Remote Sensing,
Journal Year:
2023,
Volume and Issue:
15(8), P. 2029 - 2029
Published: April 11, 2023
The
interactions
between
human
activities
and
land
cover
have
a
significant
impact
on
ecosystems.
Therefore,
studying
activity
intensity
based
use
or
is
crucial
for
understanding
the
sustainable
development
of
In
this
study,
we
selected
Anhui
Province
as
study
area
estimated
surface
(HAILS)
in
2015
2020
ChinaCover
datasets.
We
further
analyzed
spatial,
slope,
hydrological
distribution
characteristics
HAILS
explored
drivers
changes.
results
show
that
areas
with
higher
were
mainly
located
central
part
Hefei,
well
along
Yangtze
Huaihe
rivers.
largest
changes
from
to
happened
gentle
slopes
20–30%,
percentage
>
20%
decreased
over
slope
15°.
riparian
zone,
showed
clear
decreasing
trend
after
2
km,
while
than
each
flow-path
distance
belt,
except
river.
index
was
strongly
correlated
population
density,
rural
urban
average
GDP
primary
industry,
nighttime
light
data.
rapid
growth
economy,
ecological
protection
policies,
identified
above
provide
effective
data
support
address
regional
conservation
issues.
Ecological Informatics,
Journal Year:
2024,
Volume and Issue:
81, P. 102641 - 102641
Published: May 8, 2024
The
middle
reaches
of
the
Yellow
River
basin
(MYRB)
are
among
regions
most
severely
affected
by
soil
erosion
globally.
It
has
always
held
a
pivotal
role
in
and
water
conservation
ecological
restoration
efforts
China.
Nonetheless,
face
recurrent
drought
occurrences
growing
human
intervention,
there
have
been
notable
alterations
eco-environmental
quality
(EEQ)
within
MYRB.
However,
influences
intervention
on
EEQ
MYRB
remain
unclear.
In
this
study,
remote
sensing
index
(RSEI)
was
applied
to
quantify
spatiotemporal
changes
contributions
land
use
type
transitions
from
1990
2022.
results
showed
that
fluctuated
significantly
exhibited
weak
overall
improvement
trend
over
past
33
years.
proportion
good
excellent
grades
for
improved,
while
poor
fair
decreased,
especially
northern
regions.
follows
phased
pattern.
During
periods
1990–2002
2011–2022,
an
improving
is
observed,
period
2003–2010
shows
no
significant
change
EEQ.
Drought
had
strongest
influence
2003
2010,
followed
2002,
lesser
impact
2011
primarily
positively
influenced
spring,
autumn
winter
droughts
negatively
summer
droughts,
arid
grassland
unused
areas.
improved
during
initial
final
phases
projects,
with
drought.
increase
project
implementation
less
noticeable,
period.
Forests,
Journal Year:
2023,
Volume and Issue:
14(3), P. 620 - 620
Published: March 20, 2023
The
Yellow
River
Basin
(YRB)
is
a
fundamental
ecological
barrier
in
China
and
one
of
the
regions
where
environment
relatively
fragile.
Studying
spatio-temporal
variations
vegetation
coverage
YRB
their
driving
factors
through
long-time-series
dataset
great
significance
to
eco-environmental
construction
sustainable
development
YRB.
In
this
study,
we
sought
characterize
variation
its
climatic
from
2001
2020
by
constructing
new
kernel
normalized
difference
index
(kNDVI)
based
on
MOD13
A1
V6
data
Google
Earth
Engine
(GEE)
platform.
Using
Theil–Sen
median
trend
analysis,
Mann–Kendall
test,
Hurst
exponent,
investigated
characteristics
future
trends
coverage.
were
obtained
via
partial
correlation
analysis
complex
associations
between
kNDVI
both
temperature
precipitation.
results
reveal
following:
spatial
distribution
pattern
showed
that
was
high
southeast
low
northwest.
Vegetation
fluctuated
2020,
with
main
significant
increasing
growth
at
rate
0.0995/5a.
response
strong
YRB,
stronger
precipitation
than
temperature.
Additionally,
found
be
non-climatic
factors,
which
mainly
distributed
Henan,
southern
Shaanxi,
Shanxi,
western
Inner
Mongolia,
Ningxia,
eastern
Gansu.
areas
driven
northern
Shandong,
Qinghai,
Gansu,
northeastern
Sichuan.
Our
findings
have
implications
for
ecosystem
restoration
Remote Sensing,
Journal Year:
2024,
Volume and Issue:
16(4), P. 682 - 682
Published: Feb. 14, 2024
As
a
region
susceptible
to
the
impacts
of
climate
change,
evaluating
temporal
and
spatial
variations
in
ecological
environment
quality
(EEQ)
potential
influencing
factors
is
crucial
for
ensuring
security
Tibetan
Plateau.
This
study
utilized
Google
Earth
Engine
(GEE)
platform
construct
Remote
Sensing-based
Ecological
Index
(RSEI)
examined
dynamics
Plateau’s
EEQ
from
2000
2022.
The
findings
revealed
that
RSEI
Plateau
predominantly
exhibited
slight
degradation
trend
2022,
with
multi-year
average
0.404.
