Comparison of Phenology Estimated From Monthly Vegetation Indices and Solar-Induced Chlorophyll Fluorescence in China
Phenology is an important biological indicator for monitoring terrestrial ecosystems and global change. Solar-induced chlorophyll fluorescence (SIF) emitted by chlorophyll has been proven to characterize vegetation photosynthesis and phenology. In this study, we used monthly normalized difference ve...
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Published in | Frontiers in earth science (Lausanne) Vol. 10 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
15.02.2022
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Subjects | |
Online Access | Get full text |
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Summary: | Phenology is an important biological indicator for monitoring terrestrial ecosystems and global change. Solar-induced chlorophyll fluorescence (SIF) emitted by chlorophyll has been proven to characterize vegetation photosynthesis and phenology. In this study, we used monthly normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), and SIF products to qualitatively compare the effectiveness at detecting the phenological characteristics (SOS (start-of-season), EOS (end-of-season), and LOS (length-of-season)) over China during 2007–2013. The phenological characteristics determined by gross primary productivity (GPP) were applied as the reference to validate the phenological characteristics derived from NDVI, EVI, and SIF. The results demonstrated that the phenological characteristics derived from SIF were more consistent with that of GPP than VIs (NDVI and EVI) when considering all latitude grades, different elevation grades, and different land cover types in China. In the middle- and high-latitude regions, SOS derived from the vegetation indices (SOS
VIs
) did not deviate from those from GPP (SOS
GPP
) and SIF (SOS
SIF
), while in low latitudes, SOS
VIs
were about 20 d later than SOS
SIF
and SOS
GPP
. The VIs (EOS
VIs
) had a severe lag behind those of SIF (EOS
SIF
) in estimating the EOS at all latitudes. The EOS
SIF
had a deviation of fewer than 5 d compared with EOS estimated by GPP (EOS
GPP
), whereas the deviation of EOS
VIs
from EOS
GPP
was about 10–31 d across low to high latitude regions. The biases of SIF and VIs were due to the inconsistency between vegetation photosynthesis and leaf greenness. Also, VIs overestimated the LOS at all latitudes, the difference of LOS between estimated by NDVI and estimated by GPP was as long as 39 d in the high-latitude region. Our study suggests that SIF is suitable for estimating the phenological characteristics of vegetation regardless of different latitudes, elevation grades, and land cover types in China, providing a basis for SIF to study the vegetation phenological characteristics in a regional scope. |
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ISSN: | 2296-6463 2296-6463 |
DOI: | 10.3389/feart.2022.802763 |