Landslide susceptibility assessment of the Wanzhou district: Merging landslide susceptibility modelling (LSM) with InSAR-derived ground deformation map
International Journal of Applied Earth Observation and Geoinformation,
Год журнала:
2025,
Номер
136, С. 104365 - 104365
Опубликована: Янв. 18, 2025
Язык: Английский
Overcoming the data limitations in landslide susceptibility modeling
Science Advances,
Год журнала:
2025,
Номер
11(8)
Опубликована: Фев. 21, 2025
Data-driven
models
widely
used
for
assessing
landslide
susceptibility
are
severely
limited
by
the
and
environmental
data
needed
to
create
them.
They
rely
on
inventories
of
past
locations,
which
difficult
collect
often
nonrepresentative.
Furthermore,
maps
most
in
regions
without
means
assemble
an
inventory.
To
overcome
these
challenges,
we
develop
a
method
shallow
based
probabilistic
morphometric
analysis
landscape's
topography,
rather
than
characteristics
landslides.
The
model
assumes
that
hillslopes
with
higher
relief
gradient
compared
surrounding
landscape
more
prone
We
demonstrate
superior
performance
this
approach
over
contrasting
data-driven
across
northwestern
United
States.
As
our
only
requires
elevation
data,
it
overcomes
major
limitations
facilitates
creation
effective
areas
where
was
previously
unfeasible.
Язык: Английский
Functional Regression for Space‐Time Prediction of Precipitation‐Induced Shallow Landslides in South Tyrol, Italy
Journal of Geophysical Research Earth Surface,
Год журнала:
2025,
Номер
130(4)
Опубликована: Апрель 1, 2025
Abstract
Landslides
are
geomorphic
hazards
in
mountainous
terrains
across
the
globe,
driven
by
a
complex
interplay
of
static
and
dynamic
controls.
Data‐driven
approaches
have
been
employed
to
assess
landslide
occurrence
at
regional
scales
analyzing
spatial
aspects
time‐varying
conditions
separately.
However,
joint
assessment
landslides
space
time
remains
challenging.
This
study
aims
predict
precipitation‐induced
shallow
within
Italian
province
South
Tyrol
(7,400
km
2
).
We
introduce
functional
predictor
framework
where
precipitation
is
represented
as
continuous
series,
contrast
conventional
that
treat
scalar
predictor.
Using
hourly
data
past
occurrences
from
2012
2021,
we
implemented
generalized
additive
model
derive
statistical
relationships
between
occurrence,
various
factors,
preceding
evaluated
resulting
predictions
through
several
cross‐validation
routines,
yielding
performance
scores
frequently
exceeding
0.90.
To
demonstrate
predictive
capabilities,
performed
hindcast
for
storm
event
Passeier
Valley
on
4–5
August
2016,
capturing
observed
locations
illustrating
evolution
predicted
probabilities.
Compared
standard
early
warning
approaches,
this
eliminates
need
predefine
fixed
windows
aggregation
while
inherently
accounting
lagged
effects.
By
integrating
controls,
research
advances
prediction
large
areas,
addressing
seasonal
effects
underlying
limitations.
Язык: Английский
Landslide Susceptibility Mapping Considering Landslide Spatial Aggregation Using the Dual-Frequency Ratio Method: A Case Study on the Middle Reaches of the Tarim River Basin
Remote Sensing,
Год журнала:
2025,
Номер
17(3), С. 381 - 381
Опубликована: Янв. 23, 2025
The
phenomenon
of
landslide
spatial
aggregation
is
widespread
in
nature,
which
can
affect
the
result
susceptibility
prediction
(LSP).
In
order
to
eliminate
uncertainty
caused
by
an
LSP
study,
researchers
have
put
forward
some
techniques
quantify
degree
aggregation,
including
class
index
(LAI),
widely
used.
However,
due
limitations
existing
LAI
method,
it
still
uncertain
when
applied
study
area
with
complex
engineering
geological
conditions.
Considering
a
new
dual-frequency
ratio
(DFR),
was
proposed
establish
association
between
occurrence
landslides
and
twelve
predisposing
factors
(i.e.,
slope,
aspect,
elevation,
relief
amplitude,
rock
group,
fault
density,
river
average
annual
rainfall,
NDVI,
distance
road,
quarry
density
hydropower
station
density).
And
DFR
improved
used
form
frequency
ratio.
Taking
middle
reaches
Tarim
River
Basin
as
area,
application
method
verified.
Meanwhile,
four
models
were
adopted
calculate
indexes
(LSIs)
this
(FR),
analytic
hierarchy
process
(AHP),
logistic
regression
(LR)
random
forest
(RF).
Finally,
receiver
operating
characteristic
curves
(ROCs)
distribution
patterns
LSIs
assess
each
model’s
performance.
results
showed
that
could
reduce
adverse
effect
on
better
enhance
Additionally,
LR
RF
had
superior
performance,
among
DFR-RF
model
highest
accuracy
value,
quite
reliable
LSIs.
Язык: Английский
Relationship between continuous or discontinuous of controlling factors and landslide susceptibility in the high-cold mountainous areas, China
Ecological Indicators,
Год журнала:
2025,
Номер
172, С. 113313 - 113313
Опубликована: Март 1, 2025
Язык: Английский
Factors controlling the formation and movement of clustered shallow landslides triggered by the extreme rainstorm in July 2023 in Beijing, China
Geomorphology,
Год журнала:
2025,
Номер
unknown, С. 109728 - 109728
Опубликована: Март 1, 2025
Язык: Английский
Landslide Hazard and Rainfall Threshold Assessment: Incorporating Shallow and Deep-Seated Failure Mechanisms with Physics-Based Models
Geosciences,
Год журнала:
2024,
Номер
14(10), С. 280 - 280
Опубликована: Окт. 21, 2024
Landslides
pose
a
significant
threat
worldwide,
leading
to
numerous
fatalities
and
severe
economic
losses.
The
city
of
Manizales,
located
in
the
Colombian
Andes,
is
particularly
vulnerable
due
its
steep
topography
permeable
volcanic
ash-derived
soils.
This
study
aims
assess
landslide
hazards
Manizales
by
integrating
shallow
planar
deep-seated
circular
failure
mechanisms
using
physics-based
models
(TRIGRS
Scoops3D).
By
combining
hazard
zonation
maps
with
rainfall
thresholds
calibrated
through
historical
data,
we
provide
refined
approach
for
early
warning
systems
(EWS)
region.
Our
results
underscore
significance
maps,
which
combine
scenarios.
categorizing
urban
areas
into
high,
medium,
low-risk
zones,
offer
practical
framework
planning.
Moreover,
developed
warning,
simplifying
their
application
while
aiming
enhance
regional
predictive
accuracy.
comprehensive
equips
local
authorities
essential
tools
mitigate
risks,
refine
zoning,
strengthen
systems,
promoting
safer
development
Andean
region
beyond,
as
methods
used
are
well-established
implemented
globally.
Язык: Английский