Land,
Год журнала:
2024,
Номер
13(11), С. 1840 - 1840
Опубликована: Ноя. 5, 2024
Fractional
vegetation
cover
(FVC)
plays
a
key
role
in
ecological
and
environmental
status
assessment
because
it
directly
reflects
the
extent
of
its
status,
yet
is
an
important
component
ecosystems.
FVC
estimation
methods
have
evolved
from
traditional
manual
interpretation
to
advanced
remote
sensing
technologies,
such
as
satellite
data
analysis
unmanned
aerial
vehicle
(UAV)
image
processing.
Extraction
based
on
high-resolution
UAV
are
being
increasingly
studied
fields
ecology
sensing.
However,
research
UAV-based
extraction
against
backdrop
high
soil
reflectance
arid
regions
remains
scarce.
In
this
paper,
12
visible
light
images
differentiated
scenarios
Ebinur
Lake
basin,
Xinjiang,
China,
various
used
for
high-precision
estimation:
Otsu’s
thresholding
method
combined
with
Visible
Vegetation
Indices
(abbreviated
Otsu-VVIs)
(excess
green
index,
excess
red
minus
normalized
green–red
difference
green–blue
red–green
ratio
color
index
extraction,
visible-band-modified
soil-adjusted
modified
red–green–blue
visible-band
index),
space
(red,
green,
blue,
hue,
saturation,
value,
lightness,
‘a’
(Green–Red
component),
‘b’
(Blue–Yellow
component)),
linear
mixing
model
(LMM),
two
machine
learning
algorithms
(a
support
vector
neural
network).
The
results
show
that
following
exhibit
accuracy
across
scenarios:
Otsu–CIVE,
(‘a’:
Green–Red
LMM,
SVM
(Accuracy
>
0.75,
Precision
0.8,
kappa
coefficient
0.6).
Nonetheless,
higher
scene
complexity
entropy
reduce
applicability
precise
methods.
This
study
facilitates
accurate,
efficient
information
within
semiarid
regions,
providing
technical
references
similar
areas.
Ecological Indicators,
Год журнала:
2024,
Номер
159, С. 111639 - 111639
Опубликована: Янв. 27, 2024
Since
the
21st
century,
China
has
shown
dramatic
rural
depopulation
and
rapid
urbanization,
surface
vegetation
been
affected
by
this
urban–rural
development
pattern.
Using
remote
sensing
population
data
from
2000
to
2020,
we
investigated
spatial
temporal
evolution
of
terrestrial
under
coexistence
“rural
loss
urbanization”.
We
also
analyzed
relationship
between
loss,
urbanization
area
covered
four
types
(forest,
grassland,
shrubs
cropland).
found
that
forests
is
increasing,
shrubs,
grasslands,
cropland
decreasing.
Spatially,
results
Moran
index
prove
characterized
autocorrelation.
Grasslands
are
predominantly
located
on
western
side
Hu
line,
forests,
croplands
eastern
line.
Rural
contributes
growth
forest
grassland
cover,
but
inhibits
shrub
cover.
The
advance
reduces
benefits
As
a
result
direct
effect,
reduction
cropland,
while
promotes
opposite
true
for
spillover
effect.
This
study
helps
us
better
understand
direction
ecological
shifts
in
migration
patterns.
Ecological Informatics,
Год журнала:
2024,
Номер
81, С. 102630 - 102630
Опубликована: Май 5, 2024
The
Normalized
Difference
Vegetation
Index
(NDVI)
is
the
most
commonly
used
index
for
assessing
vegetation.
However,
significant
differences
among
various
satellite
datasets,
complex
terrain,
and
impact
of
clouds
on
optical
sensors
limit
vegetation
change
assessment
based
NDVI.
To
address
these
issues,
this
study
utilizes
multi-source
data
(GIMMS3g
NDVI,
CDR
AVHRR
SPOT
MODIS
NDVI)
to
monitor
dynamics
at
different
time
scales
from
1990
2020
in
Sichuan
Province,
China.
results
indicate
that
over
time,
NDVI
values
four
products
Province
have
shown
an
upward
trend.
There
are
certain
spatial
distribution
heterogeneity
rate
scales,
mainly
concentrated
Basin
(SB)
Western
alpine
plateau
region
(WS).
Compared
with
other
three
products,
GIMMS
has
highest
value
but
smallest
increase
during
period.
smallest,
relatively
large.
within
overlapping
period
only
annual
average
showed
a
downward
trend
(slope2000–2013
=
−0.0001·a−1).
fluctuation
compared
its
correlation
climate
factors
shows
significantly
weaker
variability.
