Sustainability,
Год журнала:
2024,
Номер
16(21), С. 9595 - 9595
Опубликована: Ноя. 4, 2024
This
study
selected
the
five
indicators
of
soil
erosion,
climate
environment,
geological
hazards,
biodiversity,
and
human
disturbances
uses
entropy
weight
method
to
calculate
ecological
sensitivity
West
Qinling
Mountains
from
2000
2020.
The
analysis
produced
a
spatiotemporal
distribution
over
20-year
period.
An
equal
step
size
500
m
was
used
progressively
increase
spatial
scale
6
km.
optimal
for
differentiation
in
determined
by
analyzing
characteristics
changes
at
different
scales,
response
mechanisms,
parameters
geographical
detector
identification.
Based
on
this
scale,
change
intensity
pattern
influencing
factors
were
analyzed.
results
show
following:
(1)
5.5
km
balances
requirements
accuracy,
heterogeneity,
data
adequacy,
making
it
variation
patterns
Mountains.
(2)
From
2020,
mean
exhibited
decreasing
trend,
indicating
an
improvement
environment.
Spatially,
showed
“low
west
high
east,
low
south
north”.
During
period,
region
remained
generally
stable,
with
no
high-frequency
observed.
(3)
Population
density
is
primary
driving
factor
Mountains,
while
GDP
serves
as
secondary
factor.
Overall,
socioeconomic
have
most
significant
impact
sensitivity.
(4)
Over
75%
trends
exhibit
perennial
unchanged
fluctuating
trends,
areas
smaller
than
decrease.
Regions
are
primarily
concentrated
northeastern
part
increased
fluctuation
mainly
located
western
southern
parts
Future
efforts
should
focus
these
regions.
Sustainability,
Год журнала:
2024,
Номер
16(9), С. 3549 - 3549
Опубликована: Апрель 24, 2024
Investigating
the
spatial-temporal
evolution
of
land
use
and
its
driving
forces
provides
a
scientific
basis
for
policy
formulation,
land-use
structure
adjustment,
ecological
civilization
development.
Using
Google
Earth
Engine
(GEE)
platform,
this
study
analyzed
remote
sensing
images
from
2000,
2010,
2020
to
derive
basic
data
Putian
City
five
districts
counties.
These
were
then
systematically
using
methodologies
such
as
Single
Land-use
Dynamics
Geo-informatic
Tupu
reveal
characteristics
transitions
(LUTs),
pattern
over
past
two
decades
in
City,
China.
Subsequently,
socioeconomic
conditions
macro
policies
identified
factors
further
explore
mechanisms
behind
area
through
canonical
correspondence
analysis
(CCA).
The
findings
revealed
that:
(1)
predominant
consisted
mainly
cultivated
forest
land,
with
other
types
interspersed
within
them,
while
built-up
exhibited
continual
outward
expansion.
(2)
Various
regions
varying
degrees
abandoned
farmland,
ultimately
transforming
into
wasteland
(grassland)
weed
growth,
presenting
significant
challenges
ensuring
food
security
mitigating
conversion
non-agricultural
non-grain
uses.
(3)
Specific
macro-economic
development
objectives
during
distinct
periods,
particularly
urban
expansion
growth
secondary
industry
resulting
municipal
county
mergers,
emerged
pivotal
spatial
temporal
influenced
differential
distribution
across
City.
Consequently,
suggests
bolstering
planning
implementing
effective
regulations
concerning
use,
it
advocates
efficient
utilization
space-time
resources
pertaining
integrating
them
agriculture,
culture,
tourism
endeavors.
Such
measures
are
proposed
ensure
harmonized
sustainable
regional
economy.
Applied Sciences,
Год журнала:
2024,
Номер
14(11), С. 4554 - 4554
Опубликована: Май 25, 2024
Human
actions
have
led
to
consistent
and
profound
alterations
in
land
use,
which
turn
had
a
notable
effect
on
the
services
provided
by
ecosystems.
In
this
research,
Google
Earth
Engine
(GEE)
was
initially
employed
perform
supervised
classification
of
Landsat
satellite
images
from
2000
2020,
allowed
us
obtain
land-use
data
for
Putian
City,
China.
Next,
geo-informatic
Tupu
model
revised
valuation
were
used
explore
spatial
attributes
ecological
effects
changes
(LUCs).
Subsequently,
EEH
(eco-economic
harmony),
ESTD
(ecosystem
tradeoffs
synergies
degree
index),
ESDA
(exploratory
analysis)
methods
further
analyze
coordination
level,
trade-offs,
synergies,
patterns
ecological-economic
system
development.
The
findings
revealed
that:
(1)
composition
City
predominantly
cultivated
forest
land,
with
other
types
intermixed.
Concurrently,
there
an
ongoing
trend
expansion
urban
areas.
(2)
ESV
exhibited
upward
trend,
increasing
15.4
billion
CNY
23.1
2020.
(3)
imbalance
distribution,
high-high
agglomeration
areas
concentrated
central
part
coastal
region
Hanjiang
District,
while
low-low
prevalent
Xianyou
County
southwest,
Xiuyu
District
along
coast,
Licheng
center.
(4)
Synergistic
relationships
among
ESs
predominated,
though
trade-off
relationship
showed
tendency
expand.
