillion dollar business that is absolutely essential to the lives of all 7 billion of us living on this planet,” Johnson explained. “Human agriculture is visible from space, but traditional methods of understanding and forecasting agriculture are mostly stuck in the last century, based on paper surveys of farmers and visits to crops growing in the fields. Since the dawn of the United States, mechanization and biotechnology have multiplied the productivity of the American farm by an enormous factor, and the new frontier in this technological revolution is information.”
Descartes sees its work as a faster, more high-tech, and—it asserts—more accurate alternative to the USDA data collected through the traditional NASS farmer surveys.
The startup also sees plenty of potential for the information and insights provided through such a high-tech approach.
“By looking at this massive amount of data, instead of looking at a small sample of farms via surveys and visits, we’re able to observe and measure every farm in the world every day,” Johnson said. “What’s even more impressive about this approach is that besides being more accurate than traditional methods, we are adding a level of granularity such that we can measure the yield of an individual field. This opens up a whole new set of data-driven applications, from helping farm operators optimize their production, to helping insurance companies cover losses, to helping the supply-chain companies trade, store and move the crops to local and far-flung markets.”
What do you think about using satellite imagery to measure crop conditions and estimate production? Do you see this as a more or less accurate method than USDA’s approach? Let us know in the comments.