Solar thematic maps for space weather operations
Space Weather
By: E. Joshua Rigler, Steven M. Hill, Alysha A. Reinard, and Robert A. Steenburgh
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Abstract
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.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Solar thematic maps for space weather operations |
| Series title | Space Weather |
| DOI | 10.1029/2012SW000780 |
| Volume | 10 |
| Year Published | 2012 |
| Language | English |
| Publisher | American Geophysical Union |
| Contributing office(s) | Geologic Hazards Science Center |
| Description | S08009, 16 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Space Weather |
| Country | United States |
| Google Analytic Metrics | Metrics page |