Solar thematic maps for space weather operations

Citations of this article
Mendeley users who have this article in their library.

This artice is free to access.


Thematic maps are arrays of labels, or "themes," associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high-cadence, high-resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next-generation GOES-R series of satellites starting ∼2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions. © 2012. American Geophysical Union. All Rights Reserved.




Rigler, E. J., Hill, S. M., Reinard, A. A., & Steenburgh, R. A. (2012). Solar thematic maps for space weather operations. Space Weather, 10(8).

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free