Jurnal Sylva Lestari,
Год журнала:
2024,
Номер
12(2), С. 242 - 257
Опубликована: Март 12, 2024
A
management
unit-based
land
cover
change
analysis
was
examined
in
Kahayan
Tengah
Forest
Management
Unit
(FMU)
to
understand
past,
present,
and
future
assist
forest
planning
FMU.
This
study
aims
model
2011
2016,
predict
2021,
simulate
2026
Modeling
prediction
simulation
using
MOLUSCE
from
the
QGIS
plugin.
The
results
revealed
that
agricultural
experienced
significant
increase
total
area
during
2011–2016.
potential
transitions
2016
with
Artificial
Neural
Network
method
showed
a
Kappa
coefficient
of
0.701
good
category,
2021
Cellular
Automata
0.672
category.
By
2026,
will
continue
while
tends
remain
stable
its
area.
managed
simulated
accuracy.
Thus,
this
data
information
can
support
Keywords:
unit,
Tengah,
change,
prediction,
Environmental Research Letters,
Год журнала:
2023,
Номер
19(1), С. 013002 - 013002
Опубликована: Ноя. 29, 2023
Abstract
Urban
climate-related
disaster
risks
are
set
to
rise,
driven
by
the
interaction
of
two
global
megatrends:
urbanization
and
climate
change.
A
detailed
understanding
whether,
where
how
cities
growing
within
or
into
hazard-prone
areas
is
an
urgent
prerequisite
for
assessing
future
risk
trajectories,
risk-informed
planning,
adaptation
decisions.
However,
this
analysis
has
been
mostly
neglected
date,
as
most
change
research
focused
on
assessment
hazard
trends
but
less
socio-economic
changes
affect
exposure.
growth
expansion
modeling
provide
a
powerful
tool,
given
that
urban
major
driver
in
cities.
The
paper
reviews
achievements
lately
made
exposure
assesses
they
can
be
applied
context
future-oriented
planning
measures.
It
also
analyses
which
methodological
challenges
persist
might
overcome.
These
points
pertain
particularly
need
consider
integrate
(1)
morphology
patterns
potential
linkages
well
vulnerability,
(2)
long-term
time
horizons
developments,
(3)
feedbacks
between
trajectories
trends,
(4)
integration
drivers
responses,
(5)
urbanization,
(6)
scenarios,
developed
commonly
defined
scenario
framework.
Jurnal Sylva Lestari,
Год журнала:
2024,
Номер
12(2), С. 242 - 257
Опубликована: Март 12, 2024
A
management
unit-based
land
cover
change
analysis
was
examined
in
Kahayan
Tengah
Forest
Management
Unit
(FMU)
to
understand
past,
present,
and
future
assist
forest
planning
FMU.
This
study
aims
model
2011
2016,
predict
2021,
simulate
2026
Modeling
prediction
simulation
using
MOLUSCE
from
the
QGIS
plugin.
The
results
revealed
that
agricultural
experienced
significant
increase
total
area
during
2011–2016.
potential
transitions
2016
with
Artificial
Neural
Network
method
showed
a
Kappa
coefficient
of
0.701
good
category,
2021
Cellular
Automata
0.672
category.
By
2026,
will
continue
while
tends
remain
stable
its
area.
managed
simulated
accuracy.
Thus,
this
data
information
can
support
Keywords:
unit,
Tengah,
change,
prediction,
