A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification
Aurora is a very important geophysical phenomenon in the high latitudes of Arctic and Antarctic regions, and it is important to make a comparative study of the auroral morphology between the two hemispheres. Based on the morphological characteristics of the four labeled dayside discrete auroral type...
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ftdoajarticles:oai:doaj.org/article:b3f53d769faf46148e92c05747394c26 2023-05-15T14:00:44+02:00 A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification Q. Yang Z.-J. Hu 2018-03-01T00:00:00Z https://doi.org/10.5194/gi-7-113-2018 https://doaj.org/article/b3f53d769faf46148e92c05747394c26 EN eng Copernicus Publications https://www.geosci-instrum-method-data-syst.net/7/113/2018/gi-7-113-2018.pdf https://doaj.org/toc/2193-0856 https://doaj.org/toc/2193-0864 doi:10.5194/gi-7-113-2018 2193-0856 2193-0864 https://doaj.org/article/b3f53d769faf46148e92c05747394c26 Geoscientific Instrumentation, Methods and Data Systems, Vol 7, Pp 113-122 (2018) Geophysics. Cosmic physics QC801-809 article 2018 ftdoajarticles https://doi.org/10.5194/gi-7-113-2018 2022-12-31T14:05:53Z Aurora is a very important geophysical phenomenon in the high latitudes of Arctic and Antarctic regions, and it is important to make a comparative study of the auroral morphology between the two hemispheres. Based on the morphological characteristics of the four labeled dayside discrete auroral types (auroral arc, drapery corona, radial corona and hot-spot aurora) on the 8001 dayside auroral images at the Chinese Arctic Yellow River Station in 2003, and by extracting the local binary pattern (LBP) features and using a k -nearest classifier, this paper performs an automatic classification of the 65 361 auroral images of the Chinese Arctic Yellow River Station during 2004–2009 and the 39 335 auroral images of the South Pole Station between 2003 and 2005. Finally, it obtains the occurrence distribution of the dayside auroral morphology in the Northern and Southern Hemisphere. The statistical results indicate that the four dayside discrete auroral types present a similar occurrence distribution between the two stations. To the best of our knowledge, we are the first to report statistical comparative results of dayside auroral morphology distribution between the Northern and Southern Hemisphere. Article in Journal/Newspaper Antarc* Antarctic Arctic South pole South pole Directory of Open Access Journals: DOAJ Articles Antarctic Arctic South Pole Geoscientific Instrumentation, Methods and Data Systems 7 1 113 122 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Geophysics. Cosmic physics QC801-809 |
spellingShingle |
Geophysics. Cosmic physics QC801-809 Q. Yang Z.-J. Hu A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification |
topic_facet |
Geophysics. Cosmic physics QC801-809 |
description |
Aurora is a very important geophysical phenomenon in the high latitudes of Arctic and Antarctic regions, and it is important to make a comparative study of the auroral morphology between the two hemispheres. Based on the morphological characteristics of the four labeled dayside discrete auroral types (auroral arc, drapery corona, radial corona and hot-spot aurora) on the 8001 dayside auroral images at the Chinese Arctic Yellow River Station in 2003, and by extracting the local binary pattern (LBP) features and using a k -nearest classifier, this paper performs an automatic classification of the 65 361 auroral images of the Chinese Arctic Yellow River Station during 2004–2009 and the 39 335 auroral images of the South Pole Station between 2003 and 2005. Finally, it obtains the occurrence distribution of the dayside auroral morphology in the Northern and Southern Hemisphere. The statistical results indicate that the four dayside discrete auroral types present a similar occurrence distribution between the two stations. To the best of our knowledge, we are the first to report statistical comparative results of dayside auroral morphology distribution between the Northern and Southern Hemisphere. |
format |
Article in Journal/Newspaper |
author |
Q. Yang Z.-J. Hu |
author_facet |
Q. Yang Z.-J. Hu |
author_sort |
Q. Yang |
title |
A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification |
title_short |
A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification |
title_full |
A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification |
title_fullStr |
A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification |
title_full_unstemmed |
A comparative study of auroral morphology distribution between the Northern and Southern Hemisphere based on automatic classification |
title_sort |
comparative study of auroral morphology distribution between the northern and southern hemisphere based on automatic classification |
publisher |
Copernicus Publications |
publishDate |
2018 |
url |
https://doi.org/10.5194/gi-7-113-2018 https://doaj.org/article/b3f53d769faf46148e92c05747394c26 |
geographic |
Antarctic Arctic South Pole |
geographic_facet |
Antarctic Arctic South Pole |
genre |
Antarc* Antarctic Arctic South pole South pole |
genre_facet |
Antarc* Antarctic Arctic South pole South pole |
op_source |
Geoscientific Instrumentation, Methods and Data Systems, Vol 7, Pp 113-122 (2018) |
op_relation |
https://www.geosci-instrum-method-data-syst.net/7/113/2018/gi-7-113-2018.pdf https://doaj.org/toc/2193-0856 https://doaj.org/toc/2193-0864 doi:10.5194/gi-7-113-2018 2193-0856 2193-0864 https://doaj.org/article/b3f53d769faf46148e92c05747394c26 |
op_doi |
https://doi.org/10.5194/gi-7-113-2018 |
container_title |
Geoscientific Instrumentation, Methods and Data Systems |
container_volume |
7 |
container_issue |
1 |
container_start_page |
113 |
op_container_end_page |
122 |
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1766270078386438144 |