NSSC OpenIR  > 空间科学部
Automatic extraction of gravity waves from all-sky airglow image based on machine learning
Lai, Chang1,2; Xu, Jiyao2; Yue, Jia3; Yuan, Wei2; Liu, Xiao4; Li, Wei1; Li, Qinzeng2
Department空间科学部
Source PublicationRemote Sensing
2019
Volume11Issue:13
DOI10.3390/rs11131516
ISSN2072-4292
Language英语
AbstractWith the development of ground-based all-sky airglow imager (ASAI) technology, a large amount of airglow image data needs to be processed for studying atmospheric gravity waves. We developed a program to automatically extract gravity wave patterns in the ASAI images. The auto-extraction program includes a classification model based on convolutional neural network (CNN) and an object detection model based on faster region-based convolutional neural network (Faster R-CNN). The classification model selects the images of clear nights from all ASAI raw images. The object detection model locates the region of wave patterns. Then, the wave parameters (horizontal wavelength, period, direction, etc.) can be calculated within the region of the wave patterns. Besides auto-extraction, we applied a wavelength check to remove the interference of wavelike mist near the imager. To validate the auto-extraction program, a case study was conducted on the images captured in 2014 at Linqu (36.2°N, 118.7°E), China. Compared to the result of the manual check, the auto-extraction recognized less (28.9% of manual result) wave-containing images due to the strict threshold, but the result shows the same seasonal variation as the references. The auto-extraction program applies a uniform criterion to avoid the accidental error in manual distinction of gravity waves and offers a reliable method to process large ASAI images for efficiently studying the climatology of atmospheric gravity waves. © 2019 by the authors.
Indexed BySCI ; EI
Citation statistics
Document Type期刊论文
Identifierhttp://ir.nssc.ac.cn/handle/122/7072
Collection空间科学部
Affiliation1.School of Science, Chongqing University of Posts and Telecommunications, Chongqing; 500000, China;
2.State Key Laboratory of SpaceWeather, Center for Space Science and Applied Research, Chinese Academy of Sciences, Beijing; 110000, China;
3.Atmospheric and Planetary Science, Hampton University, Hampton; VA; 23668, United States;
4.College of Mathematics and Information Science, Henan Normal University, Xinxiang; 453007, China
Recommended Citation
GB/T 7714
Lai, Chang,Xu, Jiyao,Yue, Jia,et al. Automatic extraction of gravity waves from all-sky airglow image based on machine learning[J]. Remote Sensing,2019,11(13).
APA Lai, Chang.,Xu, Jiyao.,Yue, Jia.,Yuan, Wei.,Liu, Xiao.,...&Li, Qinzeng.(2019).Automatic extraction of gravity waves from all-sky airglow image based on machine learning.Remote Sensing,11(13).
MLA Lai, Chang,et al."Automatic extraction of gravity waves from all-sky airglow image based on machine learning".Remote Sensing 11.13(2019).
Files in This Item:
File Name/Size DocType Version Access License
201913.pdf(6115KB)期刊论文出版稿开放获取CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Lai, Chang]'s Articles
[Xu, Jiyao]'s Articles
[Yue, Jia]'s Articles
Baidu academic
Similar articles in Baidu academic
[Lai, Chang]'s Articles
[Xu, Jiyao]'s Articles
[Yue, Jia]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Lai, Chang]'s Articles
[Xu, Jiyao]'s Articles
[Yue, Jia]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.