Using reflectance to reduce solar angle effects on the scattering of far-red solar-induced chlorophyll fluorescence to better track the diurnal dynamics of gross primary productivity

• SIF observed (SIF obs ) from top of canopy and gross primary productivity (GPP) have different diurnal dynamics. • The variation in scattering of SIF (i.e., f esc ) leads to the different diurnal pattern of SIF obs and GPP. • Reflectance provides simple and effective means to estimate the f esc and total emitted SIF (SIF total ). • SIF total is insensitive to the scattering of SIF and improves the estimation of GPP at diurnal scale. Solar-induced chlorophyll fluorescence (SIF) is linked to photosynthesis and provides reliable estimation of Gross Primary Productivity (GPP). However, SIF observed (SIF obs ) at the top-of-canopy is theoretically less accurate in predicting GPP compared with the total emitted SIF (SIF total ). Converting remotely sensed SIF obs to SIF total is therefore crucial for improving GPP estimation. SIF obs is a portion of SIF total and their ratio is termed the fluorescence escape ratio ( f esc ), describing the scattering and re-absorption processes. f esc is affected by canopy structure and sun-observer geometry. Vegetation indices, such as the Fluorescence Correction Vegetation Index (FCVI) and the near-infrared reflectance of vegetation (NIR v ), have been developed to estimate f esc and SIF total with reasonable accuracy particularly under varying viewing angles scenarios. However, their performance in estimating f esc and SIF total has not been well-studied for a diurnal scale, in which solar angles vary. Solar angles affect both f esc and SIF total , while viewing angles affect f esc but not SIF emission. In this study, we analyzed the solar angle effects on far-red SIF scattering and mitigated the effects by leveraging these indices to estimate f esc , facilitating the derivation of SIF total for improving GPP estimation. Numerical experiments were employed to support the use of FCVI and NIR v for f esc estimation under varying chlorophyll content ( C ab ), leaf angle distribution (LAD) and leaf area index (LAI) conditions. SIF total was derived to enhance the accuracy of GPP estimation at the diurnal scale in filed measurements. Our results indicated that both FCVI and NIR v reliably estimated f esc under varying solar angles. Moreover, SIF total improved the SIF-GPP relationship, with R ² increasing to 0.43 – 0.80, compared to SIF obs (0.12 < R 2 <0.52), and its diurnal pattern was more consistent with that of GPP. Our study suggested that the use of FCVI and NIR v for f esc mitigates solar angle effects on SIF obs and thus improves GPP estimation.

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Publication Details

Journal
Agricultural and Forest Meteorology
Published
2025-08-18
DOI
https://doi.org/10.1016/j.agrformet.2025.110794
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.72

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article

Using reflectance to reduce solar angle effects on the scattering of far-red solar-induced chlorophyll fluorescence to better track the diurnal dynamics of gross primary productivity

Christiaan van der Tol, Xuhui Lu, Peiqi Yang, Alasdair Mac Arthur
1 citations
Agricultural and Forest Meteorology
Remote Sensing in Agriculture
1.72
article

Using reflectance to reduce solar angle effects on the scattering of far-red solar-induced chlorophyll fluorescence to better track the diurnal dynamics of gross primary productivity

Christiaan van der Tol, Xuhui Lu, Peiqi Yang, Alasdair Mac Arthur
article en
1 citations

Abstract

• SIF observed (SIF obs ) from top of canopy and gross primary productivity (GPP) have different diurnal dynamics. • The variation in scattering of SIF (i.e., f esc ) leads to the different diurnal pattern of SIF obs and GPP. • Reflectance provides simple and effective means to estimate the f esc and total emitted SIF (SIF total ). • SIF total is insensitive to the scattering of SIF and improves the estimation of GPP at diurnal scale. Solar-induced chlorophyll fluorescence (SIF) is linked to photosynthesis and provides reliable estimation of Gross Primary Productivity (GPP). However, SIF observed (SIF obs ) at the top-of-canopy is theoretically less accurate in predicting GPP compared with the total emitted SIF (SIF total ). Converting remotely sensed SIF obs to SIF total is therefore crucial for improving GPP estimation. SIF obs is a portion of SIF total and their ratio is termed the fluorescence escape ratio ( f esc ), describing the scattering and re-absorption processes. f esc is affected by canopy structure and sun-observer geometry. Vegetation indices, such as the Fluorescence Correction Vegetation Index (FCVI) and the near-infrared reflectance of vegetation (NIR v ), have been developed to estimate f esc and SIF total with reasonable accuracy particularly under varying viewing angles scenarios. However, their performance in estimating f esc and SIF total has not been well-studied for a diurnal scale, in which solar angles vary. Solar angles affect both f esc and SIF total , while viewing angles affect f esc but not SIF emission. In this study, we analyzed the solar angle effects on far-red SIF scattering and mitigated the effects by leveraging these indices to estimate f esc , facilitating the derivation of SIF total for improving GPP estimation. Numerical experiments were employed to support the use of FCVI and NIR v for f esc estimation under varying chlorophyll content ( C ab ), leaf angle distribution (LAD) and leaf area index (LAI) conditions. SIF total was derived to enhance the accuracy of GPP estimation at the diurnal scale in filed measurements. Our results indicated that both FCVI and NIR v reliably estimated f esc under varying solar angles. Moreover, SIF total improved the SIF-GPP relationship, with R ² increasing to 0.43 – 0.80, compared to SIF obs (0.12 < R 2 <0.52), and its diurnal pattern was more consistent with that of GPP. Our study suggested that the use of FCVI and NIR v for f esc mitigates solar angle effects on SIF obs and thus improves GPP estimation.

Agricultural and Forest MeteorologyVol. 373
Nanjing Normal University (CN), Parc Científic de la Universitat de València (ES), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application (CN), University of Twente (NL), University of Edinburgh (GB)
China Scholarship Council
Openalex Percentile: Top 14%
Remote Sensing in Agriculture
1.72
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