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... 

Navigate to item

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.

Navigate to item

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.

Navigate to item

Frozen secrets

How one geophysicist explores glaciers with radar.

Navigate to item

News related to data science

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.

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

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.

Navigate to Machine learning in geoscience: Riding a wave of progress

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.

Navigate to Building a ‘billion sensors’ earthquake observatory with optical fibers

Mapping the Corn Belt with satellites

Research by Stanford Earth's David Lobell and George Azzari shows how better mapping of farm fields with satellites can lead to new ways to measure and boost crop yields.
 

Navigate to Mapping the Corn Belt with satellites
maillinkedindouble carrot leftarrow leftdouble carrotplayerinstagramclosecarrotquotefacebooktwitterplusminussearchmenuarrowcloudclock