| Issue |
J. Space Weather Space Clim.
Volume 5, 2015
Statistical Challenges in Solar Information Processing
|
|
|---|---|---|
| Article Number | A39 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/swsc/2015042 | |
| Published online | 23 December 2015 | |
- Aboudarham, J., I. Scholl, N. Fuller, et al. Automatic detection and tracking of filaments for a solar feature database. Ann. Geophys., 26, 243–248, 2008. [Google Scholar]
- Bernasconi, P.N., D.M. Rust, and D. Hakim. Advanced automated solar filament detection and characterization code: description, performance, and results. Sol. Phys., 228, 97–117, 2005. [Google Scholar]
- De Pontieu, B., A.M. Title, J.R. Lemen, G.D. Kushner, D.J. Akin, et al. The Interface Region Imaging Spectrograph (IRIS). Sol. Phys., 289, 2733–2779, 2014. [NASA ADS] [CrossRef] [Google Scholar]
- Freeland, S., R. Bentley, and P. Murdin. SolarSoft. Encyclopedia of Astronomy and Astrophysics, Bristol, IOP Publishing, 3390, 2000. [Google Scholar]
- Foullon, C., and E. Verwichte. Automated detection of EUV prominences. Sol. Phys., 234, 135–150, 2006. [NASA ADS] [CrossRef] [Google Scholar]
- Gaetz, T.J., and E.E. Salpeter. Line radiation from a hot, optically thin plasma – Collision strengths and emissivities. Astrophys. J. Suppl. Ser., 52, 155–168, 1983. [Google Scholar]
- Gao, J., H. Wang, and M. Zhou. Development of an automatic filament disappearance detection system. Sol. Phys., 205, 93–103, 2002. [NASA ADS] [CrossRef] [Google Scholar]
- Gissot, S.F., and J.-F. Hochedez. Multiscale optical flow probing of dynamics in solar EUV images. Algorithm, calibration, and first results. A&A, 464, 1107–1118, 2007. [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
- Gissot, S.F., J.-F. Hochedez, P. Chainais, and J.-P. Antoine. 3D Reconstruction from SECCHI-EUVI images using an optical-flow algorithm: method description and observation of an erupting filament. Sol. Phys., 252, 397–408, 2008. [NASA ADS] [CrossRef] [Google Scholar]
- Gopalswamy, N., M. Shimojo, W. Lu, S. Yashiro, K. Shibasaki, and R.A. Howard. Prominence eruptions and coronal mass ejection: a statistical study using microwave observations. Astrophys. J., 586, 562–578, 2003. [NASA ADS] [CrossRef] [Google Scholar]
- Gosling, J.T. The solar flare myth. J. Geophys. Res., 98, 18937–18950, 1993. [NASA ADS] [CrossRef] [Google Scholar]
- Hao, Q., C. Fang, and P.F. Chen. Developing an advanced automated method for solar filament recognition and its scientific application to a solar cycle of MLSO H# data. Sol. Phys., 286, 385–404, 2013. [CrossRef] [Google Scholar]
- Hurlburt, N., and S. Jaffey. A spectral optical flow method for determining velocities from digital imagery. Earth Space Science Informatics, 8, 959–965, 2015. [CrossRef] [Google Scholar]
- Hurlburt, N., M. Cheung, C. Schrijver, L. Chang, S. Freeland, et al. Heliophysics event knowledgebase for the Solar Dynamics Observatory (SDO) and beyond. Sol. Phys., 275, 67–78, 2012. [Google Scholar]
- Joshi, A.D., N. Srivastava, and S.K. Mathew. Automated detection of filaments and their disappearance using full-disc Hα images. Sol. Phys., 262, 425–436, 2010. [CrossRef] [Google Scholar]
- Kaiser, M.L., T.A. Kucera, J.M. Davila, O.C. St. Cyr, M. Guhathakurta, and E. Christian. The STEREO Mission: an Introduction. Space Sci. Rev., 136, 5–16, 2008. [NASA ADS] [CrossRef] [Google Scholar]
- Kosugi, T., K. Matsuzaki, T. Sakao, T. Shimizu, Y. Sone, et al. The Hinode (Solar-B) Mission: an overview. Sol. Phys., 243, 3–17, 2007. [NASA ADS] [CrossRef] [Google Scholar]
- Labrosse, N., S. Dalla, and S. Marshall. Automatic detection of limb prominences in 304 Å EUV images. Sol. Phys., 262, 449–460, 2010. [CrossRef] [Google Scholar]
- Lemen, J.R., A.M. Title, D.J. Akin, P.F. Boerner, C. Chou, et al. The Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO). Sol. Phys., 275, 17–40, 2012. [NASA ADS] [CrossRef] [Google Scholar]
- Munro, R.H., J.T. Gosling, E. Hildner, R.M. MacQueen, A.I. Poland, and C.L. Ross. The association of coronal mass ejection transients with other forms of solar activity. Sol. Phys., 61, 201–215, 1979. [Google Scholar]
- Priest, E.R. Solar Magneto-hydrodynamics, D. Reidel Pub. Co, Dordrecht, Holland, Boston, 1982. [Google Scholar]
- Qu, M., F.Y. Shih, J. Jing, and H. Wang. Automatic solar filament detection using image processing techniques. Sol. Phys., 228, 119–135, 2005. [Google Scholar]
- Scholl, I.F., and S.R. Habbal. Automatic detection and classification of coronal holes and filaments based on EUV and magnetogram observations of the solar disk. Sol. Phys., 248, 425–439, 2008. [NASA ADS] [CrossRef] [MathSciNet] [PubMed] [Google Scholar]
- Schuh, M.A., J.M. Banda, P.N. Bernasconi, R.A. Angryk, and P.C.H. Martens. A comparative evaluation of automated solar filament detection. Sol. Phys., 289, 2503–2524, 2014. [CrossRef] [Google Scholar]
- Shine, R.A., G.W. Simon, and N.E. Hurlburt. Supergranule and mesogranule evolution. Sol. Phys., 193, 313–331, 2000. [NASA ADS] [CrossRef] [Google Scholar]
- Tian, H., E.E. DeLuca, S.R. Cranmer, B. De Pontieu, H. Peter, et al. Prevalence of small-scale jets from the networks of the solar transition region and chromosphere. Science, 346, A1255711, 2014. [CrossRef] [Google Scholar]
- Title, A.M., and C.J. Schrijver. The Sun’s magnetic carpet. The Tenth Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun, 154, 345–357, 1998. [Google Scholar]
- Wang, Y., H. Cao, J. Chen, T. Zhang, S. Yu, H. Zheng, C. Shen, J. Zhang, and S. Wang. Solar Limb Prominence Catcher and Tracker (SLIPCAT): an automated system and its preliminary statistical results. Astrophys. J., 717, 973–986, 2010. [Google Scholar]
- Yan, X.-L., Z.-Q. Qu, and D.-F. Kong. Relationship between eruptions of active-region filaments and associated flares and coronal mass ejections. Monthly Notices of the Royal Astronomical Society, 414, 2803–2811, 2011. [CrossRef] [Google Scholar]
- Yuan, Y., F.Y. Shih, J. Jing, H. Wang, and J. Chae. Automatic solar filament segmentation and characterization. Sol. Phys., 272, 101–117, 2011. [NASA ADS] [CrossRef] [Google Scholar]
- Zharkova, V.V., and V. Schetinin. Filament recognition in solar images with the neural network technique. Sol. Phys., 228, 137–148, 2005. [Google Scholar]
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