中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 地理科学与资源研究所
  3. 中国科学院地理科学与资源研究所
  4. 生态系统研究网络观测与模拟重点实验室
  5. 外文论文
Estimating global transpiration from TROPOMI SIF with angular normalization and separation for sunlit and shaded leaves

文献类型：期刊论文

作者Zheng, Chen5,6,7; Wang, Shaoqiang4,6,7; Chen, Jing M.5; Xiao, Jingfeng3; Chen, Jinghua6,7; Zhang, Zhaoying2; Forzieri, Giovanni1
刊名REMOTE SENSING OF ENVIRONMENT
出版日期2025-03-15
卷号319页码:114586
关键词Angular normalization Transpiration Sunlit and shaded SIF Hybrid model TROPOMI SIF
ISSN号0034-4257
DOI10.1016/j.rse.2024.114586
产权排序1
文献子类Article
英文摘要Gross primary productivity (GPP) is more accurately estimated by total canopy solar-induced chlorophyll fluorescence (SIFtotal) compared to raw sensor observed SIF signals (SIFobs). The use of two-leaf strategy, which distinguishes between SIF from sunlit (SIFsunlit) and shaded (SIFshaded) leaves, further improves GPP estimates. However, the two-leaf strategy, along with SIF corrections for bidirectional effects, has not been applied to transpiration (T) estimation. In this study, we used the angular normalization method to correct the bidirectional effects and separate SIFsunlit and SIFshaded. Then we developed SIFsunlit and SIFshaded driven semi-mechanistic and hybrid models, comparing their T estimates with those from a SIFobs driven semi-mechanistic model at both site and global scales. All three types of SIF-driven T models integrate canopy conductance (g(c)) with the Penman-Monteith model, differing in how g(c) is derived: from a SIFobs driven semi-mechanistic equation, a SIFsunlit and SIFshaded driven semi-mechanistic equation, and a SIFsunlit and SIFshaded driven machine learning model. When evaluated against partitioned T using the underlying water use efficiency method at 72 eddy covariance sites and two global T remote sensing products, a consistent pattern emerged: SIFsunlit and SIFshaded driven hybrid model > SIFsunlit and SIFshaded driven semi-mechanistic model > SIFobs driven semi-mechanistic model. The SIFsunlit and SIFshaded driven hybrid model demonstrated a notable proficiency under high vapor pressure deficit and low soil water content conditions. The SIFobs driven semi-mechanistic model tends overestimate T at low T values, and this issue is significantly alleviated by the SIFsunlit and SIFshaded driven semi-mechanistic and hybrid models. Our findings demonstrate that correcting the bidirectional effects and using the two-leaf strategy on GPP estimation can improve T estimation and provide a new global T product incorporating vegetation physiological signal.
URL标识查看原文
WOS关键词INDUCED CHLOROPHYLL FLUORESCENCE ; WATER-USE EFFICIENCY ; CANOPY CONDUCTANCE ; AVAILABLE ENERGY ; 2-LEAF MODEL ; BIG-LEAF ; EVAPOTRANSPIRATION ; PHOTOSYNTHESIS ; RESOLUTION ; CARBON
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
WOS记录号WOS:001421787900001
出版者ELSEVIER SCIENCE INC
源URL[http://ir.igsnrr.ac.cn/handle/311030/212399]  
专题生态系统网络观测与模拟院重点实验室_外文论文
通讯作者Zheng, Chen; Wang, Shaoqiang
作者单位1.Univ Florence, Dept Civil & Environm Engn, Florence, Italy
2.Nanjing Univ, Int Inst Earth Syst Sci, Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing, Jiangsu, Peoples R China;
3.Univ New Hampshire, Inst Study Earth Oceans & Space, Earth Syst Res Ctr, Durham, NH 03824 USA;
4.Chinese Univ Geosci, Sch Geog & Informat Engn, Key Lab Reg Ecol Proc & Environm Evolut, Wuhan 430074, Peoples R China;
5.Univ Toronto, Dept Geog & Program Planning, Toronto, ON M5S 3G3, Canada;
6.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China;
7.Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China;
推荐引用方式
GB/T 7714		 Zheng, Chen,Wang, Shaoqiang,Chen, Jing M.,et al. Estimating global transpiration from TROPOMI SIF with angular normalization and separation for sunlit and shaded leaves[J]. REMOTE SENSING OF ENVIRONMENT,2025,319:114586.
APA Zheng, Chen.,Wang, Shaoqiang.,Chen, Jing M..,Xiao, Jingfeng.,Chen, Jinghua.,...&Forzieri, Giovanni.(2025).Estimating global transpiration from TROPOMI SIF with angular normalization and separation for sunlit and shaded leaves.REMOTE SENSING OF ENVIRONMENT,319,114586.
MLA Zheng, Chen,et al."Estimating global transpiration from TROPOMI SIF with angular normalization and separation for sunlit and shaded leaves".REMOTE SENSING OF ENVIRONMENT 319(2025):114586.

入库方式： OAI收割

来源：地理科学与资源研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。