Assessment of LiDAR-Based Atmospheric Observations Using YOLOv9 for Sky Image Recognition

doi:10.1109/JSEN.2024.3491303

	Assessment of LiDAR-Based Atmospheric Observations Using YOLOv9 for Sky Image Recognition
	Xu, Long 1,2; Lin, Xin 3; Liu, Linmei 3; Wang, Jiqin 3; Lin, Xingkui4 ; Bai, Chunhai4 ; Lin, Zhaoxiang 5; Wang, Wei 3; Yang, Yong 3; Cheng, Xuewu 3; Li, Faquan 3
	2025
Source Publication	IEEE SENSORS JOURNAL
ISSN	1530-437X
Volume	25 Issue:1 Pages:1825-1838
Contribution Rank	3
Abstract	This study introduces an innovative method to improve the quality and accuracy of LiDAR observation data using YOLOv9 image recognition technology. By correlating daytime cloud image grayscale values and nighttime sky star counts with LiDAR data, this method provides a robust solution for all-weather observations. Experimental results show that this technique can accurately predict LiDAR data quality under various environmental conditions, offering a valuable tool for atmospheric science research and meteorological monitoring.
Keyword	Atmospheric modeling Laser radar Clouds Accuracy Meteorology Data models Atmospheric measurements Stars Predictive models Image recognition Atmospheric detection data quality assessment environmental monitoring image recognition LiDAR YOLOv9
DOI	10.1109/JSEN.2024.3491303
Indexed By	SCI
Language	英语
WOS Keyword	105 KM ALTITUDE
Funding Project	National Natural Science Foundation of China[42305152] ; National Key Research and Development Program of China[2022YFC2807201] ; Chinese Meridian Project(CMP)
WOS Research Area	Engineering ; Instruments & Instrumentation ; Physics
WOS Subject	Engineering, Electrical & Electronic ; Instruments & Instrumentation ; Physics, Applied
WOS ID	WOS:001389581900005
Publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Funding Organization	National Natural Science Foundation of China ; National Key Research and Development Program of China ; Chinese Meridian Project(CMP)
Citation statistics	Cited Times:1[WOS] [WOS Record] [Related Records in WOS]
Document Type	期刊论文
Identifier	http://ir.xao.ac.cn/handle/45760611-7/7363
Collection	光学天文与技术应用研究室_光学天文技术研究团组
Corresponding Author	Lin, Xin
Affiliation	1.Univ Chinese Acad Sci, Innovat Acad Precis Measurement Sci & Technol, Beijing 101408, Peoples R China 2.Chinese Acad Sci, Innovat Acad Precis Measurement Sci & Technol, Wuhan 100049, Peoples R China 3.Chinese Acad Sci, Innovat Acad Precis Measurement Sci & Technol, Wuhan 100864, Peoples R China 4.Chinese Acad Sci, Xinjiang Astron Observ, Xinjiang 830011, Peoples R China 5.South Cent Minzu Univ, Coll Elect & Informat Engn, Hubei Key Lab Intelligent Wireless Commun, Wuhan 430074, Peoples R China
Recommended Citation GB/T 7714	Xu, Long,Lin, Xin,Liu, Linmei,et al. Assessment of LiDAR-Based Atmospheric Observations Using YOLOv9 for Sky Image Recognition[J]. IEEE SENSORS JOURNAL,2025,25(1):1825-1838.
APA	Xu, Long.,Lin, Xin.,Liu, Linmei.,Wang, Jiqin.,Lin, Xingkui.,...&Li, Faquan.(2025).Assessment of LiDAR-Based Atmospheric Observations Using YOLOv9 for Sky Image Recognition.IEEE SENSORS JOURNAL,25(1),1825-1838.
MLA	Xu, Long,et al."Assessment of LiDAR-Based Atmospheric Observations Using YOLOv9 for Sky Image Recognition".IEEE SENSORS JOURNAL 25.1(2025):1825-1838.

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