Environmental and Sustainability Indicators,
Год журнала:
2024,
Номер
22, С. 100372 - 100372
Опубликована: Фев. 29, 2024
Quantitatively
investigating
and
assessing
the
spatiotemporal
variation
in
human
activity
intensity
(HAI)
its
influencing
factors
are
crucial
for
coordinating
regional
human–land
relationships
protecting
eco-environment.
However,
scale,
pattern,
driving
of
Guangxi
Beibu
Gulf
Zone
have
not
yet
been
determined.
To
bridge
this
gap,
study
focused
on
evaluating
analyzing
characteristics
HAI
from
2000
to
2020
by
a
quantitative
model
based
multi-period
land
use
data,
field
survey
statistical
data.
Moreover,
socioeconomic
geographical
determinants
were
investigated
using
PCA
method
Geodetector
model.
The
results
showed
that
(1)
overall
value
was
relatively
high
increased
18.97%
20.06%
2020.
Haicheng
District
always
highest
peaked
at
60.78%
(2)
Spatially,
approximately
19.88%
area
exhibited
values,
these
areas
mainly
distributed
urban
districts,
county
seats,
towns,
farming
areas.
In
contrast,
with
low
values
concentrated
mountainous
natural
reserves.
(3)
significant
spatial
agglomeration
effect,
hot
spots
intense
change,
such
as
economic
development
zones,
industrial
parks,
suburbs,
towns
added
counties.
(4)
affected
various
factors,
explanatory
power
multiple
change
greater
than
single
factor.
Remote Sensing,
Год журнала:
2025,
Номер
17(3), С. 488 - 488
Опубликована: Янв. 30, 2025
Net
primary
productivity
(NPP)
is
a
core
ecological
indicator
within
terrestrial
ecosystems,
representing
the
potential
of
vegetation
growth
to
offset
anthropogenic
carbon
emissions.
Thus,
assessing
NPP
in
given
region
crucial
for
promoting
regional
restoration
and
sustainable
development.
This
study
utilized
CASA
model
GEE
calculate
annual
average
Shandong
Province
(2001–2020).
Through
trend
analysis,
Moran’s
Index,
PLS−SEM,
spatiotemporal
evolution
driving
factors
were
explored.
The
results
show
that:
(1)
From
2001
2020,
showed
an
overall
increasing
trend,
rising
from
254.96
322.49
g
C·m⁻2/year.
shift
was
accompanied
by
gradual
eastward
movement
centroid,
indicating
significant
spatial
changes
productivity.
(2)
Regionally,
47.9%
experienced
improvement,
27.6%
saw
slight
20.1%
exhibited
degradation,
highlighting
notable
heterogeneity.
(3)
Driver
analysis
that
climatic
positively
influenced
across
all
four
periods
(2005,
2010,
2015,
2020),
with
strongest
impact
2015
(coefficient
=
0.643).
Topographic
such
as
elevation
slope
also
had
positive
effects,
peaking
at
0.304
2015.
In
contrast,
human
activities,
especially
GDP
nighttime
light
intensity,
negatively
impacted
NPP,
negative
effect
2010
−0.567).
These
findings
provide
valuable
scientific
evidence
ecosystem
management
offer
key
insights
development
strategies
national
level.
Remote Sensing,
Год журнала:
2024,
Номер
16(4), С. 682 - 682
Опубликована: Фев. 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.
