The
2015–2016
El
Niño-induced
drought
caused
biomass
loss
in
global
tropical
forests,
yet
the
recovery
duration
of
different
vegetation
components
(woody
components,
upper
canopies,
and
leaves)
remains
unknown.
Here,
we
use
satellite
remote
sensing
data
optical
depth
leaf
area
index,
with
varying
sensitivity
to
examine
during
event.
We
find
that
woody
component
had
slowest
compared
canopy
leaves,
displayed
greater
spatial
variability
between
continents.
Key
factors
influencing
include
severity,
moisture-related
climatic
conditions
(i.e.,
vapor
pressure
deficit,
precipitation,
soil
moisture),
seasonal
variations
temperature
precipitation.
Our
study
highlights
importance
for
maintaining
ecosystem
balance
under
disturbances
indicates
need
further
research
explore
mechanisms
long-term
impacts
on
forest
dynamics.
Woody
forests
have
a
slower
rate
from
severe
canopies
according
multiple
observations
across
tropics
2015-2016
Remote Sensing,
Journal Year:
2024,
Volume and Issue:
16(22), P. 4235 - 4235
Published: Nov. 14, 2024
Accurate
surface
soil
moisture
(SM)
data
are
crucial
for
agricultural
management
in
Jiangsu
Province,
one
of
the
major
regions
China.
However,
seasonal
performance
different
SM
products
is
still
unknown.
To
address
this,
this
study
aims
to
evaluate
applicability
four
L-band
microwave
remotely
sensed
products,
namely,
Soil
Moisture
Active
Passive
Single-Channel
Algorithm
at
Vertical
Polarization
Level
3
(SMAP
SCA-V
L3,
hereafter
SMAP-L3),
SMOS-SMAP-INRAE-BORDEAUX
(SMOSMAP-IB),
and
Ocean
Salinity
version
IC
(SMOS-IC),
SMAP-INRAE-BORDEAUX
(SMAP-IB)
scale.
In
addition,
effects
dynamic
environmental
variables
such
as
leaf
vegetation
index
(LAI),
mean
temperature
(MSST),
wetness
(MSSM)
on
above
investigated.
The
results
indicate
that
all
exhibit
significant
differences
when
evaluated
against
situ
observations
between
2016
2022,
with
most
achieving
their
highest
correlation
(R)
unbiased
root-mean-square
difference
(ubRMSD)
scores
during
autumn.
Conversely,
significantly
deteriorates
summer,
ubRMSD
values
exceeding
0.06
m3/m3.
SMOS-IC
generally
achieves
better
R
across
seasons
but
has
limited
temporal
availability,
while
SMAP-IB
typically
lowest
values,
even
reaching
0.03
m3/m3
morning
observation
winter.
Additionally,
sensitivity
products’
skill
metrics
factors
varies
seasons.
For
ubRMSD,
SMAP-L3
shows
a
general
increase
LAI
seasons,
exhibits
notable
becomes
wetter
summer.
wet
conditions
notably
reduce
autumn
products.
These
findings
expected
offer
valuable
insights
appropriate
selection
enhancement
retrieval
algorithms.
The
2015–2016
El
Niño-induced
drought
caused
biomass
loss
in
global
tropical
forests,
yet
the
recovery
duration
of
different
vegetation
components
(woody
components,
upper
canopies,
and
leaves)
remains
unknown.
Here,
we
use
satellite
remote
sensing
data
optical
depth
leaf
area
index,
with
varying
sensitivity
to
examine
during
event.
We
find
that
woody
component
had
slowest
compared
canopy
leaves,
displayed
greater
spatial
variability
between
continents.
Key
factors
influencing
include
severity,
moisture-related
climatic
conditions
(i.e.,
vapor
pressure
deficit,
precipitation,
soil
moisture),
seasonal
variations
temperature
precipitation.
Our
study
highlights
importance
for
maintaining
ecosystem
balance
under
disturbances
indicates
need
further
research
explore
mechanisms
long-term
impacts
on
forest
dynamics.
Woody
forests
have
a
slower
rate
from
severe
canopies
according
multiple
observations
across
tropics
2015-2016
