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Thursday, April 11 • 4:05pm - 4:20pm
Mapping High-Voltage Infrastructure with Machine Learning + Humans

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Over 1.2 billion people around the world lack access to electricity. In developing nations, this problem is especially acute as it limits participation in modern economy and culture. Improving the electric grid, however, is often logistically challenging in these regions because there is rarely a complete and accurate map of the existing electric infrastructure. This map is crucial as there is no way to make informed decisions on how to spend resources to improve the electric grid without it.
Toward solving this problem, we built a pipeline to efficiently map the high-voltage (HV) grid at a country-wide scale. This pipeline relied on both machine learning (ML) and our Data Team -- a group of eight professional mappers. The ML component processed satellite imagery across an entire target country and returned geospatial locations likely to contain HV towers -- the tall metal structures that support HV lines running for hundreds or thousands of kilometers. Our Data Team then overlaid this information on top of satellite imagery and used it as a guide to help quicken their mapping of HV towers, lines, and substations. With this overlay, they could focus their attention on high priority areas and avoid the tedious task of reviewing entire countries worth of imagery by hand.

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avatar for Drew Bollinger

Drew Bollinger

Developer, Development Seed
Drew is a developer and data analyst at Development Seed. He has rich experience running advanced analysis and machine learning algorithms on large geospatial data sets. He is passionate about using powerful analysis and visualization techniques to promote social change. He is a firm... Read More →


Thursday April 11, 2019 4:05pm - 4:20pm EDT
Violet Crown: Theater 3 200 W Main St, Charlottesville, VA 22902, USA