An Integrated Solar Database (ISD) with Extended Spatiotemporal Querying Capabilities

This paper focuses on the problem of tracking solar phenomena by creating spatiotemporal trajectories from solar event detection reports. Though tracking of multiple objects in video sequences has seen much research and improvement in recent years, there has been relatively little focus on the domain of tracking solar phenomena (events). In this work, we improve on our previous endeavors by eliminating offline model training requirements and utilizing crowd-sourced human labels to evaluate our performance. We apply our method to the metadata of two solar event types spanning 4 yr of detection reports from the automated detection modules for the Solar Dynamics Observatory mission. We compare our results with those produced by the detection module for active regions and coronal holes by using a crowd-sourced trajectory database as the ground truth. We show that our results are as good as or better than the event-specific detection module for these two event types. This is especially promising because our tracking algorithm is a generalized module for all solar events, and not specific to a single event type, allowing it to be applied to other solar event types reported to the Heliophysics Event Knowledgebase that do not contain tracking information.

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An Integrated Solar Database (ISD) with Extended Spatiotemporal Querying Capabilities

Cited by 2 publications

References 5 publications

Parallel computation of magnetic field parameters from HMI active region patches

Parallel computation of magnetic field parameters from HMI active region patches

Tracking Solar Phenomena from the SDO

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