





This project has been built using the Zooniverse Project Builder but is not yet an official Zooniverse project. Queries and issues relating to this project directed at the Zooniverse Team may not receive any response.
You can do real research by clicking to get started here!
Chat with the research team and other volunteers!
Active stats provide information about currently active workflows and subjects.
Connect with the research team on Talk to learn more about this project!
Since 2006, THEMIS all-sky imagers have been capturing images of the night sky every three seconds at many different sites across North America. While the broad phenomena that lead to the aurora are well-understood, the smaller-scale shapes that are captured in these all-sky images and their connection to underlying magnetospheric processes are not. To enable large-scale machine learning and statistical studies of the aurora that may lead to a better understanding of auroral morphology, this project aims to classify all of these images into one of six categories: arc aurora, diffuse aurora, discrete aurora, cloudy, moon, or clear/no aurora.