Land,
Год журнала:
2024,
Номер
13(12), С. 2195 - 2195
Опубликована: Дек. 16, 2024
The
rapid
expansion
of
cropland
in
Cambodia,
the
world’s
seventh-largest
rice
exporter,
has
created
an
imbalance
land
use
structure.
However,
there
is
a
lack
quantitative
investigation
loss
ecological
as
result
and
its
drivers.
In
this
research,
spatial
autocorrelation,
landscape
pattern
index
transfer
matrix
methods
were
used
based
on
data
from
2000
to
2023.
Then,
eXtreme
Gradient
Boosting-SHapley
Additive
exPlanations
(XGBoost-SHAP)
Geographic
Detector
explore
drivers
expansion.
findings
indicate
that
expanse
agricultural
Cambodia
significantly
increased
by
13.47%.
proportion
area
(37.87%)
close
forest
(40.19%).
Cultivated
dominated
fields,
supplemented
drylands.
Spatial
clustering
obvious
both
drylands
fields.
Drylands
are
mainly
concentrated
eastern
western
mountainous
areas
northern
border,
while
fields
central
plains.
encroached
total
30,579.27km2
land,
which
62.88%
was
dry
37.12%
Forests
shrubs
main
source
cropland.
addition,
soil
type
(0.18),
elevation
(0.17)
GDP
(0.17),
population
(0.52)
their
interactions
strongly
drove
dryland
should
conduct
scientific
research
assess
demand
for
growth
economic
progress.
It
realize
orderly
cultivated
reduce
damage
promote
coordinated
development
society,
environment
economy.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Янв. 11, 2025
Flash
flood
susceptibility
mapping
is
essential
for
identifying
areas
prone
to
flooding
events
and
aiding
decision-makers
in
formulating
effective
prevention
measures.
This
study
aims
evaluate
the
flash
Yarlung
Tsangpo
River
Basin
(YTRB)
using
multiple
machine
learning
(ML)
models
facilitated
by
H2O
automated
ML
platform.
The
best-performing
model
was
used
generate
a
map,
its
interpretability
analyzed
Shapley
Additive
Explanations
(SHAP)
tree
interpretation
method.
results
revealed
that
top
four
models,
including
both
single
ensemble
demonstrated
high
accuracy
tests.
map
generated
eXtreme
Randomized
Trees
(XRT)
showed
8.92%,
12.95%,
15.42%,
31.34%,
31.37%
of
area
exhibited
very
high,
moderate,
low,
low
susceptibility,
respectively,
with
approximately
74.9%
historical
floods
occurring
classified
as
moderate
susceptibility.
SHAP
plot
identified
topographic
factors
primary
drivers
floods,
importance
analysis
ranking
most
influential
such
descending
order
DEM,
wetness
index,
position
normalized
difference
vegetation
average
multi-year
precipitation.
demonstrates
benefits
interpretable
learning,
which
can
provide
guidance
mitigation.
Urban Science,
Год журнала:
2024,
Номер
8(3), С. 104 - 104
Опубликована: Авг. 1, 2024
Artificial
intelligence
(AI)
has
become
a
transformative
force
across
various
disciplines,
including
urban
planning.
It
unprecedented
potential
to
address
complex
challenges.
An
essential
task
is
facilitate
informed
decision
making
regarding
the
integration
of
constantly
evolving
AI
analytics
into
planning
research
and
practice.
This
paper
presents
review
how
methods
are
applied
in
studies,
focusing
particularly
on
carbon
neutrality
We
highlight
already
being
used
generate
new
scientific
knowledge
interactions
between
human
activities
nature.
consider
conditions
which
advantages
AI-enabled
studies
can
positively
influence
decision-making
outcomes.
also
importance
interdisciplinary
collaboration,
responsible
governance,
community
engagement
guiding
data-driven
suggest
contribute
supporting
carbon-neutrality
goals.
Land,
Год журнала:
2025,
Номер
14(4), С. 765 - 765
Опубликована: Апрель 3, 2025
Land
Use
and
Cover
Change
(LULCCs)
shapes
catchment
dynamics
is
a
key
driver
of
hydrological
risks,
affecting
responses
as
vegetated
land
replaced
with
urban
developments
cultivated
land.
The
resultant
risks
are
likely
to
become
more
critical
in
the
future
climate
changes
becomes
increasingly
variable.
Understanding
effects
LULCC
vital
for
developing
management
strategies
reducing
adverse
on
cycle
environment.
This
study
examines
Niger
Delta
Region
(NDR)
Nigeria
from
1986
2024.
A
supervised
maximum
likelihood
classification
was
applied
Landsat
5
TM
8
OLI
images
1986,
2015,
Five
use
classes
were
classified:
Water
bodies,
Rainforest,
Built-up,
Agriculture,
Mangrove.
overall
accuracy
Kappa
coefficients
93%
0.90,
91%
0.87,
84%
0.79
2024,
respectively.
Between
built-up
agriculture
areas
substantially
increased
by
about
8229
6727
km2
(561%
79%),
respectively,
concomitant
decrease
mangrove
vegetation
14,350
10,844
(−54%
−42%),
spatial
distribution
across
NDR
states
varied,
Delta,
Bayelsa,
Cross
River,
Rivers
States
experiencing
highest
rainforest,
losses
64%,
55,
44%,
44%
(5711
km2,
3554
2250
1297
km2),
NDR’s
mangroves
evidently
under
serious
threat.
has
important
implications,
particularly
given
role
played
forests
regulating
hazards.
dramatic
rainforest
could
exacerbate
climate-related
impacts.
provides
quantitative
information
that
be
used
support
planning
practices
well
sustainable
development.
Sustainability,
Год журнала:
2024,
Номер
16(10), С. 4104 - 4104
Опубликована: Май 14, 2024
Land
use,
as
one
of
the
major
sources
carbon
emissions,
has
profound
implications
for
global
climate
change.
County-level
land-use
systems
play
a
critical
role
in
national
emission
management
and
control.
Consequently,
it
is
essential
to
explore
spatiotemporal
effects
optimization
strategies
emissions
at
county
scale
promote
achievement
regional
dual
targets.
This
study,
focusing
on
Shaanxi
Province,
analyzed
characteristics
land
use
from
2000
2020.
By
establishing
evaluation
model,
county-level
were
clarified.
Utilizing
Geodetector
K-means
clustering
methods,
driving
mechanisms
elucidated,
explored.
The
results
showed
that
during
2000–2020,
Province
underwent
significant
changes,
with
constructed
increasing
by
97.62%,
while
cultivated
grassland
substantially
reduced.
overall
exhibited
pattern
North
>
Central
South.
total
within
province
increased
nearly
fourfold
over
20
years,
reaching
1.00
×
108
tons.
Constructed
was
primary
source
forest
contributed
significantly
sink
study
area.
Interactions
among
factors
had
impacts
spatial
differentiation
emissions.
For
counties
different
types
differentiated
recommended.
Low-carbon
should
intensify
ecological
protection
rational
utilization,
medium-carbon
need
strike
balance
between
economic
development
environmental
protection,
high-carbon
prioritize
reduction
structural
transformation.
