Spatio-temporal characteristics and driving factors of cultivated land change in various agricultural regions of China: A detailed analysis based on county-level data
Ecological Indicators,
Год журнала:
2024,
Номер
166, С. 112485 - 112485
Опубликована: Авг. 10, 2024
Язык: Английский
Advancing ecological quality assessment in China: Introducing the ARSEI and identifying key regional drivers
Ecological Indicators,
Год журнала:
2024,
Номер
163, С. 112109 - 112109
Опубликована: Май 15, 2024
Accurate
analysis
of
regional
ecological
quality
and
its
drivers
is
crucial
for
the
sustainable
development
human
society.
The
remote
sensing
eco-index
(RSEI)
has
been
widely
used
to
monitor
changes
in
many
countries
or
regions,
but
it
ignores
problem
declining
air
caused
by
economic
population
growth.
Consequently,
an
improved
remotely
sensed
index
(ARSEI)
was
developed
evaluate
China's
environment
incorporating
aerosol
optical
depth
(AOD)
into
system.
Additionally,
a
random
forest
regression
model
rank
importance
indexes
ARSEI.
Furthermore,
geographical
detector
utilized
assess
impact
natural
socioeconomic
factors
on
spatial
heterogeneity
ARSEI
six
geographic
regions
China,
identifying
their
primary
drivers.
research
findings
revealed
following:
(1)
There
are
similarities
differences
order
indicators
across
regions.
(2)
values
significantly
increased
24.70%
areas,
primarily
Northeast
Plain,
Loess
Plateau,
Tarim
Basin,
while
they
decreased
5.35%
mainly
Qinghai-Tibetan
northern
part
Tianshan
Mountains,
eastern
coastal
cities,
central
urban
agglomerations.
(3)
Rainfall
vegetation
conditions
main
affecting
environmental
Three-North
region
(XB,
HB
DB).
In
southern
(XN,
ZN
HD)
cover
land
use
change,
density
PM2.5
concentrations
were
greater
than
influence
climate
factors.
interaction
factors,
including
PM2.5,
had
results
this
study
can
provide
data
support
coordinated
ecosystems
socioeconomics.
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
Exploration of the utilization of a new land degradation index in Lake Ebinur Basin in China
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Июль 30, 2024
Land
degradation
significantly
impacts
regional
economic
development
and
food
security,
particularly
in
arid
river
basins
where
soil
water
conservation
is
crucial.
Understanding
the
extent
causes
of
land
pivotal
for
effectively
prevention
management.
This
study
employs
adjusted
vegetation
index
(SAVI),
temperature
dryness
(TVDI),
salinization
detection
(SDI),
combined
with
analytic
hierarchy
process
entropy
weight
method,
to
construct
a
comprehensive
(LDI).
Sen's
slope
trend
analysis
Mann-Kendall
significance
test
were
used
analyze
trends
Ebinur
Lake
watershed
from
2002
2022.
Additionally,
optimal
parameters-based
geographical
detector
was
examine
underlying
mechanisms
degradation.
The
results
indicate
following:
(1)
From
2012,
degree
worsened,
eastern
southeastern
parts,
as
well
southern
region
Toli
County.
2012
2022,
improved,
notable
reduction
degraded
area.
(2)
Over
period
2002-2022,
$$93.08\%$$
research
exhibited
declining
LDI
trend,
$$3.95\%$$
showed
no
change,
only
$$2.96\%$$
an
increasing
trend.
(3)
Moderate,
severe,
very
severe
mainly
occurred
on
grassland
unused
land,
while
light
non-degradation
primarily
forest
cultivated
land.
(4)
Unreasonable
use
overgrazing
identified
primary
factors
influencing
degradation,
elevation
being
secondary
factor.
interaction
between
other
found
be
most
significant,
followed
by
synergistic
effects
grazing
quantity
elevation,
annual
average
temperature,
gross
domestic
product,
moisture,
precipitation,
temperature.
this
offer
empirical
basis
taking
decisions
assistance
control
Basin,
examples
references
assessing
places.
Язык: Английский