Evaluating Multi-Angle Photochemical Reflectance Index and Solar-Induced Fluorescence for the Estimation of Gross Primary Production in Maize

doi:10.3390/rs12172812

	Evaluating Multi-Angle Photochemical Reflectance Index and Solar-Induced Fluorescence for the Estimation of Gross Primary Production in Maize
	Chen, Jinghua 1,2; Zhang, Qian 3,4; Chen, Bin 1,2; Zhang, Yongguang 3; Ma, Li 1,2; Li, Zhaohui 3; Zhang, Xiaokang 3; Wu, Yunfei 3; Wang, Shaoqiang 1,2; Mickler, Robert A.5
刊名	REMOTE SENSING
	2020-09-01
卷号	12 期号:17 页码:16
关键词	vegetation photosynthesis light use efficiency model sun-view geometry temporal dynamics environmental variables
DOI	10.3390/rs12172812
通讯作者	Wang, Shaoqiang(sqwang@igsnrr.ac.cn)
英文摘要	The photochemical reflectance index (PRI) has been suggested as an indicator of light use efficiency (LUE), and for use in the improvement of estimating gross primary production (GPP) in LUE models. Over the last two decades, solar-induced fluorescence (SIF) observations from remote sensing have been used to evaluate the distribution of GPP over a range of spatial and temporal scales. However, both PRI and SIF observations have been decoupled from photosynthesis under a variety of non-physiological factors, i.e., sun-view geometry and environmental variables. These observations are important for estimating GPP but rarely reported in the literature. In our study, multi-angle PRI and SIF observations were obtained during the 2018 growing season in a maize field. We evaluated a PRI-based LUE model for estimating GPP, and compared it with the direct estimation of GPP using concurrent SIF measurements. Our results showed that the observed PRI varied with view angles and that the averaged PRI from the multi-angle observations exhibited better performance than the single-angle observed PRI for estimating LUE. The PRI-based LUE model when compared to SIF, demonstrated a higher ability to capture the diurnal dynamics of GPP (the coefficient of determination (R-2) = 0.71) than the seasonal changes (R-2= 0.44), while the seasonal GPP variations were better estimated by SIF (R-2= 0.50). Based on random forest analyses, relative humidity (RH) was the most important driver affecting diurnal GPP estimation using the PRI-based LUE model. The SIF-based linear model was most influenced by photosynthetically active radiation (PAR). The SIF-based linear model did not perform as well as the PRI-based LUE model under most environmental conditions, the exception being clear days (the ratio of direct and diffuse sky radiance > 2). Our study confirms the utility of multi-angle PRI observations in the estimation of GPP in LUE models and suggests that the effects of changing environmental conditions should be taken into account for accurately estimating GPP with PRI and SIF observations.
资助项目	National Key Research and Development Program of China[2017YFC0503803] ; National Natural Science Foundation of China[41571192] ; National Natural Science Foundation of China[41701393] ; Natural Science Foundation of Jiangsu Province for Youth[BK20170641] ; China Scholarship Council (CSC)[201906195015]
WOS关键词	LIGHT-USE EFFICIENCY ; INDUCED CHLOROPHYLL FLUORESCENCE ; PHOTOSYNTHETICALLY ACTIVE RADIATION ; SUN-INDUCED FLUORESCENCE ; HYPERSPECTRAL IMAGERY ; ECOSYSTEM PRODUCTION ; SENSITIVITY-ANALYSIS ; VEGETATION INDEXES ; PRI IMPLICATIONS ; SEASONAL-CHANGES
WOS研究方向	Remote Sensing
语种	英语
出版者	MDPI
WOS记录号	WOS:000569719200001
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; Natural Science Foundation of Jiangsu Province for Youth ; China Scholarship Council (CSC)
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/156929]
专题	中国科学院地理科学与资源研究所
通讯作者	Wang, Shaoqiang
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 3.Nanjing Univ, Sch Geog & Oceanog Sci, Int Inst Earth Syst Sci, Nanjing 210023, Peoples R China 4.Max Planck Inst Biogeochem, Hans Knoll Str 10, D-07745 Jena, Germany 5.North Carolina State Univ, Dept Forestry & Environm Resources, 2820 Faucette Dr, Raleigh, NC 27695 USA
推荐引用方式 GB/T 7714	Chen, Jinghua,Zhang, Qian,Chen, Bin,et al. Evaluating Multi-Angle Photochemical Reflectance Index and Solar-Induced Fluorescence for the Estimation of Gross Primary Production in Maize[J]. REMOTE SENSING,2020,12(17):16.
APA	Chen, Jinghua.,Zhang, Qian.,Chen, Bin.,Zhang, Yongguang.,Ma, Li.,...&Mickler, Robert A..(2020).Evaluating Multi-Angle Photochemical Reflectance Index and Solar-Induced Fluorescence for the Estimation of Gross Primary Production in Maize.REMOTE SENSING,12(17),16.
MLA	Chen, Jinghua,et al."Evaluating Multi-Angle Photochemical Reflectance Index and Solar-Induced Fluorescence for the Estimation of Gross Primary Production in Maize".REMOTE SENSING 12.17(2020):16.