Stanford University

Using Data Science to Understand Earth

We finally have the tools to explore earth in its real complexity

Data has become cheaper, faster, and more central to analyzing the broad scope of work carried out by Earth scientists than ever before. Beginning with data acquisition, and on to processing, modeling, and analysis, advanced computing techniques are a core skill practiced by students and faculty. "These are skills in high demand across many disciplines and jobs today," says senior associate dean Margot Gerritsen.  

Today's Earth science is data driven

The satellite and supercomputer are the tools of modern geoscientists whose research spans from climate change projections and earthquake simulations to energy resources optimization. They investigate causes of drought, design defenses against natural disasters, and blaze a path toward a renewable energy future. 

Stanford Earth scientists are as likely to be found in front of an electronic screen, analyzing torrents of remote-sensing data with algorithms or simulating nature with computer models, as they are to be drilling ice cores in Antarctica or gathering soil samples from mountains in Mongolia. Read on... 

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Computational Geoscience Program

A graduate degree track within the Institute of Computational and Mathematical Engineering that provides students with the skills to develop numerical solutions to Earth science problems.

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Stanford Geospatial Center

The Stanford Geospatial Center, housed in Branner library, offers workshops on fundamentals of GIS, data management, data visualization tools, and spatial analysis.

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Frozen secrets

How one geophysicist explores glaciers with radar.

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News related to data science

Outstanding research by outstanding women

Women in Data Science (WiDS) and Stanford Earth hosted a symposium to highlight the research done by women who use data science to assess a range of topics in the geosciences, including Earth processes, hazards, climate, and sustainability.

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Can a drone reveal the murky secrets of San Francisco Bay?

Measurements of suspended sediment concentrations reveal a lot about the health of a waterway, but until now such data has been difficult to obtain.

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Machine learning in geoscience: Riding a wave of progress

Greg Beroza writes about how machine learning offers a new way to use massive amounts of geoscience data to tackle complex, unsolved problems in the context of a March 2019 conference he helped organize.

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Building a ‘billion sensors’ earthquake observatory with optical fibers

The same optical fibers that deliver high-speed internet and HD video to our homes could one day double as seismic sensors for monitoring and studying earthquakes.

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