Remote Sensing,
Journal Year:
2024,
Volume and Issue:
16(22), P. 4189 - 4189
Published: Nov. 10, 2024
In
the
context
of
drought
events
caused
by
global
warming,
there
is
limited
understanding
vegetation
loss
and
subsequent
recovery
after
ends.
However,
employing
a
single
index
representing
specific
characteristic
to
explore
drought’s
impact
on
may
overlook
features
introduce
increased
uncertainty.
We
applied
enhanced
(EVI),
fraction
cover
(FVC),
gross
primary
production
(GPP),
leaf
area
(LAI),
our
constructed
remote
sensing
(RSVI)
assess
in
Central
Asia.
analyzed
differences
experiences
for
different
climatic
regions
types
following
events.
The
results
indicate
that
during
years
(2012
2019),
across
were
considerable.
arid,
semiarid,
Mediterranean
climate
was
more
susceptible
drought.
indices
used
exhibited
varying
degrees
dynamic
changes,
with
state
mild
experiencing
significantly
assessment
significant
variations
periods
(with
period
16
days:
EVI
85%,
FVC
50%,
GPP
84%,
LAI
61%,
RSVI
44%).
Moreover,
required
tended
decrease
from
arid
humid
climates,
influenced
both
types.
Sensitivity
analysis
indicated
factors
leading
varied
depending
used.
proposed
demonstrates
high
sensitivity,
correlation,
interpretability
dry–wet
can
be
vegetation.
These
findings
are
essential
water
resource
management
implementation
measures
mitigate
Agronomy,
Journal Year:
2024,
Volume and Issue:
14(4), P. 708 - 708
Published: March 28, 2024
To
accurately
forecast
the
future
development
trend
of
vegetation
in
dry
areas,
it
is
crucial
to
continuously
monitor
phenology,
health
indices,
and
drought
indices
over
an
extended
period.
This
because
caused
by
high
temperatures
significantly
affects
vegetation.
study
thoroughly
investigated
spatial
temporal
variations
phenological
characteristics
abdominal
part
Maowusu
Sandland
China
past
20
years.
Additionally,
established
a
linear
correlation
between
temperature
arid
zone.
address
issue
predicting
long-term
trends
changes,
we
have
developed
method
that
combines
Informer
deep
learning
model
with
seasonal
Seasonal
Trend
decomposition
using
Loess
(STL)
empirical
mode
(EMD).
utilized
linearly
correlated
meteorological
data
spanning
years
predict
Normalized
Difference
Vegetation
Index
(NDVI)
Temperature
Dryness
(TVDI).
The
study’s
findings
indicate
20-year
observation
period,
there
was
upward
NDVI,
accompanied
decrease
both
frequency
severity
droughts.
STL-EMD-Informer
successfully
predicted
mean
absolute
percentage
error
(MAPE
=
1.16%)
changes
for
next
decade.
suggests
overall
expected
continue
improving
during
time.
work
examined
plant
growth
circumstances
locations
from
several
angles
complete
analytical
provide
strong
scientific
basis
ecological
conservation
management
regions.
Open Geosciences,
Journal Year:
2024,
Volume and Issue:
16(1)
Published: Jan. 1, 2024
Abstract
Normalized
difference
vegetation
index
(NDVI)
and
land
surface
temperature
(LST)
are
important
indicators
of
ecological
changes,
their
spatial
temporal
variations
coupling
can
provide
a
theoretical
basis
for
the
sustainable
development
environment.
Based
on
MOD13A1
MOD11A2
datasets,
distribution
characteristics
NDVI
LST
from
2000
to
2020
were
analyzed,
trend
change
slope
method
model
used
calculate
significant
changes.
Finally,
was
degree
between
LST.
The
study
shows
that:
(1)
From
2020,
annual
value
Mu
Us
Sandy
Land
0.25
0.43,
showing
stable
upward
overall,
with
an
increase
rate
0.074/(10a).
proportion
improvement
areas
in
area
is
81.48%.
(2)
There
differences
Land,
overall
decreasing
northwest
southeast
higher
west
than
east.
greatly
affected
by
changes
use
types.
spatiotemporal
variation
different
gradual
warming
global
climate
change.
main
reason
that
human
activities
have
changed
types
increased
local
coverage.
(3)
negative
correlation
R
2
0.5073
passing
significance
test
at
0.01
level.
This
indicates
engineering
policies
effectively
reduce
area,
thereby
achieving
effect
improving
very
high
level,
average
0.895
area.
two
mainly
exhibit
state
mutual
antagonism
space,
reflecting
importance
green
regulating
regional
result
joint
influence
change,
dominated
2020.
