Energy Infrastructure Map of the World

Project Summary

A team of students led by researchers in the Energy Data Analytics Lab and the Sustainable Energy Transitions Initiative will develop machine learning techniques for automatically mapping global electricity infrastructure using satellite imagery. By identifying substations, transmission lines, and distribution lines, students will create and publish a training dataset that we will use to automate grid infrastructure geolocation. These data and techniques will empower researchers and policymakers to better understand who has grid-connected access to electricity, who is underserved, and how to most efficiently transition communities and countries towards sustainable electrification.

Themes and Categories
Contact
Paul Bendich
Mathematics
bendich@math.duke.edu

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