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	Spectral invariant provides a practical modeling approach for future biophysical variable estimations
	Zeng, Yelu; Xu, Baodong; Yin, Gaofei; Wu, Shengbiao; Hu, Guoqing; Yan, Kai; Yang, Bin; Song, Wanjuan; Li, Jing
刊名	Remote Sensing
	2018
卷号	Vol.10 No.10
ISSN号	2072-4292
URL标识	查看原文
公开日期	[db:dc_date_available]
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/5469101
专题	湖南大学
作者单位	1.) Department of Global Ecology, Carnegie Institution for Science, Stanford 2.CA 3.94305, United States 4.State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences and Beijing Normal University, Beijing 5.100101, China 6.Macro Agriculture Research Institute, College of Resource and Environment, Huazhong Agricultural University, 7.Shizishan Street, Wuhan 8.430070, China 9.Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 10.610041, China
推荐引用方式 GB/T 7714	Zeng, Yelu,Xu, Baodong,Yin, Gaofei,et al. Spectral invariant provides a practical modeling approach for future biophysical variable estimations[J]. Remote Sensing,2018,Vol.10 No.10.
APA	Zeng, Yelu.,Xu, Baodong.,Yin, Gaofei.,Wu, Shengbiao.,Hu, Guoqing.,...&Li, Jing.(2018).Spectral invariant provides a practical modeling approach for future biophysical variable estimations.Remote Sensing,Vol.10 No.10.
MLA	Zeng, Yelu,et al."Spectral invariant provides a practical modeling approach for future biophysical variable estimations".Remote Sensing Vol.10 No.10(2018).

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