Land,
Journal Year:
2024,
Volume and Issue:
13(3), P. 307 - 307
Published: Feb. 29, 2024
Sand
prevention
and
control
are
the
main
tasks
of
desertification
control.
The
MU
Us
Sandy
Land
(MUSL),
one
China’s
four
deserts,
frequently
experiences
droughts
has
a
very
fragile
biological
environment.
Climate
change
is
factor
leading
to
drought,
it
may
result
in
more
serious
drought
situations
future.
Temperature
Vegetation
Dryness
Index
(TVDI)
was
established
using
land
surface
temperature
normalized
difference
vegetation
index
data.
In
this
paper,
we
investigate
spatial
temporal
characteristics,
future
trends,
time-lag
effect
TVDI
on
climate
factors
at
different
scales
MUSL
from
2001
2020
Sen
+
Mann–Kendall
trend
analysis,
Hurstexponent,
partial
correlation
lag
analysis
methods.
results
show
that
(1)
overall
shows
characteristic
gradually
alleviating
west
east
(TVDI
=
0.6).
A
significant
drying
dominated
38.5%
pixels
fall
(Z
1.99),
highly
rest
three
seasons
average
2.95)
whole
year
3.47).
(2)
future,
dry
autumn,
winter,
will
be
by
continuous
drying,
spring
summer
mainly
wet.
relationships
between
winter
(−0.06)
precipitation
(−0.07)
were
negative,
while
evapotranspiration
(0.18)
showed
positive
correlation.
six
use
types
spring,
summer,
fall,
primarily
non-significantly
positively
correlated
with
evapotranspiration.
(3)
At
seasonal
scale,
sensitive
autumn
opposite,
responding
quickly
(0.3
months)
being
less
(1.8
(2
months).
interannual
desert
most
(2.6
least
responsive
(3
Forests,
Journal Year:
2023,
Volume and Issue:
14(8), P. 1679 - 1679
Published: Aug. 18, 2023
In
the
context
of
global
warming,
timely
and
accurate
drought
monitoring
is
great
importance
to
ensure
regional
ecological
security
guide
agricultural
production.
This
study
established
Drought
Severity
Index
(DSI),
based
on
potential
evapotranspiration
(PET),
(ET)
normalized
difference
vegetation
index
(NDVI)
data
from
2001
2020,
compensate
for
low
accuracy
spatial
temporal
evolution
due
uneven
distribution
stations.
The
DSI
was
reveal
variation
droughts
in
Inner
Mongolia
past
20
years,
using
trend
analysis,
gravity
shift
geographic
probes,
explore
influence
different
factors
DSI.
results
were
as
follows.
(1)
showed
that
during
2001–2020
had
strong
heterogeneity,
generally
characteristics
west
wet
east.
addition,
changes
all
exhibited
a
rising
tendency,
with
highest
tendency
deciduous
broadleaf
forests
(DBF)
lowest
grassland
(GRA).
(2)
center
wet,
normal
arid
areas
migration
northeast
southwest,
distances
209
km,
462
km
826
respectively.
(3)
four
combinations
temperature
elevation,
slope,
land
use,
rainfall
contributed
most.
obtained
this
are
important
scheduling
early
warnings
prevention
control.
FUDMA Journal of Sciences,
Journal Year:
2024,
Volume and Issue:
8(4), P. 199 - 209
Published: Aug. 24, 2024
This
study
reviews
the
application
and
effectiveness
of
various
remote
sensing
(RS)
indices
for
drought
monitoring
in
Sub-Saharan
Africa
(SSA).
Given
region’s
diverse
climatic
zones
frequent
occurrences,
accurate
timely
assessment
tools
are
crucial.
The
examines
from
different
spectral
regions,
including
optical,
thermal
infrared,
microwave
bands,
focusing
on
their
spatial
temporal
resolutions,
data
availability,
strengths,
limitations.
Optical
such
as
Normalized
Difference
Vegetation
Index
(NDVI)
Water
(NDWI)
effective
semi-arid
sub-humid
where
vegetation
density
varies.
Thermal
infrared
indices,
Temperature
Condition
(TCI),
Health
(VHI),
Dryness
(TVDI),
provide
insights
into
anomalies
health,
with
TCI
particularly
suited
TVDI
useful
both
zones.
Microwave
Backscatter
Moisture
(NBMI),
Depth
(VOD),
Polarization
(MPDI),
excel
capturing
soil
moisture
water
content,
proving
humid
forest
integration
these
other
meteorological
hydrological
enhances
management
strategies.
Recommendations
made
optimal
use
across
SSA
agroecological
