Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1088/1748-9326/ab65cc |
Radiance-based NIRv as a proxy for GPP of corn and soybean | |
Wu, Genghong1,2; Guan, Kaiyu1,2,3; Jiang, Chongya1,2; Peng, Bin1,3; Kimm, Hyungsuk1; Chen, Min4; Yang, Xi5; Wang, Sheng1,2; Suyker, Andrew E.6; Bernacchi, Carl J.2,7,8; Moore, Caitlin E.2,8; Zeng, Yelu9; Berry, Joseph A.9; Pilar Cendrero-Mateo, M.10 | |
2020-03-01 | |
发表期刊 | ENVIRONMENTAL RESEARCH LETTERS |
ISSN | 1748-9326 |
出版年 | 2020 |
卷号 | 15期号:3 |
文章类型 | Article |
语种 | 英语 |
国家 | USA; Spain |
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 (APAR(green)), 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. |
英文关键词 | photosynthesis gross primary production NIRv near-infrared radiance of vegetation |
领域 | 气候变化 |
收录类别 | SCI-E |
WOS记录号 | WOS:000537406500003 |
WOS关键词 | GROSS PRIMARY PRODUCTION ; LIGHT-USE EFFICIENCY ; INDUCED CHLOROPHYLL FLUORESCENCE ; PHOTOSYNTHETICALLY ACTIVE RADIATION ; ECOSYSTEM RESPIRATION ; RESOLUTION ; PRODUCTIVITY ; MODIS ; EXCHANGE ; LANDSAT |
WOS类目 | Environmental Sciences ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/279253 |
专题 | 气候变化 |
作者单位 | 1.Univ Illinois, Coll Agr Consumer & Environm Sci, Urbana, IL 61801 USA; 2.Univ Illinois, Ctr Adv Bioenergy & Bioprod Innovat, Urbana, IL 61801 USA; 3.Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA; 4.Pacific Northwest Natl Lab, Joint Global Change Res Inst, College Pk, MD USA; 5.Univ Virginia, Dept Environm Sci, Clark Hall, Charlottesville, VA 22903 USA; 6.Univ Nebraska Lincoln, Sch Nat Resources, Lincoln, NE USA; 7.USDA ARS, Global Change & Photosynth Res Unit, Urbana, IL USA; 8.Univ Illinois, Dept Plant Biol, Urbana, IL USA; 9.Carnegie Inst Sci, Dept Global Ecol, Stanford, CA USA; 10.Univ Valencia, Image Proc Lab, Lab Earth Observat, Valencia, Spain |
推荐引用方式 GB/T 7714 | Wu, Genghong,Guan, Kaiyu,Jiang, Chongya,et al. Radiance-based NIRv as a proxy for GPP of corn and soybean[J]. ENVIRONMENTAL RESEARCH LETTERS,2020,15(3). |
APA | Wu, Genghong.,Guan, Kaiyu.,Jiang, Chongya.,Peng, Bin.,Kimm, Hyungsuk.,...&Pilar Cendrero-Mateo, M..(2020).Radiance-based NIRv as a proxy for GPP of corn and soybean.ENVIRONMENTAL RESEARCH LETTERS,15(3). |
MLA | Wu, Genghong,et al."Radiance-based NIRv as a proxy for GPP of corn and soybean".ENVIRONMENTAL RESEARCH LETTERS 15.3(2020). |
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