Modeling winter wheat phenology and carbon dioxide fluxes at the ecosystem scale based on digital photography and eddy covariance data

CORC > 地理科学与资源研究所 > 中国科学院地理科学与资源研究所 > 生态系统研究网络观测与模拟重点实验室 > CERN水分分中心

	Modeling winter wheat phenology and carbon dioxide fluxes at the ecosystem scale based on digital photography and eddy covariance data
	Yu, GR
刊名	ECOLOGICAL INFORMATICS
	2013
卷号	18 页码:69-78
关键词	Digital camera Greenness index Phenological date Gross primary production Winter wheat
通讯作者	He, HL
英文摘要	Recent studies have shown that the greenness index derived from digital camera imagery has high spatial and temporal resolution. These findings indicate that it can not only provide a reasonable characterization of canopy seasonal variation but also make it possible to optimize ecological models. To examine this possibility, we evaluated the application of digital camera imagery for monitoring winter wheat phenology and modeling gross primary production (GPP). By combining the data for the green cover fraction and for GPP, we first compared 2 different indices (the ratio greenness index (green-to-red ratio, G/R) and the relative greenness index (green to sum value, G%)) extracted from digital images obtained repeatedly over time and confirmed that G/R was best suited for tracking canopy status. Second, the key phenological stages were estimated using a time series of G/R values. The mean difference between the observed phenological dates and the dates determined from field data was 33 days in 2011 and 4 days in 2012, suggesting that digital camera imagery can provide high-quality ground phenological data. Furthermore, we attempted to use the data (greenness index and meteorological data in 2011) to optimize a light use efficiency CLUE) model and to use the optimal parameters to simulate the daily GPP in 2012. A high correlation (R-2 = 0.90) was found between the values of LUE-based GPP and eddy covariance (EC) tower-based GPP, showing that the greenness index and meteorological data can be used to predict the daily GPP. This finding provides a new method for interpolating GPP data and an approach to the estimation of the temporal and spatial distributions of photosynthetic productivity. In this study, we expanded the potential use of the greenness index derived from digital camera imagery by combining it with the LUE model in an analysis of well-managed cropland. The successful application of digital camera imagery will improve our knowledge of ecosystem processes at the temporal and spatial levels.
收录类别	SCI
资助信息	National Natural Science Foundation of China 41071251；Chinese Academy of Sciences XDA05050600；Environmental Protection Public Welfare Industry Targeted Research Fund gyh5031103
公开日期	2014-01-20
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/28621]
专题	地理科学与资源研究所_生态系统研究网络观测与模拟重点实验室_CERN水分分中心
推荐引用方式 GB/T 7714	Yu, GR. Modeling winter wheat phenology and carbon dioxide fluxes at the ecosystem scale based on digital photography and eddy covariance data[J]. ECOLOGICAL INFORMATICS,2013,18:69-78.
APA	Yu, GR.(2013).Modeling winter wheat phenology and carbon dioxide fluxes at the ecosystem scale based on digital photography and eddy covariance data.ECOLOGICAL INFORMATICS,18,69-78.
MLA	Yu, GR."Modeling winter wheat phenology and carbon dioxide fluxes at the ecosystem scale based on digital photography and eddy covariance data".ECOLOGICAL INFORMATICS 18(2013):69-78.