Automatic extraction of gravity waves from all-sky airglow image based on machine learning

doi:10.3390/rs11131516

	Automatic extraction of gravity waves from all-sky airglow image based on machine learning
	Lai, Chang 1,2; Xu, Jiyao 2; Yue, Jia 3; Yuan, Wei 2; Liu, Xiao 4; Li, Wei 1; Li, Qinzeng 2
刊名	Remote Sensing
	2019
卷号	11 期号:13
ISSN号	2072-4292
DOI	10.3390/rs11131516
英文摘要	With 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.
语种	英语
内容类型	期刊论文
源URL	[http://ir.nssc.ac.cn/handle/122/7072]
专题	国家空间科学中心_空间科学部
作者单位	1.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
推荐引用方式 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).