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@ARTICLE{Konings:280327,
author = {Konings, Alexandra G. and Piles, María and Rötzer,
Kathrina and McColl, Kaighin A. and Chan, Steven K. and
Entekhabi, Dara},
title = {{V}egetation optical depth and scattering albedo retrieval
using time series of dual-polarized {L}-band radiometer
observations},
journal = {Remote sensing of environment},
volume = {172},
issn = {0034-4257},
address = {Amsterdam [u.a.]},
publisher = {Elsevier Science},
reportid = {FZJ-2016-00111},
pages = {178 - 189},
year = {2016},
abstract = {Passive microwave measurements have the potential to
estimate vegetation optical depth (VOD), an indicator of
aboveground vegetation water content. They are also
sensitive to the vegetation scattering albedo and soil
moisture. In this work, we propose a novel algorithm to
retrieve VOD and soil moisture from time series of
dual-polarized L-band radiometric observations along with
time-invariant scattering albedo. The method takes advantage
of the relatively slow temporal dynamics of early morning
vegetation water content and combines a number of
consecutive observations to estimate a single VOD. It is
termed the multi-temporal dual channel algorithm (MT-DCA).
The soil dielectric constant (directly related to soil
moisture) of each observation is also retrieved
simultaneously. Additionally, the method retrieves a
constant albedo, thereby providing for the first time
information on global single-scattering albedo variations.
The algorithm is tested using three years of L-band passive
observations from the NASA Aquarius sensor. The global VOD
distribution follows expected gradients of climate and
canopy biomass conditions. Its seasonal dynamics follow
expected behavior based on precipitation and land cover. The
retrieved VOD is closely related to coincident
cross-polarized backscatter coefficients. The VOD and
dielectric retrievals from MT-DCA are compared to those
obtained from implementing the commonly used Land Parameter
Retrieval Model (LPRM) algorithm and shown to have less
high-frequency noise. There is almost as much variation in
MT-DCA retrieved albedo between pixels of a given land cover
class than between land cover classes, suggesting the common
approach of assigning albedo based on land cover class may
not capture its spatial variability. Globally, albedo
appears to be primarily sensitive to woody biomass. The
proposed algorithm allows for a more accurate accounting of
the effects of vegetation on radiometric soil moisture
retrievals, and generates new observations of L-band VOD and
effective single-scattering albedo. These new datasets are
complementary to existing remotely sensed vegetation
measurements such as fluorescence and optical-infrared
indices.},
cin = {IBG-3},
ddc = {050},
cid = {I:(DE-Juel1)IBG-3-20101118},
pnm = {255 - Terrestrial Systems: From Observation to Prediction
(POF3-255)},
pid = {G:(DE-HGF)POF3-255},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000366764500014},
doi = {10.1016/j.rse.2015.11.009},
url = {https://juser.fz-juelich.de/record/280327},
}