Moreover,
ability
distinguish
land
cover
types
poor
(STD
0.045).
findings
will
provide
reference
further
research
changes
reconstruction
cloudy
areas.
Remote Sensing,
Год журнала:
2024,
Номер
16(5), С. 790 - 790
Опубликована: Фев. 24, 2024
Vegetation
greening
is
time-dependent
and
region-specific.
The
uncertainty
of
vegetation
under
global
warming
has
been
highlighted.
Thus,
it
crucial
to
investigate
its
response
climate
change
at
the
regional
scale.
Yellow
River
Basin
(YRB)
a
vital
ecological
barrier
in
China
with
high
vulnerability
climatic
sensitivity.
relationship
between
YRB
relative
contribution
remain
be
explored.
Using
Enhanced
Index
(EVI)
meteorological
observation
data,
spatiotemporal
patterns
across
basin
sub-regional
scales
from
2000
2020
were
analyzed.
impact
human
activities
on
was
further
quantified.
Results
showed
that
approximately
92%
had
experienced
greening,
average
annual
growing
season
rates
0.0024
0.0034
year–1,
respectively.
Greening
particularly
prominent
central
eastern
YRB.
Browning
more
prevalent
urban
areas
intensity
activities,
occupying
less
than
6.3%
total
basin,
but
this
proportion
increased
significantly
seasonal
scales,
especially
spring.
Regional
positively
correlated
overall
warmer
wetter
climate,
partial
correlation
coefficients
EVI
precipitation
higher
those
temperature.
However,
varied
among
different
sub-regions.
combined
effects
conducive
84.5%
during
season,
while
stronger
change.
contributions
browning
65.15%
70.30%,
respectively,
mainly
due
promotion
rehabilitation
programs
inhibition
urbanization
construction
projects.
Forests,
Год журнала:
2024,
Номер
15(2), С. 231 - 231
Опубликована: Янв. 25, 2024
Examining
the
features
of
vegetation
change
and
analyzing
its
driving
forces
across
an
extensive
time
series
in
Xinjiang
are
pivotal
for
ecological
environment.
This
research
can
offer
a
crucial
point
reference
regional
conservation
endeavors.
We
calculated
fractional
cover
(FVC)
using
MOD13Q1
data
accessed
through
Google
Earth
Engine
(GEE)
platform.
To
discern
characteristics
changes
forecast
future
trends,
we
employed
analysis,
coefficient
variation,
Hurst
exponent.
The
correlation
between
climate
factors
FVC
was
investigated
analysis.
Simultaneously,
to
determine
relative
impact
meteorological
anthropogenic
actions
on
FVC,
utilized
multiple
regression
residual
Furthermore,
adhering
China’s
functional
zone
classification,
segmented
into
five
zones:
R1
Altai
Mountains-Junggar
West
Mountain
Forest
Grassland
Ecoregion,
R2
Junggar
Basin
Desert
R3
Tianshan
Mountains
R4
Tarim
Basin-Eastern
Frontier
R5
Pamir-Kunlun
Mountains-Altan
Alpine
Ecoregion.
A
comparative
analysis
these
regions
subsequently
conducted.
results
showed
following:
(1)
During
first
two
decades
21st
century,
overall
primarily
exhibited
trend
growth,
exhibiting
rate
increase
4
×
10−4
y−1.
multi-year
average
0.223.
mean
value
0.223,
values
different
zones
following
order:
>
R4.
(2)
predominant
spatial
pattern
Xinjiang’s
landscape
is
characterized
by
higher
coverage
northwest
lower
southeast.
In
this
region,
66.63%
terrain
exhibits
deteriorating
vegetation,
while
11%
region
notable
rise
plant
growth.
Future
will
be
dominated
decreasing
trend.
Regarding
variation
outcomes,
minor
representing
42.12%
total,
noticeable;
stands
at
0.2786.
stability
varied
follows
R5.
(3)
Factors
that
have
facilitating
effect
included
humidity,
daylight
hours,
precipitation,
with
humidity
having
greater
influence,
hindering
air
temperature
wind
speed,
speed
influence.
(4)
Vegetation
alterations
influenced
change,
human
activities
play
secondary
role,
contributing
56.93%
43.07%,
respectively.
underscores
necessity
continued
surveillance
dynamics
enhancement
policies
focused
habitat
renewal
safeguarding
Xinjiang.
