Planet’s archive, according to Maples, dates back to 2009, which also provides students and researchers with historical context to leverage. “The addition of Planet data to the Libraries’ catalog of resources will offer faculty and students new tools to support the cutting-edge research being done across a variety of disciplines to address urgent global issues,” said Stace Maples, geospatial manager at Stanford Libraries. “We're excited to test Planet data on some long-standing problems where coarser sensors have struggled, such as tracking economic activity in remote areas, or measuring cropping diversity in tropical agriculture,” said Lobell.Ĭombining machine learning and Planet imagery, the Stanford-based Natural Capital Project-a partnership between the Chinese Academy of Sciences, the University of Minnesota, the Stockholm Resilience Centre, The Nature Conservancy, and the World Wildlife Fund-is developing an algorithm for detecting and mapping dams globally. There are estimated to be over 16 million dams worldwide, with only a small fraction documented. Lobell and Marshall Burke, assistant professor of Earth System Science, are interested in using Planet imagery to run predictive modeling around food security and sustainability, at continental scales. “Planet offers an unprecedented combination of fine spatial resolution and temporal frequency,” said David Lobell, the Gloria and Richard Kushel Director of FSE and professor of Earth System Science at Stanford. Planet’s imagery can be used across several disciplines and has countless commercial and humanitarian applications-including agriculture, energy and infrastructure, the environment, and more. With the world's largest constellation of Earth-imaging satellites in orbit, the new Planet subscription provides students, faculty and scholars with access to daily high-resolution images of Earth’s lands and oceans. Stanford, CA- Stanford Libraries, with support from the Natural Capital Project and The Center on Food Security and the Environment (FSE), has entered into an agreement with Planet, a San Francisco based aerospace and data analytics company, to provide subscription access to their analysis-ready images. The Planet catalog of images join other large datasets, including CoreLogic and Schrodinger, available to the Stanford community courtesy of the Libraries. Stanford Libraries is one of the first academic institutions to add Planet’s dataset to its list of resources.

Earth imagery