Annales Geophysicae
Annales Geophysicae
ANGEO
Articles | Volume 37, issue 1
Articles | Volume 37, issue 1
https://doi.org/10.5194/angeo-37-77-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/angeo-37-77-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 37, issue 1
Regular paper
 | 
31 Jan 2019
Regular paper |  | 31 Jan 2019

Extending the coverage area of regional ionosphere maps using a support vector machine algorithm

Mingyu Kim and Jeongrae Kim

Viewed

Total article views: 3,848 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
2,892 859 97 3,848 108 172
  • HTML: 2,892
  • PDF: 859
  • XML: 97
  • Total: 3,848
  • BibTeX: 108
  • EndNote: 172
Views and downloads (calculated since 25 Sep 2018)
Cumulative views and downloads (calculated since 25 Sep 2018)

Viewed (geographical distribution)

Total article views: 3,848 (including HTML, PDF, and XML) Thereof 3,343 with geography defined and 505 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 03 Dec 2025
Download
Short summary
Spatial extrapolation of an ionosphere TEC map was carried out using a SVM learning algorithm. There has been much research on the temporal extrapolation or prediction of TEC time series, but the spatial extrapolation has rarely been attempted. Some researchers have performed simultaneous extrapolation both in time and in spatial domains, but this research covers the spatial extrapolation only by using an inner TEC map. This spatial TEC extrapolation can be useful for small countries.
Read more
Share