J. Space Weather Space Clim.
Volume 6, 2016
Statistical Challenges in Solar Information Processing
|Number of page(s)||19|
|Published online||25 January 2016|
Image patch analysis of sunspots and active regions
II. Clustering via matrix factorization
Electrical Engineering and Computer Science Department, University of Michigan, Ann Arbor, MI 48109, USA
2 SIDC, Royal Observatory of Belgium, 1180 Brussels, Belgium
3 National Solar Observatory, CO 80303, Boulder, USA
* Corresponding author: firstname.lastname@example.org
Accepted: 10 December 2015
Context. Separating active regions that are quiet from potentially eruptive ones is a key issue in Space Weather applications. Traditional classification schemes such as Mount Wilson and McIntosh have been effective in relating an active region large scale magnetic configuration to its ability to produce eruptive events. However, their qualitative nature prevents systematic studies of an active region’s evolution for example.
Aims. We introduce a new clustering of active regions that is based on the local geometry observed in Line of Sight magnetogram and continuum images.
Methods. We use a reduced-dimension representation of an active region that is obtained by factoring the corresponding data matrix comprised of local image patches. Two factorizations can be compared via the definition of appropriate metrics on the resulting factors. The distances obtained from these metrics are then used to cluster the active regions.
Results. We find that these metrics result in natural clusterings of active regions. The clusterings are related to large scale descriptors of an active region such as its size, its local magnetic field distribution, and its complexity as measured by the Mount Wilson classification scheme. We also find that including data focused on the neutral line of an active region can result in an increased correspondence between our clustering results and other active region descriptors such as the Mount Wilson classifications and the R-value.
Conclusions. Matrix factorization of image patches is a promising new way of characterizing active regions. We provide some recommendations for which metrics, matrix factorization techniques, and regions of interest to use to study active regions.
Key words: Sun / Active region / Sunspot / Neutral line / Data analysis / Classification / Clustering / Image patches / Hellinger distance / Grassmannian
© K.R. Moon et al., Published by EDP Sciences 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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