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Stanford scientists locate nearly all U.S. solar panels by applying machine learning to a billion satellite images

aerial image of two-story houses in a neighborhood with solar panels on the roofs
Image credit: Getty Images
Dec 19 2018
Fellow, Research, Stanford, Students

Knowing which Americans have installed solar panels on their roofs and why they did so would be enormously useful for managing the changing U.S. electricity system and to understanding the barriers to greater use of renewable resources. But until now, all that has been available are essentially estimates.

To get accurate numbers, Stanford University scientists analyzed more than a billion high-resolution satellite images with a machine learning algorithm and identified nearly every solar power installation in the contiguous 48 states. The results are described in a paper published in the Dec. 19 issue of Joule. The data are publicly available on the project’s website.

The team includes Zhecheng Wang, a 2018 Stanford Interdisciplinary Graduate Fellow.

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