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Combination of Vegetation Indices and SIF Can Better Track Phenological Metrics and Gross Primary Production

文献类型：期刊论文

作者Zheng, Chen2,3,4,5; Wang, Shaoqiang2,4,6; Chen, Jing M.3,5; Chen, Jinghua2,4; Chen, Bin2,4; He, Xinlei7; Li, Hui6; Sun, Leigang1,8
刊名JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
出版日期2023-07-01
卷号128期号:7页码:20
ISSN号2169-8953
关键词vegetation indices (VIs) solar-induced chlorophyll fluorescence (SIF) the start of growing season (SOS) the end of growing season (EOS) the length of growing season (LOS) gross primary productivity (GPP)
DOI10.1029/2022JG007315
通讯作者Wang, Shaoqiang(sqwang@igsnrr.ac.cn)
英文摘要Accurate phenological extraction is important for estimating carbon uptake in terrestrial ecosystems under climate change. The emergence of remotely sensed vegetation indices (VIs) and solar-induced chlorophyll fluorescence (SIF) provides multiple approaches for extracting land surface phenology. However, there is lacking studies to track phenological metrics via multiple VIs and SIF. Therefore, the advantage of combining VIs and SIF to estimate more accurate phenology requires exploration. In this study, we combined the advantages of the normalized difference, enhanced, green-red, near-infrared reflectance vegetation indices from MCD43A4 data set, and SIF from CSIF data set to estimate hybrid phenology at 20 eddy flux sites in North America. Results showed that the hybrid phenology derived from the best-performing start (SOS) and end (EOS) of the growing season among multiple VIs and SIF for each plant functional type and site were both more consistent with those derived from gross primary production (GPP). Specifically, the R-2 of hybrid phenology increased by 0.11-0.4 (0.04-0.4) for SOS, 0.01-0.24 (0.09-0.22) for EOS, 0.01-0.7 (0.05-0.34) for the length of the growing season (LOS) based on Gaussian (logistic) method. Moreover, hybrid phenology can improve the explanation of the seasonal and annual variations in GPP. The explanatory power of hybrid phenology for GPP variations increased by 0.05-0.15 (0.02-0.23) for SOS, 0-0.36 (0.11-0.27) for EOS, 0.01-0.51 (0.03-0.4) for LOS, 0.04-0.18 (0.04-0.16) fo....r LOS x seasonal GPP maximum based on Gaussian (logistic) method. These findings highlight the potential of combining high-spatiotemporal structural and coarse-spatiotemporal physiological vegetation indicators in tracking phenology and GPP.
WOS关键词SOLAR-INDUCED FLUORESCENCE ; GREEN-UP DATE ; SPRING PHENOLOGY ; CHLOROPHYLL FLUORESCENCE ; USE EFFICIENCY ; SURFACE ; FOREST ; CLIMATE ; CANOPY ; NDVI
资助项目National Natural Science Foundation of China[41871342] ; Strategic Priority Research Program of the Chinese Academy of Sciences Grant[XDA23100202] ; Science and Technology Planning Project of Hebei Academy of Sciences, China[22A03]
WOS研究方向Environmental Sciences & Ecology ; Geology
语种英语
出版者AMER GEOPHYSICAL UNION
WOS记录号WOS:001047917100001
资助机构National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences Grant ; Science and Technology Planning Project of Hebei Academy of Sciences, China
源URL[http://ir.igsnrr.ac.cn/handle/311030/196890]  
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.Hebei Technol Innovat Ctr Geog Informat Applicat, Shijiazhuang, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Univ Toronto, Dept Geog, Toronto, ON, Canada
4.Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China
5.Univ Toronto, Program Planning, Toronto, ON, Canada
6.Chinese Univ Geosci Wuhan, Sch Geog & Informat Engn, Lab Reg Ecol Proc & Environm Change, Wuhan, Peoples R China
7.Beijing Normal Univ, Fac Geog Sci, Sch Nat Resources, State Key Lab Earth Surface Proc & Resource Ecol, Beijing, Peoples R China
8.Hebei Acad Sci, Inst Geog Sci, Shijiazhuang, Peoples R China
推荐引用方式
GB/T 7714		 Zheng, Chen,Wang, Shaoqiang,Chen, Jing M.,et al. Combination of Vegetation Indices and SIF Can Better Track Phenological Metrics and Gross Primary Production[J]. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,2023,128(7):20.
APA Zheng, Chen.,Wang, Shaoqiang.,Chen, Jing M..,Chen, Jinghua.,Chen, Bin.,...&Sun, Leigang.(2023).Combination of Vegetation Indices and SIF Can Better Track Phenological Metrics and Gross Primary Production.JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES,128(7),20.
MLA Zheng, Chen,et al."Combination of Vegetation Indices and SIF Can Better Track Phenological Metrics and Gross Primary Production".JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES 128.7(2023):20.

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来源：地理科学与资源研究所

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