气候变化领域集成服务门户(CCPortal): Radiance-based NIRv as a proxy for GPP of corn and soybean

CCPortal

DOI	10.1088/1748-9326/ab65cc
	Radiance-based NIRv as a proxy for GPP of corn and soybean
	Wu G.; Guan K.; Jiang C.; Peng B.; Kimm H.; Chen M.; Yang X.; Wang S.; Suyker A.E.; Bernacchi C.J.; Moore C.E.; Zeng Y.; Berry J.A.; Cendrero-Mateo M.P.
发表日期	2020
ISSN	17489318
卷号	15 期号:3
英文摘要	Substantial uncertainty exists in daily and sub-daily gross primary production (GPP) estimation, which dampens accurate monitoring of the global carbon cycle. Here we find that near-infrared radiance of vegetation (NIRv,Rad), defined as the product of observed NIR radiance and normalized difference vegetation index, can accurately estimate corn and soybean GPP at daily and half-hourly time scales, benchmarked with multi-year tower-based GPP at three sites with different environmental and irrigation conditions. Overall, NIRv,Rad explains 84% and 78% variations of half-hourly GPP for corn and soybean, respectively, outperforming NIR reflectance of vegetation (NIRv,Ref), enhanced vegetation index (EVI), and far-red solar-induced fluorescence (SIF760). The strong linear relationship between NIRv,Rad and absorbed photosynthetically active radiation by green leaves (APARgreen), and that between APARgreen and GPP, explain the good NIRv,Rad-GPP relationship. The NIRv,Rad-GPP relationship is robust and consistent across sites. The scalability and simplicity of NIRv,Rad indicate a great potential to estimate daily or sub-daily GPP from high-resolution and/or long-term satellite remote sensing data. © 2020 The Author(s). Published by IOP Publishing Ltd.
英文关键词	gross primary production; near-infrared radiance of vegetation; NIRv; photosynthesis
语种	英语
scopus关键词	Photosynthesis; Remote sensing; Vegetation; Enhanced vegetation index; Gross primary production; Near Infrared; NIRv; Normalized difference vegetation index; Photosynthetically active radiation; Satellite remote sensing data; Solar-induced fluorescences; Infrared devices; carbon cycle; maize; near infrared; photosynthesis; photosynthetically active radiation; primary production; radiance; remote sensing; satellite data; soybean; uncertainty analysis; Glycine max; Zea mays
来源期刊	Environmental Research Letters
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/154156
作者单位	College of Agricultural, Consumer and Environmental Sciences, University of Illinois at Urbana Champaign, Urbana, Illinois, United States; Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana Champaign, Urbana, Illinois, United States; National Center of Supercomputing Applications, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States; Joint Global Change Research Institute, Pacific Northwest National Laboratory, College Park, Maryland, United States; Department of Environmental Sciences, University of Virginia, Charlottesville, Virginia, United States; School of Natural Resources, University of Nebraska-Lincoln, Lincoln, Nebraska, United States; Global Change and Photosynthesis Research Unit, USDA-ARS, Urbana, Illinois, United States; Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States; Department of Global Ecology, Carnegie Institution for Science, Stanford, California, United States; Labora...
推荐引用方式 GB/T 7714	Wu G.,Guan K.,Jiang C.,et al. Radiance-based NIRv as a proxy for GPP of corn and soybean[J],2020,15(3).
APA	Wu G..,Guan K..,Jiang C..,Peng B..,Kimm H..,...&Cendrero-Mateo M.P..(2020).Radiance-based NIRv as a proxy for GPP of corn and soybean.Environmental Research Letters,15(3).
MLA	Wu G.,et al."Radiance-based NIRv as a proxy for GPP of corn and soybean".Environmental Research Letters 15.3(2020).