Leaf Area Index Retrieval Combining HJ1/CCD and Landsat8/OLI Data in the Heihe River Basin, China

	Leaf Area Index Retrieval Combining HJ1/CCD and Landsat8/OLI Data in the Heihe River Basin, China
	Zhao, Jing 1; Li, Jing 1; Liu, Qinhuo 1; Fan, Wenjie 1; Zhong, Bo 1; Wu, Shanlong 1; Yang, Le 1; Zeng, Yelu 1; Xu, Baodong 1; Yin, Gaofei 1
刊名	REMOTE SENSING
	2015
卷号	7 期号:6 页码:541-548
通讯作者	Li, J (reprint author), Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
英文摘要	The primary restriction on high resolution remote sensing data is the limit observation frequency. Using a network of multiple sensors is an efficient approach to increase the observations in a specific period. This study explores a leaf area index (LAI) inversion method based on a 30 m multi-sensor dataset generated from HJ1/CCD and Landsat8/OLI, from June to August 2013 in the middle reach of the Heihe River Basin, China. The characteristics of the multi-sensor dataset, including the percentage of valid observations, the distribution of observation angles and the variation between different sensor observations, were analyzed. To reduce the possible discrepancy between different satellite sensors on LAI inversion, a quality control system for the observations was designed. LAI is retrieved from the high quality of single-sensor observations based on a look-up table constructed by a unified model. The averaged LAI inversion over a 10-day period is set as the synthetic LAI value. The percentage of valid LAI inversions increases significantly from 6.4% to 49.7% for single-sensors to 75.9% for multi-sensors. LAI retrieved from the multi-sensor dataset show good agreement with the field measurements. The correlation coefficient (R-2) is 0.90, and the average root mean square error (RMSE) is 0.42. The network of multiple sensors with 30 m spatial resolution can generate LAI products with reasonable accuracy and meaningful temporal resolution.
研究领域[WOS]	Remote Sensing
收录类别	SCI ; EI
语种	英语
WOS记录号	WOS:000357589800015
内容类型	期刊论文
源URL	[http://ir.ceode.ac.cn/handle/183411/38183]
专题	遥感与数字地球研究所_SCI/EI期刊论文_期刊论文
作者单位	1.[Zhao, Jing 2.Li, Jing 3.Liu, Qinhuo 4.Zhong, Bo 5.Wu, Shanlong 6.Yang, Le 7.Zeng, Yelu 8.Xu, Baodong 9.Yin, Gaofei] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 10.[Zhao, Jing
推荐引用方式 GB/T 7714	Zhao, Jing,Li, Jing,Liu, Qinhuo,et al. Leaf Area Index Retrieval Combining HJ1/CCD and Landsat8/OLI Data in the Heihe River Basin, China[J]. REMOTE SENSING,2015,7(6):541-548.
APA	Zhao, Jing.,Li, Jing.,Liu, Qinhuo.,Fan, Wenjie.,Zhong, Bo.,...&Yin, Gaofei.(2015).Leaf Area Index Retrieval Combining HJ1/CCD and Landsat8/OLI Data in the Heihe River Basin, China.REMOTE SENSING,7(6),541-548.
MLA	Zhao, Jing,et al."Leaf Area Index Retrieval Combining HJ1/CCD and Landsat8/OLI Data in the Heihe River Basin, China".REMOTE SENSING 7.6(2015):541-548.