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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
Source PublicationRemote Sensing
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
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Document Type期刊论文
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).
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