kNDVI Spatiotemporal Variations and Climate Lag on Qilian Southern Slope: Sen–Mann–Kendall and Hurst Index Analyses for Ecological Insights
Forests,
Год журнала:
2025,
Номер
16(2), С. 307 - 307
Опубликована: Фев. 10, 2025
In
the
context
of
climate
change,
southern
slope
Qilian
Mountains
stands
as
a
pivotal
region
for
China’s
ecological
security,
holding
immense
significance
sustaining
sustainable
development.
This
study
aims
to
precisely
monitor
and
predict
dynamic
changes
in
vegetation
cover
within
this
region,
along
with
their
time-lagged
effects
on
thereby
providing
scientific
basis
management.
By
calculating
kNDVI
from
2001
2020
Google
Earth
Engine
(GEE)
platform,
integrating
Sen’s
trend
analysis,
Hurst
exponent,
partial
correlation
we
have
conducted
an
in-depth
exploration
long-term
spatiotemporal
variations
its
delayed
responses
factors.
The
primary
research
findings
can
be
summarized
follows:
exhibits
overall
positive
trend,
notable
geographical
spatial
distribution.
proportion
areas
showing
improvement
is
high
84%,
while
degraded
account
only
17%.
Furthermore,
there
average
lag
response
1.6
months
precipitation
0.6
temperature
region.
speed
positively
correlates
coefficient
between
Notably,
more
sensitive
area
Mountains.
not
fills
gap
monitoring
but
also
offers
support
governance
green
development
initiatives
Additionally,
it
showcases
innovative
application
advanced
remote
sensing
technologies
statistical
analysis
methods
research,
fresh
perspectives
future
management
strategies.
These
hold
profound
implications
promoting
conservation
area.
Язык: Английский
Spatiotemporal Dynamics and Response of Land Surface Temperature and Kernel Normalized Difference Vegetation Index in Yangtze River Economic Belt, China: Multi-Method Analysis
Land,
Год журнала:
2025,
Номер
14(3), С. 598 - 598
Опубликована: Март 12, 2025
As
global
climate
change
intensifies,
its
impact
on
the
ecological
environment
is
becoming
increasingly
pronounced.
Among
these,
land
surface
temperature
(LST)
and
vegetation
cover
status,
as
key
indicators,
have
garnered
widespread
attention.
This
study
analyzes
spatiotemporal
dynamics
of
LST
Kernel
Normalized
Difference
Vegetation
Index
(KNDVI)
in
11
provinces
along
Yangtze
River
their
response
to
based
MODIS
Terra
satellite
data
from
2000
2020.
The
linear
regression
showed
a
significant
KNDVI
increase
0.003/year
(p
<
0.05)
rise
0.065
°C/year
0.01).
Principal
Component
Analysis
(PCA)
explained
74.5%
variance,
highlighting
dominant
influence
urbanization.
K-means
clustering
identified
three
regional
patterns,
with
Shanghai
forming
distinct
group
due
low
variability.
Generalized
Additive
Model
(GAM)
analysis
revealed
nonlinear
LST–KNDVI
relationship,
most
evident
Hunan,
where
cooling
effects
weakened
beyond
threshold
0.25.
Despite
0.07
increase,
high-temperature
areas
Chongqing
Jiangsu
expanded
by
over
2500
km2,
indicating
limited
mitigation.
reveals
complex
interaction
between
KNDVI,
which
may
provide
scientific
basis
for
development
management
adaptation
strategies.
Язык: Английский
Dynamic monitoring and drivers of ecological environmental quality in the Three-North region, China: Insights based on remote sensing ecological index
Ecological Informatics,
Год журнала:
2024,
Номер
unknown, С. 102936 - 102936
Опубликована: Дек. 1, 2024
Язык: Английский
Interpretable LAI Fine Inversion of Maize by Fusing Satellite, UAV Multispectral, and Thermal Infrared Images
Agriculture,
Год журнала:
2025,
Номер
15(3), С. 243 - 243
Опубликована: Янв. 23, 2025
Leaf
area
index
(LAI)
serves
as
a
crucial
indicator
for
characterizing
the
growth
and
development
process
of
maize.
However,
LAI
inversion
maize
based
on
unmanned
aerial
vehicles
(UAVs)
is
highly
susceptible
to
various
factors
such
weather
conditions,
light
intensity,
sensor
performance.
In
contrast
satellites,
spectral
stability
UAV-based
data
relatively
inferior,
phenomenon
“spectral
fragmentation”
prone
occur
during
large-scale
monitoring.
This
study
was
designed
solve
problem
that
UAVs
difficult
achieve
both
high
spatial
resolution
consistency.
A
two-stage
remote
sensing
fusion
method
integrating
coarse
fine
proposed.
The
SHapley
Additive
exPlanations
(SHAP)
model
introduced
investigate
contributions
20
features
in
7
categories
maize,
canopy
temperature
extracted
from
thermal
infrared
images
one
them.
