Electric Transmission Infrastructure Satellite Imagery Dataset for Computer Vision

This dataset accompanies the paper, <b>GridTracer: Automatic Mapping of Power Grids using Deep Learning and Overhead Imagery</b>, found at https://arxiv.org/abs/2101.06390. Please see that link for more information (live link below in references).<b><br></b><b>Overview</b><b><br></b>This dataset contains fully annotated electric transmission and distribution infrastructure for approximately 264 km² of high resolution satellite and aerial imagery, spanning 7 cities and 2 countries across 5 continents. <br>This dataset was designed for training machine learning algorithms to automatically identify electricity infrastructure in satellite imagery; for those working on identifying the best pathways to electrification in low and middle income countries, and for researchers investigating domain adaptation for computer vision.<br><b><i>Additional information on this dataset is available in the Documentation.pdf file included in this dataset.</i></b><br><b>Data Sources</b><br>LINZ: Land Information New Zealand<br>USGS: United States Geological SurveySource of imagery tagged as from USGS: U.S. Geological Survey.