气候变化领域集成服务门户(CCPortal): Ground-Based Cloud Classification Using Task-Based Graph Convolutional Network

CCPortal

DOI	10.1029/2020GL087338
	Ground-Based Cloud Classification Using Task-Based Graph Convolutional Network
	Liu S.; Li M.; Zhang Z.; Cao X.; Durrani T.S.
发表日期	2020
ISSN	0094-8276
卷号	47 期号:5
英文摘要	Clouds play a significant role in weather forecasts, water cycle, and climate system. However, existing methods ignore the relations of ground-based cloud images. In this letter, we propose a novel method named task-based graph convolutional network (TGCN) for ground-based cloud classification, which takes image relations into consideration. To this end, we construct the graph using convolutional neural network-based features of ground-based cloud images which are learned in a supervised manner, and incorporate the graph computation into TGCN. Given that existing ground-based cloud databases are with limited labeled training images and categorized according to different classification criteria, we release the largest ground-based remote sensing cloud database (GRSCD) to provide a comparative study for different methods and to further improve the study of regional sky conditions. The experimental results on GRSCD manifest the effectiveness of TGCN for ground-based cloud classification. ©2020. American Geophysical Union. All Rights Reserved.
英文关键词	Classification (of information); Convolution; Image enhancement; Remote sensing; Weather forecasting; Classification criterion; Climate system; Cloud classification; Cloud database; Comparative studies; Convolutional networks; Ground-based remote sensing; Training image; Convolutional neural networks; artificial neural network; cloud classification; comparative study; database; deconvolution; remote sensing; supervised classification
语种	英语
来源期刊	Geophysical Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/170602
作者单位	Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, Tianjin, China; Meteorological Observation Centre, China Meteorological Administration, Beijing, China; Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, United Kingdom
推荐引用方式 GB/T 7714	Liu S.,Li M.,Zhang Z.,et al. Ground-Based Cloud Classification Using Task-Based Graph Convolutional Network[J],2020,47(5).
APA	Liu S.,Li M.,Zhang Z.,Cao X.,&Durrani T.S..(2020).Ground-Based Cloud Classification Using Task-Based Graph Convolutional Network.Geophysical Research Letters,47(5).
MLA	Liu S.,et al."Ground-Based Cloud Classification Using Task-Based Graph Convolutional Network".Geophysical Research Letters 47.5(2020).