Result: Automated Identification of Auroral Luminosity Boundaries Using pyIntensityFeatures.
Further Information
Imagers that observe optical or ultraviolet emissions from the atmosphere are commonly used to identify and study ionospheric phenomena. These phenomena include the auroral oval, equatorial plasma bubbles, and traveling ionospheric disturbances. One difficulty with using imager observations is accurately and automatically retrieving locations of interest from these images. This article presents an automated method designed to identify auroral luminosity boundaries from space‐based imager data. This method was originally developed for the Imager for Magnetopause‐to‐Aurora Global Exploration (IMAGE) observations, but has been further adapted for use with a wider range of observations. This article discusses the updated boundary detection method, and demonstrates the process on two different satellite data sets. The updated detection method has been made publicly accessible through a new Python package, pyIntensityFeatures. Plain Language Summary: This article presents pyIntensityFeatures, a new Python package designed to identify the edges of the aurora (commonly referred to as the northern or southern lights) in images taken from a satellite. This new package builds on previous methods that were designed to find the edges of aurora when the images taken contained the entire auroral oval in one hemisphere. It has now been improved for more situations and applied to two different data sets. Key Points: Created a new Python tool for identifying auroral luminosity boundariespyIntensityFeatures is capable of handling incomplete auroral images and complex structuresDemonstrated the identification of auroral luminosity boundaries on two different satellite imagers [ABSTRACT FROM AUTHOR]
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