Researchers from the University establish a new methodology to improve, from space and through machine learning, the observation and analysis of the terrestrial biosphere. This statistical approach will represent a significant advance in monitoring crops and carbon sinks, as well as in predicting floods and droughts. The work has been published in the journal Science Advances.
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Machine learning revolutionizes methods to quantify the terrestrial biosphere
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