A University of Minnesota-led research team is using data-driven approaches to better understand the environmental and social impacts of climate change.
The U.S. National Science Foundation in 2010 awarded a $10-million Expeditions in Computing grant to the research team to address key challenges in climate change science. As part of a project, the team developed methods that use climate and ecosystem data from a range of sources to refine predictions and identify changes in the climate.
For example, the researchers built a system to monitor the dynamics of global surface water bodies using data from the U.S. National Aeronautics and Space Administration's Earth observation satellites. The system was able to identify a range of hydrological changes, from the meanderings of rivers to the reduction and growth of water bodies due to droughts, melting glaciers, and dam construction.
"These innovative approaches are helping to provide a new understanding of the complex nature of the Earth system and the mechanisms contributing to the adverse consequences of climate change," says University of Minnesota professor Vipin Kumar, who received the ACM SIGKDD Innovation Award in 2012. Kumar discussed some of the team's machine learning and data mining advances during a keynote speech at the 2016 ACM SIGIR Conference on Research and Development in Information Retrieval in Italy.
From National Science Foundation
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