Satellite imagery is not a new concept; for years companies have been collecting and selling imagery. The more difficult part of the commercial imagery equation is the post-collection analysis. It takes smart engineering and effort to analyze imagery—to turn pixels into insights. Our newest customer, Descartes Labs, is an image analysis startup that’s doing just that.
The Descartes Labs team— spun out of Los Alamos National Laboratory in December 2014— built a platform that uses machine learning and computer vision technology to efficiently analyze satellite imagery.
Just recently Descartes Labs was able to predict quickly and accurately 2015 agricultural corn yields using satellite imagery. See the full project.
Fields of leafy green lettuce and other spring produce border Yuma International Airport. Yuma’s year-round warmth allows lettuce, broccoli, melons, dates, and citrus to flourish. Image: Planet Labs.
According to Descartes, our global, high-frequency imagery will help them refine their analysis for U.S. crops, and extend their analysis to “smaller sized commercial and subsistence farms in developing countries, where much of the world’s food supply is grown.” When compared to traditional surveying methods, timely satellite data can reduce the time and cost of large scale agricultural analysis.
Our CEO, Will Marshall, commented: “I’m very pleased to get our high frequency, global data set into the hands of Descartes Labs’ top-notch team of imagery experts and data scientists. They’ll help us pioneer fascinating new use cases.”
I know I speak for all at Planet when I say we’re excited to call Descartes Labs a partner and look forward to their brilliant work with our imagery.