Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based Observations

Tower-based solar-induced chlorophyll fluorescence (SIF) measurements have yielded crucial datasets for investigating the diurnal patterns of SIF and its relationship with vegetation photosynthesis. This study assessed the performance of 3 distinct SIF retrieval algorithms, including band shape fitt...

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Main Authors: Xinjie Liu, Liangyun Liu, Shanshan Du, Mengjia Qi
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS) 2025-01-01
Series:Journal of Remote Sensing
Online Access:https://spj.science.org/doi/10.34133/remotesensing.0429
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author Xinjie Liu
Liangyun Liu
Shanshan Du
Mengjia Qi
author_facet Xinjie Liu
Liangyun Liu
Shanshan Du
Mengjia Qi
author_sort Xinjie Liu
collection DOAJ
description Tower-based solar-induced chlorophyll fluorescence (SIF) measurements have yielded crucial datasets for investigating the diurnal patterns of SIF and its relationship with vegetation photosynthesis. This study assessed the performance of 3 distinct SIF retrieval algorithms, including band shape fitting (BSF), 3-band Fraunhofer line discrimination (3FLD), and a data-driven approach based on singular vector decomposition (SVD), for retrieving far-red SIF diurnal patterns from tower-based observations at the 2 flux sites in China. This study analyzed diurnal patterns of SIF and SIF yield, as well as correlations between SIF, near-infrared radiance reflected by vegetation (NIRvR), and gross primary productivity (GPP) at diurnal and seasonal scales. More pronounced inconsistencies in retrieved SIF by different algorithms at noon compared with the morning and afternoon were observed. Similarly, correlations between the SIF and NIRvR or GPP are weaker during midday. This study underscores the need to consider the reliability of SIF data when investigating diurnal patterns, and the necessity for developments in tower-based SIF retrieval algorithms.
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language English
publishDate 2025-01-01
publisher American Association for the Advancement of Science (AAAS)
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spelling doaj-art-915415f3ca3f406788bea62a677ccbd32025-08-20T01:56:49ZengAmerican Association for the Advancement of Science (AAAS)Journal of Remote Sensing2694-15892025-01-01510.34133/remotesensing.0429Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based ObservationsXinjie Liu0Liangyun Liu1Shanshan Du2Mengjia Qi3International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China.Tower-based solar-induced chlorophyll fluorescence (SIF) measurements have yielded crucial datasets for investigating the diurnal patterns of SIF and its relationship with vegetation photosynthesis. This study assessed the performance of 3 distinct SIF retrieval algorithms, including band shape fitting (BSF), 3-band Fraunhofer line discrimination (3FLD), and a data-driven approach based on singular vector decomposition (SVD), for retrieving far-red SIF diurnal patterns from tower-based observations at the 2 flux sites in China. This study analyzed diurnal patterns of SIF and SIF yield, as well as correlations between SIF, near-infrared radiance reflected by vegetation (NIRvR), and gross primary productivity (GPP) at diurnal and seasonal scales. More pronounced inconsistencies in retrieved SIF by different algorithms at noon compared with the morning and afternoon were observed. Similarly, correlations between the SIF and NIRvR or GPP are weaker during midday. This study underscores the need to consider the reliability of SIF data when investigating diurnal patterns, and the necessity for developments in tower-based SIF retrieval algorithms.https://spj.science.org/doi/10.34133/remotesensing.0429
spellingShingle Xinjie Liu
Liangyun Liu
Shanshan Du
Mengjia Qi
Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based Observations
Journal of Remote Sensing
title Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based Observations
title_full Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based Observations
title_fullStr Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based Observations
title_full_unstemmed Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based Observations
title_short Inconsistent Diurnal Patterns of Far-Red Solar-Induced Chlorophyll Fluorescence Retrieved with Different Algorithms from Tower-Based Observations
title_sort inconsistent diurnal patterns of far red solar induced chlorophyll fluorescence retrieved with different algorithms from tower based observations
url https://spj.science.org/doi/10.34133/remotesensing.0429
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AT shanshandu inconsistentdiurnalpatternsoffarredsolarinducedchlorophyllfluorescenceretrievedwithdifferentalgorithmsfromtowerbasedobservations
AT mengjiaqi inconsistentdiurnalpatternsoffarredsolarinducedchlorophyllfluorescenceretrievedwithdifferentalgorithmsfromtowerbasedobservations