A machine-learning-based cloud detection and thermodynamic-phaseclassification algorithm using passive spectral observations

GSTDTAP > 资源环境科学

DOI	10.5194/amt-13-2257-2020
	A machine-learning-based cloud detection and thermodynamic-phaseclassification algorithm using passive spectral observations
	admin
	2020-05-21
出版年	2020
国家	欧洲
领域	气候变化 ; 资源环境
英文摘要	A machine-learning (ML)-based approach that can be used for cloud mask and phase detection is developed. An all-day model that uses infrared (IR) observations and a daytime model that uses shortwave and IR observations from a passive instrument are trained separately for different surface types. The training datasets are selected by using reference pixel types from collocated space lidar. The ML approach is validated carefully and the overall performance is better than traditional methods.
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来源平台	European Geosciences Union
引用统计
文献类型	科技报告
条目标识符	http://119.78.100.173/C666/handle/2XK7JSWQ/274840
专题	资源环境科学气候变化
推荐引用方式 GB/T 7714	admin. A machine-learning-based cloud detection and thermodynamic-phaseclassification algorithm using passive spectral observations,2020.