Spatiotemporal Differentiation and Attribution Analysis of Ecological Vulnerability in Heilongjiang Province, China, 2000–2020
Sustainability,
Год журнала:
2025,
Номер
17(5), С. 2239 - 2239
Опубликована: Март 4, 2025
Heilongjiang
Province,
a
major
grain-producing
region
in
China,
faces
ecological
vulnerabilities
that
directly
affect
its
sustainable
development.
A
scientific
assessment
of
the
spatiotemporal
characteristics
vulnerability
and
influencing
factors
is
crucial
for
deeper
understanding
environmental
issues
provides
theoretical
support
enhancing
regional
governance
capabilities.
The
SRP
model,
combined
with
AHP-CRITIC
weighting
method,
was
employed
to
assess
Province’s
vulnerability’s
temporal
differentiation
trends
between
2000
2020.
aggregation
kinds
were
examined
using
spatial
autocorrelation.
GeoDetector
used
determine
main
elements
affecting
province.
Additionally,
status
2030
predicted
CA-Markov
model.
findings
indicate
(1)
average
EVI
values
Province
during
three
periods
0.323,
0.317,
0.347,
respectively,
indicating
medium
level
across
province;
initially
decreased
then
worsened.
Spatially,
distribution
followed
pattern
“high
east
west,
low
north
south”.
(2)
Spatial
agglomeration
evident,
high-high
(H-H)
primarily
occurring
heavily
extremely
vulnerable
areas
characterized
by
high
human
activity,
while
low–low
(L-L)
mainly
found
mildly
marginally
favorable
natural
background.
(3)
Biological
abundance,
net
primary
productivity,
dry
degree,
PM2.5
drivers
vulnerability,
interactions
these
amplifying
their
impact
on
vulnerability.
(4)
model
prediction
results
indicated
an
upward
trend
overall
2030,
reflecting
decline
environment.
study
indicates
closely
linked
geographic
conditions
influenced
through
interplay
several
elements.
Based
zoning
results,
this
paper
proposes
recommendations
regions
different
levels,
aiming
provide
future
restoration
Язык: Английский
Investigating the urban eco-environmental quality utilizing remote sensing based approach: evidence from an industrial city of Eastern India
Deleted Journal,
Год журнала:
2024,
Номер
6(12)
Опубликована: Дек. 4, 2024
Urbanization,
coupled
with
industrialization,
leads
to
both
economic
growth
and
exponential
urban
growth,
resulting
in
deteriorating
environmental
quality
areas,
which
poses
a
significant
threat
the
sustainability
of
cities.
Hence,
restore
biodiversity
ensure
regional
sustainability,
it
is
necessary
immediately
evaluate
eco-environmental
areas.
The
present
research
investigates
spatio-temporal
changes
Asansol
industrial
city
using
an
integrated
'Urban
Eco-Environmental
Index'
(UEEQI)
developed
utilizing
Google
Earth
Engine
platform
remote
sensing-based
approach.
study
used
four
spectral
indices,
including
Normalized
Difference
Vegetation
Index
(NDVI),
Modified
Water
(MNDWI),
Built-up
(NDBI),
Bareness
(NDBaI),
along
Land
Surface
Temperature
(LST)
(as
thermal
index),
derived
from
sensing
data
measure
quality.
Global
Moran's
I
LISA
were
quantify
spatial
autocorrelation,
showing
clustering
similar
values
or
outliers
UEEQ
within
geographic
space.
findings
showed
that
high
mean
NDBI
NDBaI
contributed
lower
UEEQI
value
0.38
2021
compared
previous
decades.
distribution
'Very
Poor'
category
had
grown
0.06%
1991
2%
2021,
while
'Poor',
'Good',
'Excellent'
categories
declined.
Over
30
years,
rising
trend
'Highly
Degraded'
'Degraded'
areas
decreasing
'Improved'
Improved'
city.
scatter
plot
illustrated
highly
positive
clustered
pattern
across
Hotspots
mainly
found
urbanized
"Average"
eco-environment
Conversely,
covered
bare
surfaces,
fallow
lands,
brickfields
recognized
as
Coldspots.
This
crucial
for
determining
specific
regions
declining
encourages
local
authorities
decision-makers
integrate
conservation
zones
into
planning
foster
healthier,
more
resilient,
sustainable
Язык: Английский