remote sensing
Article
Comparative Analysis on the Estimation of Diurnal
Solar-Induced Chlorophyll Fluorescence Dynamics for a
Subtropical Evergreen Coniferous Forest
Jinghua Chen
1
, Shaoqiang Wang
1,2,3,
*, Bin Chen
1,2
, Yue Li
4
, Muhammad Amir
1,2
, Li Ma
1,2
, Kai Zhu
1,2
,
Fengting Yang
1,2
, Xiaobo Wang
1,2
, Yuanyuan Liu
1,2
, Pengyuan Wang
1,2
, Junbang Wang
1,2
, Mei Huang
1,2
and Zhaosheng Wang
1,2
Citation: Chen, J.; Wang, S.; Chen, B.;
Li, Y.; Amir, M.; Ma, L.; Zhu, K.; Yang,
F.; Wang, X.; Liu,Y.; et al.
Comparative Analysis on the
Estimation of Diurnal Solar-Induced
Chlorophyll Fluorescence Dynamics
for a Subtropical Evergreen
Coniferous Forest. Remote Sens. 2021,
13, 3143. https://doi.org/10.3390/
rs13163143
Academic Editor: Shawn C. Kefauver
Received: 27 May 2021
Accepted: 6 August 2021
Published: 9 August 2021
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1
Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and
Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
chenjh.14b@igsnrr.ac.cn (J.C.); chenbin@igsnrr.ac.cn (B.C.); mamir2019@igsnrr.ac.cn (M.A.);
mali.16b@igsnrr.ac.cn (L.M.); zhuk.20b@igsnrr.ac.cn (K.Z.); yangft@igsnrr.ac.cn (F.Y.);
wangxiaobo17@mails.ucas.ac.cn (X.W.); liuyuanyuan182@mails.ucas.ac.cn (Y.L.);
wangpy.19b@igsnrr.ac.cn (P.W.); jbwang@igsnrr.ac.cn (J.W.); huangm@igsnrr.ac.cn (M.H.);
wangzs@igsnrr.ac.cn (Z.W.)
2
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
3
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
4
School of Earth Science and Engineering, Hebei University of Engineering, Handan 056038, China;
liyue@hebeu.edu.cn
* Correspondence: sqwang@igsnrr.ac.cn
Abstract: Solar-induced chlorophyll fluorescence (SIF) is considered as a prospective indicator of
vegetation photosynthetic activity and the ecosystem carbon cycle. The current coarse spatial-
temporal resolutions of SIF data from satellite missions and ground measurements still cannot satisfy
the corroboration of its correlation with photosynthesis and carbon flux. Practical approaches are
needed to be explored for the supplementation of the SIF measurements. In our study, we clarified the
diurnal variations of leaf and canopy chlorophyll fluorescence for a subtropical evergreen coniferous
forest and evaluated the performance of the canopy chlorophyll concentration (CCC) approach and
the backward approach from gross primary production (GPP) for estimating the diurnal variations
of canopy SIF by comparing with the Soil Canopy Observation Photosynthesis Energy (SCOPE)
model. The results showed that the canopy SIF had similar seasonal and diurnal variations with
the incident photosynthetically active radiation (PAR) above the canopy, while the leaf steady-state
fluorescence remained stable during the daytime. Neither the CCC nor the raw backward approach
from GPP could capture the short temporal dynamics of canopy SIF. However, after improving the
backward approach with a correction factor of normalized PAR incident on leaves, the variation of
the estimated canopy SIF accounted for more than half of the diurnal variations in the canopy SIF
(SIF
687
:R
2
= 0.53, p < 0.001; SIF
760
:R
2
= 0.72, p < 0.001) for the subtropical evergreen coniferous forest
without water stress. Drought interfered with the utilization of the improved backward approach
because of the decoupling of SIF and GPP due to stomatal closure. This new approach offers new
insight into the estimation of diurnal canopy SIF and can help understand the photosynthesis of
vegetation for future climate change studies.
Keywords: chlorophyll fluorescence; model comparison; SCOPE model; evergreen conifer; wa-
ter stress
1. Introduction
Chlorophyll Fluorescence (ChlF) is regarded as a prospective marker of vegetation pho-
tosynthetic activity and a vital indicator of the carbon cycle. Leaf chlorophyll molecules cap-
ture light energy and transmit it to the reaction centers to release through three pathways:
Remote Sens. 2021, 13, 3143. https://doi.org/10.3390/rs13163143 https://www.mdpi.com/journal/remotesensing