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@ARTICLE{Zeng:902689,
author = {Zeng, Yelu and Hao, Dalei and Badgley, Grayson and Damm,
Alexander and Rascher, Uwe and Ryu, Youngryel and Johnson,
Jennifer and Krieger, Vera and Wu, Shengbiao and Qiu, Han
and Liu, Yaling and Berry, Joseph A. and Chen, Min},
title = {{E}stimating near-infrared reflectance of vegetation from
hyperspectral data},
journal = {Remote sensing of environment},
volume = {267},
issn = {0034-4257},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2021-04476},
pages = {112723 -},
year = {2021},
abstract = {Disentangling the individual conttibutions from vegetation
and soil in measured canopy reflectance is a grand challenge
to the remote sensing and ecophysiology communities. Since
Solar lnduced chlorophyll Fluorescence (SIF) is tmiquely
emitted from vegetation, it can be used to evaluate how well
reflectance-based vegetation indices (VIs) can separate the
vegetation and soil components. Due to the residual soil
background conttibutions, Near-infrared (NIR) reflectance of
vegetation (NIRv) and Difference Vegetation index (DVI)
present offsets when compared to SIF (i.e., the value of
NIRv or DVI is non-zero when SIF is zero). In this study, we
proposed a simple framework for estimating the true NIR
reflectance ofvegetation from HyperspectraI measurements
(NIRvH) with minimal soil impacts. NIRvH takes advantage of
the spectral shape variations in ehe red-edge region to
minimize the soil effects. We evaluated the capability of
NIRvH, NIRv and DVI in isolating the true NIR reflectance of
vegetation using the data from both the model-based
simulations and Hyperspectral Plant imaging spectrometer
(HyPlant) measurements. Benchmarked by simultaneously
measured SIF, NIRvH has the smallest offset (0-0.037), as
compared to an intermediate offset of 0.047-0.062 from NIRv,
and the largest offset of 0.089-0.112 from DVI. The
magnicude of the offset can vary with different soil
reflectance spectra across spacio-temporal scales, which may
lead to bias in the downstream NIRv-based photosynthesis
estimates. NIRvH and SIF measurements from the sarne
sensor platform avoided complications due to different
geometry, footprint and time of observation across sensors
when studying the radiative transfer of reflected photons
and SIF. In addition, NIRvH was primarily determined by
canopy structure rather than chlorophyll content and soil
brightness. Our work showcases that NIRvH is promising for
retrieving canopy structure parameters such as leaf area
index and leaf inclination angle, and for estimating
fluorescence yield with current and forthcoming
hyperspectral satellite measmements.},
cin = {IBG-2},
ddc = {550},
cid = {I:(DE-Juel1)IBG-2-20101118},
pnm = {2173 - Agro-biogeosystems: controls, feedbacks and impact
(POF4-217)},
pid = {G:(DE-HGF)POF4-2173},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000714462800005},
doi = {10.1016/j.rse.2021.112723},
url = {https://juser.fz-juelich.de/record/902689},
}