(5)
environment
economic
progress
collectively
faced
potential
risk.
study
are
intended
serve
as
guide
improving
distribution
resources
developing
strategies
that
ensure
sustainable
development
region’s
socio-economic
framework.
Journal of Hydrology Regional Studies,
Год журнала:
2024,
Номер
54, С. 101874 - 101874
Опубликована: Июнь 26, 2024
Yellow
River
Basin
(YRB)
in
China.
This
study
attempts
to
shed
new
light
on
regional
land-atmosphere
coupling
and
relevant
impacts
basin-scale
water
resource
management.
Specifically,
the
objectives
are
investigate
driving
factors
physical
mechanisms
of
SM
changes
via
coupling.
Ecological
conservation
high-quality
development
YRB
stand
as
a
pivotal
national
strategy.
The
equilibrium
availability
(PME,precipitation
minus
evapotranspiration)
poses
significant
challenge
sustainability
basin's
ecosystem.
Unfortunately,
comprehensive
examination
response,
spatiotemporal
heterogeneity,
mechanism
governing
soil
moisture
(SM)
response
PME
remains
limited.
An
enhanced
multiple
linear
regression
method
is
implemented
quantify
monthly
sensitivity
coefficients,
revealing
notable
correlation:
reduced
arid
regions
correlates
with
heightened
PME.
decline
triggers
decrease
evapotranspiration,
attenuates
cooling
effect
amplifies
temperature
disparities.
Consequently,
this
process
results
an
intensified
boundary
layer
tropospheric
ascending
motion,
thereby
increasing
vapor
transport.
feedback
loop
most
pronounced
during
drought
conditions,
particularly
summer
areas
(sensitivity
coefficient
=-0.27).
findings
underscore
intricate
interplay
between
land
atmosphere,
elucidating
discernible
impact
climate
change
resources
at
sub-basin
scale.
Land,
Год журнала:
2024,
Номер
13(8), С. 1149 - 1149
Опубликована: Июль 27, 2024
The
level
of
coordination
between
cultural,
ecological,
and
economic
systems
directly
affects
the
sustainable
development
Yellow
River
Basin
(YRB).
However,
researchers
have
neglected
importance
cultural
elements
in
social-ecological
system
paid
insufficient
attention
to
interaction
YRB.
Therefore,
a
framework
coupled
cultural-ecological-economic
(CEE)
was
constructed
based
on
service-dominant
logic,
spatiotemporal
distribution,
evolutionary
trends,
factors
influencing
different
76
major
cities
YRB
were
analyzed
by
using
an
entropy-weighted
TOPSIS
model,
spatial
Markov
chain,
panel
Dubin
model.
results
as
follows:
(1)
showed
growing
trend,
grew
faster
than
ecosystem,
ecosystems
dominated
(2)
From
2011
2022,
type
CEE
mainly
state
slight
incongruity,
with
regions
showing
temporal
consistency
synchronized
growth,
upstream
area
moderate
midstream
downstream
concentrating
general
coordination.
(3)
coupling
characteristic
“gradually
converging
from
downstream”
exhibited
low-value
agglomeration
high-value
agglomeration.
Meanwhile,
there
clear
trend
spillover
terms
balanced
regional
development,
67.11%
region
neighboring
areas
maintained
stable
development.
(4)
Tourism
(TD),
foreign
trade
(FT),
human
environment
(HE),
government
control
(GC),
other
significantly
positively
impacted
In
future,
focus
should
be
improving
transregional
infrastructure
transportation
service
YRB,
enhance
cooperation
exchanges
regions.
This
research
provides
new
insights
methods
for
coordinated
at
watershed
scale.
Sustainability,
Год журнала:
2024,
Номер
16(21), С. 9595 - 9595
Опубликована: Ноя. 4, 2024
This
study
selected
the
five
indicators
of
soil
erosion,
climate
environment,
geological
hazards,
biodiversity,
and
human
disturbances
uses
entropy
weight
method
to
calculate
ecological
sensitivity
West
Qinling
Mountains
from
2000
2020.
The
analysis
produced
a
spatiotemporal
distribution
over
20-year
period.
An
equal
step
size
500
m
was
used
progressively
increase
spatial
scale
6
km.
optimal
for
differentiation
in
determined
by
analyzing
characteristics
changes
at
different
scales,
response
mechanisms,
parameters
geographical
detector
identification.
Based
on
this
scale,
change
intensity
pattern
influencing
factors
were
analyzed.
results
show
following:
(1)
5.5
km
balances
requirements
accuracy,
heterogeneity,
data
adequacy,
making
it
variation
patterns
Mountains.
(2)
From
2020,
mean
exhibited
decreasing
trend,
indicating
an
improvement
environment.
Spatially,
showed
“low
west
high
east,
low
south
north”.
During
period,
region
remained
generally
stable,
with
no
high-frequency
observed.
(3)
Population
density
is
primary
driving
factor
Mountains,
while
GDP
serves
as
secondary
factor.
Overall,
socioeconomic
have
most
significant
impact
sensitivity.
(4)
Over
75%
trends
exhibit
perennial
unchanged
fluctuating
trends,
areas
smaller
than
decrease.
Regions
are
primarily
concentrated
northeastern
part
increased
fluctuation
mainly
located
western
southern
parts
Future
efforts
should
focus
these
regions.