Utilizing
SHAP
(Shapley
Additive
Explanation)
interpret
XGBoost
(eXtreme
Gradient
Boosting),
identified
natural
as
primary
influencers
on
Plateau,
temperature,
soil
moisture,
precipitation
variables
exhibiting
higher
values,
indicating
their
substantial
contributions.
interaction
between
temperature
showed
positive
effect
RSEI,
value
increasing
rising
precipitation.
methodology
results
this
could
provide
insights
comprehensive
understanding
monitoring
dynamic
evolution
amidst
context
change.
Land,
Journal Year:
2024,
Volume and Issue:
13(2), P. 222 - 222
Published: Feb. 10, 2024
Considering
climate
change
and
increasing
human
impact,
ecological
quality
its
assessment
have
also
received
attention.
Taking
the
Irtysh
River
Basin
as
an
example,
we
utilize
multi-period
MODIS
composite
imagery
to
obtain
five
factors
(greenness,
humidity,
heat,
dryness,
salinity)
construct
model
for
amended
RSEI
(ARSEI)
based
on
Google
Earth
Engine
platform.
We
used
Otsu
algorithm
generate
dynamic
thresholds
improve
accuracy
of
ARSEI
results,
performed
spatiotemporal
pattern
evolutionary
trend
analysis
explored
influencing
quality.
Results
indicate
that:
(1)
The
demonstrates
a
correlation
exceeding
0.88
with
each
indicator,
offering
efficient
approach
characterizing
exhibits
significant
spatial
heterogeneity,
demonstrating
gradual
enhancement
from
south
north.
(2)
To
evaluate
Basin,
was
utilized,
exposing
stable
condition
slight
fluctuations.
In
current
research
context,
watershed
area
is
projected
continuously
enhance
in
future.
This
due
constant
protection
management
initiatives
carried
out
by
countries
within
basin.
(3)
Precipitation,
soil
pH,
elevation,
population
are
main
Due
driving
different
classes
vary.
Overall,
effective
method
assessment,
findings
can
provide
references
environment
protection,
management,
sustainable
development.
Ecological Indicators,
Journal Year:
2023,
Volume and Issue:
154, P. 110544 - 110544
Published: June 26, 2023
The
ecosystem
services
value
(ESV)
is
an
important
basis
for
measuring
ecological
environment
quality
and
efficient
management
of
ecosystems.
Although
there
have
been
many
studies
devoted
to
the
measurement
ESV,
research
on
key
influencing
factors
ESV
prediction
future
development
scenarios
still
limited.
This
study
coupled
Deep
Forest
model
Patch-generating
Land
Use
Simulation
(PLUS)
identify
simulated
change
trend
under
Shared
Socioeconomic
Pathways
(SSPs).
Taking
cluster
cities
around
Yellow
River
floodplain
area
as
object,
this
quantitatively
analyzed
spatiotemporal
evolution
characteristics
its
from
2000
2020,
identified
affecting
using
model.
results
showed
that:
(1)
overall
upward
with
strong
spatial
heterogeneity;
(2)
were
construction
land
ratio,
distance
railway,
SHDI,
etc.;
(3)
best
pathway
in
2025,
2030
2035
would
be
SSPs5,
SSPs2
SSPs4
respectively.
can
provide
theoretical
support
maximizing
benefits
area.
International Journal of Applied Earth Observation and Geoinformation,
Journal Year:
2023,
Volume and Issue:
125, P. 103564 - 103564
Published: Nov. 16, 2023
Accurately
identifying
and
systematically
mapping
winter-time
cover
crops
their
phenological
characteristics
offer
significant
benefits
to
agricultural
producers
policymakers,
as
are
one
of
several
potential
solutions
climate
change
mitigation.
We
present
a
methodological
framework
for
the
presence
at
field
level
aggregated
county
scales
from
2013
2019
by
using
Google
Earth
Engine
(GEE),
random
forest
classifier
with
time
series
data
Landsat
8,
yearly
crop
training
United
States
Department
Agriculture
(USDA)-Natural
Resources
Conservation
Service
(NRCS).
The
methodology
was
tested
Mississippi
Alluvial
Plain
(MAP)
region.
Despite
inter-annual
agronomic
climatic
variations
across
space,
results
demonstrated
an
overall
mean
classification
accuracy
97.7%,
kappa
coefficient
0.94.
Results
also
revealed
34%
increase
in
model-predicted
adoption
study
region
2019.
Based
on
GEE,
this
created,
first
time,
30-m
spatial
temporal
resolution
binary
annual
datasets
then
them
within
MAP
This
multi-year
novel
dataset
may
improve
our
ability
anticipate
quantify
impact
summer
production
gains
owing
extended
periods
evaluate
local
soil
ecosystems,
biogeochemical
cycles,
services.
developed
broadly
applies
other
regions
where
have
been
promoted
climate-change
mitigation
improving
health
long-term
sustainability.
Agricultural
producers,
cost-share
providers
use
information
develop
conservation
methods
land-use
policies
that
minimize
erosion
help
mitigate
effects
long
run.
