Remote Sensing of Environment,
Год журнала:
2024,
Номер
307, С. 114148 - 114148
Опубликована: Апрель 11, 2024
Effective
water
management
in
agriculture
requires
a
comprehensive
understanding
of
the
distribution
content
throughout
soil
profile
to
root
zone.
This
knowledge
empowers
farmers
and
managers
make
informed
decisions
regarding
irrigation
timing
quantity
for
optimizing
crop
growth.
To
estimate
moisture
profile,
this
study
utilized
combined
L-
P-band
radiometry
with
four
incoherent
radiative
transfer
models,
including
three
multi-layer
models
based
on
zero-order
(IZ),
first
order
(IF)
solution
(IS)
approximation,
uniform
model
(UM)
model,
as
well
stratified
coherent
Njoku
(NM).
The
impact
vegetation
was
considered
through
conventional
tau-omega
model.
Linear
(Li)
second-order
polynomial
(Pn2)
functions
were
used
represent
shape
profile.
Observations
from
tower-based
experiment
under
various
land
cover
conditions,
bare,
bare-weed,
grass,
wheat
corn,
used.
mean
square
error
(RMSE)
calculated
between
observed
estimated
profiles.
results
revealed
comparable
RMSE
values
all
five
Pn2
function
outperforming
Li
estimating
deeper
layers.
Regardless
employed
utilizing
employing
yielded
RMSEs
0.03
m3/m3,
0.08
0.1
m3/m3
over
depths
0–5
cm,
0–30
0–60
respectively.
A
comparison
indicated
that
latter
slightly
outperformed
former
dry
bare
exhibiting
0.003
lower
at
surface
while
nearly
equal
performance
bottom
Furthermore,
provided
only
better
than
UM
especially
shallow
layers,
average
entire
being
0.002
lower.
Consequently,
complexity
is
not
justified
small
gain
performance.
depth
which
reasonable
ranged
1
cm
(under
wet
corn)
39
bare),
depended
gradient
These
important
findings
pave
way
global
scale
using
future
satellite
missions.
Geotechnics,
Год журнала:
2024,
Номер
4(1), С. 78 - 108
Опубликована: Янв. 4, 2024
The
ability
to
precisely
monitor
soil
moisture
is
highly
valuable
in
industries
including
agriculture
and
civil
engineering.
As
a
spatially
erratic
temporally
dynamic
variable,
rapid,
cost-effective,
widely
applicable,
practical
techniques
are
required
for
monitoring
at
all
scales.
If
consistent
numerical
relationship
between
content
reflectance
can
be
identified,
then
spectroscopic
models
may
used
efficiently
predict
from
proximal
and/or
remotely
sensed
data.
Previous
studies
have
identified
general
decrease
visible–NIR
as
increases,
however,
the
strength,
best
wavelengths
modelling,
domain
of
remain
unclear
current
literature.
After
reviewing
relevant
literature
molecular
interactions
water
light
(400–2500
nm)
range,
this
review
presents
new
analyses
interprets
1
nm
resolution
data,
collected
>20
levels
ten
samples.
These
data
compared
results
other
published
studies,
extending
these
further
interpretation.
Analyses
high-resolution
dataset
demonstrate
that
linear
sufficient
characterise
many
cases,
but
relationships
typically
exponential.
Equations
generalising
MC
presented
number
wavelength
ranges
combinations.
Guidance
adjustment
equations
suit
types
also
provided,
allow
others
apply
solutions
here
much
wider
range
soils.
Agronomy,
Год журнала:
2025,
Номер
15(3), С. 685 - 685
Опубликована: Март 12, 2025
Net
ecosystem
productivity
(NEP)
is
a
crucial
metric
for
quantifying
carbon
storage,
exchange,
and
cycling
across
global
atmospheric
terrestrial
ecosystems.
This
study
examines
the
spatiotemporal
patterns
of
NEP
in
China’s
Zoigê
alpine
grassland
its
response
to
climate
variability,
phenological
changes,
soil
conditions
from
2000
2020.
The
results
show
statistically
significant
increase
annual
Plateau,
with
an
average
rate
3.18
g
C/m2/year.
Spatially,
displays
strong
heterogeneity,
higher
values
southwestern
northeastern
marginal
areas
(>80
C/m2)
lower
central
region
(<0
C/m2).
In
meadows
(standardized
total
effect
coefficient
[STEC]
=
0.52)
steppes
(STEC
0.43),
primarily
regulated
by
moisture
modulation,
influenced
both
water
temperature
factors.
accurately
assesses
incorporating
regional
characteristics,
providing
more
precise
evaluation
changes
vegetation
sink
sources
high-altitude
areas.
Frontiers in Environmental Science,
Год журнала:
2023,
Номер
11
Опубликована: Май 9, 2023
Taking
the
Mongolian
Plateau
as
research
area,
this
paper
studied
vegetation
growth
from
2001
to
2018.
We
quantified
changes
based
on
in
gross
primary
productivity
(GPP)
and
leaf
area
index
(LAI)
their
relationships
climate
variables
using
correlation
analysis,
partial
analysis
multiple
analysis.
The
results
showed
that
2018
both
GPP
LAI
an
increasing
trend,
with
great
heterogeneities
among
different
areas
land
cover
types.
largest
increase
of
occurred
northeast
plateau
types
forest
cropland.
main
driving
factor
was
precipitation,
while
temperature
significantly
negatively
correlated
growth.
CO
2
concentration
had
a
significant
impact
farmland,
solar
radiation
tundra.
Our
study
highlights
importance
precipitation
regulating
Plateau,
challenging
prevailing
views
dominates
northern
ecosystems.
