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DOI10.1016/j.rse.2020.111686
The potential of satellite FPAR product for GPP estimation: An indirect evaluation using solar-induced chlorophyll fluorescence
Zhang Z.; Zhang Y.; Zhang Y.; Gobron N.; Frankenberg C.; Wang S.; Li Z.
发表日期2020
ISSN00344257
卷号240
英文摘要Satellite remotely sensed fraction of photosynthetically active radiation (FPAR) products are widely used in land-surface monitoring and modeling, especially for estimating global terrestrial photosynthetic activity through light use efficiency (LUE) models. PAR absorbed by active chlorophyll (APARchl) is directly linked to vegetation photosynthesis and can be used to estimate ecosystem gross primary production (GPP). Previous studies have demonstrated that solar induced chlorophyll fluorescence has very tight relationship with APARchl at various ecosystems. Therefore, the solar angle normalized SIF (nSIF) is directly related to the fraction of PAR absorbed by chlorophyll (FPARchl). This paper intercompared six space FPAR products from Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), Copernicus Global Land Service (CGLS), Multi-angle Imaging SpectroRadiometer (MISR), Earth Polychromatic Imaging Camera (EPIC) and Ocean and Land Colour Instrument (OLCI). Their potential relationships with FPARchl were indirectly evaluated with both spaceborne (Orbiting Carbon Observatory-2, OCO-2 and TROPOspheric Monitoring Instrument, TROPOMI) and airborne (Chlorophyll Fluorescence Imaging Spectrometer, CFIS) nSIF data as well as in situ GPP measurements. Our results show that these FPAR products are different in terms of amplitudes and seasonal variations across biomes. Among six FPAR products, OLCI FPAR shows the best relationships with TROPOMI nSIF740, OCO-2 nSIF757, and CFIS nSIF755. The coefficient of determination (R2) for the relationship between OLCI FPAR and TROPOMI nSIF740 is 0.79 ± 0.17 on a global average. APAR calculated from OLCI also exhibits the best relationship (R2 = 0.79) with in situ GPP over 25 flux towers. © 2020 Elsevier Inc.
英文关键词CGLS; EPIC; FPAR; FPARchl; MISR; MODIS; OLCI; SIF; VIIRS
语种英语
scopus关键词Chlorophyll; Earth (planet); Ecosystems; Orbits; Radiometers; Spectrometers; Thermography (imaging); CGLS; EPIC; FPAR; FPARchl; MISR; MODIS; OLCI; VIIRS; Fluorescence imaging; chlorophyll; light use efficiency; MODIS; OCO; photosynthesis; photosynthetically active radiation; primary production; satellite data; VIIRS
来源期刊Remote Sensing of Environment
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/179428
作者单位Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources, School of Geography and Ocean Science, Nanjing University, Nanjing, Jiangsu 210023, China; International Institute for Earth System Sciences, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Nanjing, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China; Climate and Ecosystem Science Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, United States; European Commission, Joint Research Centre, Via Enrico Fermi, Ispra, VA 2749 21027, Italy; Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, United States
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Zhang Z.,Zhang Y.,Zhang Y.,et al. The potential of satellite FPAR product for GPP estimation: An indirect evaluation using solar-induced chlorophyll fluorescence[J],2020,240.
APA Zhang Z..,Zhang Y..,Zhang Y..,Gobron N..,Frankenberg C..,...&Li Z..(2020).The potential of satellite FPAR product for GPP estimation: An indirect evaluation using solar-induced chlorophyll fluorescence.Remote Sensing of Environment,240.
MLA Zhang Z.,et al."The potential of satellite FPAR product for GPP estimation: An indirect evaluation using solar-induced chlorophyll fluorescence".Remote Sensing of Environment 240(2020).
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