Additionally,
most
suitable
feature
sampling
window
determined
through
multi-scale
experiments.
grid
search
used
optimize
hyperparameters
models
Gradient
Boosting,
XGBoost,
Random
Forest,
their
accuracy
compared.
results
showed
that,
by
utilizing
3
×
9
with
highest
contributions,
whole
stage
Forest
could
reach
R2
=
0.90
RMSE
0.38
m2/m2.
Compared
single
UAV
source
mode,
enhanced
nearly
25%.
jointing,
tasseling,
filling
stages
were
0.87,
0.86,
0.62,
respectively.
Moreover,
this
verified
significant
role
inversion,
providing
new
Язык: Английский
Development of a Drought Monitoring System for Winter Wheat in the Huang-Huai-Hai Region, China, Utilizing a Machine Learning–Physical Process Hybrid Model
Agronomy,
Год журнала:
2025,
Номер
15(3), С. 696 - 696
Опубликована: Март 13, 2025
Droughts,
intensified
by
climate
change
and
human
activities,
pose
a
significant
threat
to
winter
wheat
cultivation
in
the
Huang-Huai-Hai
(HHH)
region.
Soil
moisture
drought
indices
are
crucial
for
monitoring
agricultural
droughts,
while
challenges
such
as
data
accessibility
soil
heterogeneous
necessitate
use
of
numerical
simulations
their
effective
regional-scale
applications.
The
existing
simulation
methods
like
physical
process
models
machine
learning
(ML)
algorithms
have
limitations:
struggle
with
parameter
acquisition
at
regional
scales,
ML
face
difficulties
settings
due
presence
crops.
As
more
advanced
complex
branch
ML,
deep
even
greater
limitations
related
crop
growth
management.
To
address
these
challenges,
this
study
proposed
novel
hybrid
system
that
merged
model.
Initially,
we
employed
Random
Forest
(RF)
regression
model
integrated
multi-source
environmental
factors
estimate
prior
sowing
wheat,
achieving
an
average
coefficient
determination
(R2)
0.8618,
root
mean
square
error
(RMSE)
0.0182
m3
m−3,
absolute
(MAE)
0.0148
m−3
across
eight
depths.
RF
provided
vital
parameters
operation
Water
Balance
Winter
Wheat
(WBWW)
scale,
enabling
assessments
combined
Moisture
Anomaly
Percentage
Index
(SMAPI).
Subsequent
comparative
analyses
between
system-generated
results
actual
disaster
records
during
two
events
highlighted
its
efficacy.
Finally,
utilized
examine
spatiotemporal
variations
patterns
HHH
region
over
past
decades.
findings
revealed
overall
intensification
conditions
decline
SMAPI
rate
−0.021%
per
year.
Concurrently,
there
has
been
shift
patterns,
characterized
increase
both
frequency
extremity
events,
duration
intensity
individual
decreased
majority
Additionally,
identified
northeastern,
western,
southern
areas
requiring
concentrated
attention
targeted
intervention
strategies.
These
efforts
signify
notable
application
fusion
techniques
integration
within
big
context,
thereby
facilitating
prevention,
management,
mitigation
Язык: Английский
Driving mechanisms and threshold identification of landscape ecological risk: A nonlinear perspective from the Qilian Mountains, China
Ecological Indicators,
Год журнала:
2025,
Номер
173, С. 113342 - 113342
Опубликована: Март 26, 2025
Язык: Английский
Analysis of Vegetation Changes and Driving Factors on the Qinghai-Tibet Plateau from 2000 to 2022
Forests,
Год журнала:
2024,
Номер
15(12), С. 2188 - 2188
Опубликована: Дек. 12, 2024
This
study
assesses
the
impact
of
climate
change
and
human
activities
on
vegetation
dynamics
(kNDVI)
Qinghai-Tibet
Plateau
(QTP)
between
2000
2022,
considering
both
lag
cumulative
effects.
Given
QTP’s
high
sensitivity
to
activities,
it
is
imperative
understand
their
effects
for
sustainable
development
regional
national
terrestrial
ecosystems.
Using
MOD13Q1
NDVI
activity
data,
we
applied
methods
such
as
Sen-MK,
effect
analysis,
improved
residual
geographical
detector
analysis.
The
outcomes
were
follows.
(1)
kNDVI
QTP
showed
an
overall
fluctuating
growth
trend
2022;
regions
more
significant
than
degraded
regions,
with
primarily
distributed
in
humid
semi-humid
areas
favorable
conditions,
arid
semi-arid
areas;
this
implies
that
conditions
have
a
changes
QTP.
(2)
analysis
revealed
temperature
precipitation
substantial
0
months
1
month
temperature,
2
precipitation,
respectively.
(3)
Improved
based
positively
contributed
66%
QTP,
suggesting
notable
positive
activities.
Geographical
indicated
that,
among
different
factors
affecting
changes,
explanatory
power
2005
2015
ranked
X3
(livestock
density)
>
X1
(population
X2
(per
capita
GDP)
X4
(artificial
afforestation
X5
(land
use
type),
2020,
X2.
density
land
type
has
relatively
increased,
indicating
recent
efforts
ecological
protection
restoration
including
developing
artificial
forest
programs,
considerably
greening.
Язык: Английский