Natural Hazards,
Journal Year:
2024,
Volume and Issue:
120(5), P. 4053 - 4081
Published: Jan. 4, 2024
Abstract
To
increase
the
resilience
of
communities
against
floods,
it
is
necessary
to
develop
methodologies
estimate
vulnerability.
The
concept
vulnerability
multidimensional,
but
most
flood
studies
have
focused
only
on
social
approach.
Nevertheless,
in
recent
years,
following
seismic
analysis,
physical
point
view
has
increased
its
relevance.
Therefore,
present
study
proposes
a
methodology
map
and
applies
using
an
index
at
urban
parcel
scale
for
medium-sized
town
(Ponferrada,
Spain).
This
based
multiple
indicators
fed
by
geographical
open-source
data,
once
they
been
normalized
combined
with
different
weights
extracted
from
Analytic
Hierarchic
Process.
results
show
raster
that
facilitates
future
emergency
risk
management
diminish
potential
damages.
A
total
22.7%
parcels
studied
value
higher
than
0.4,
which
considered
highly
vulnerable.
location
these
would
passed
unnoticed
without
use
open
governmental
datasets,
when
average
calculated
overall
municipality.
Moreover,
building
percentage
covered
water
was
influential
indicator
area,
where
simulated
generated
alleged
dam
break.
exceeds
spatial
constraints
collecting
this
type
data
direct
interviews
inhabitants
allows
working
larger
areas,
identifying
buildings
infrastructure
differences
among
parcels.
Sustainable Cities and Society,
Journal Year:
2023,
Volume and Issue:
99, P. 104847 - 104847
Published: Aug. 13, 2023
A
key
role
in
making
cities
resilient
has
been
acknowledged
raising
risk
preparedness
and
awareness
of
urban
communities,
by
appropriate
education
communication
strategies,
which
should
rely
on
innovative
pervasive
tools.
In
this
regard,
an
outstanding
paradigm
shift
is
driven
the
advancement
Virtual
Reality,
can
take
advantage
Serious
Games,
for
helping
individuals
develop
responsive
behaviours
case
both
slow
sudden
disasters
and,
thus,
boosting
effective
human-urban-building
interaction
within
a
wider
process
safety
sustainability.
To
end,
paper
proposes
VR-SGs
training
prototype
multi-hazard
scenarios
open
spaces.
The
integrates
results
from
phenomenological
behavioural
analyses
applied
to
representative
typologies
built
environment.
demonstrated
heat
wave
protection
earthquake
response
through
design
implementation
its
functional
features
–
virtual
environment,
mode,
learning
outcomes
storyline
informative
contents,
including
simulation-based
data
surface
temperatures,
extent
falling
debris
crowd
motion.
final
goal
validate
reliable
flexible
tool
view
wide
replication
contexts
instructing
critical
situations
communicating
mitigation
strategies.
ISPRS International Journal of Geo-Information,
Journal Year:
2024,
Volume and Issue:
13(12), P. 419 - 419
Published: Nov. 21, 2024
Geodata,
geographical
information
science
(GISc),
and
GeoAI
(geo-intelligence
workflows)
play
an
increasingly
important
role
in
predictive
disaster
risk
reduction
management
(DRRM),
aiding
decision-makers
determining
where
when
to
allocate
resources.
There
have
been
discussions
on
the
ethical
pitfalls
of
these
systems
context
DRRM
because
documented
cases
biases
AI
other
socio-technical
systems.
However,
none
expound
how
audit
geo-intelligence
workflows
for
from
data
collection,
processing,
model
development.
This
paper
considers
a
case
study
that
uses
characterize
housing
stock
vulnerability
flooding
Karonga
district,
Malawi.
We
use
Friedman
Nissenbaum’s
definition
categorization
emphasize
as
negative
undesirable
outcome.
limit
scope
affect
visibility
different
typologies
workflow.
The
results
show
introduces
amplifies
against
houses
certain
materials.
Hence,
group
within
population
area
living
would
potentially
miss
out
interventions.
Based
this
example,
we
urge
community
researchers
practitioners
normalize
auditing
prevent
disasters
biases.
Remote Sensing,
Journal Year:
2023,
Volume and Issue:
15(12), P. 3009 - 3009
Published: June 8, 2023
Floods
occur
throughout
the
world
and
are
becoming
increasingly
frequent
dangerous.
This
is
due
to
different
factors,
among
which
climate
change
land
use
stand
out.
In
Mexico,
they
every
year
in
areas.
Tabasco
a
periodically
flooded
region,
causing
losses
negative
consequences
for
rural,
urban,
livestock,
agricultural,
service
industries.
Consequently,
it
necessary
create
strategies
intervene
effectively
affected
Different
techniques
have
been
developed
mitigate
damage
caused
by
this
phenomenon.
Satellite
programs
provide
large
amount
of
data
on
Earth’s
surface
geospatial
information
processing
tools
useful
environmental
forest
monitoring,
impacts,
risk
analysis,
natural
disasters.
paper
presents
strategy
classification
areas
using
satellite
images
obtained
from
synthetic
aperture
radar,
as
well
U-Net
neural
network
ArcGIS
platform.
The
study
area
located
Los
Rios,
region
Tabasco,
Mexico.
results
show
that
performs
despite
limited
number
training
samples.
As
epochs
increase,
its
precision
increases.
Ecological Informatics,
Journal Year:
2024,
Volume and Issue:
82, P. 102677 - 102677
Published: June 12, 2024
In
the
Yangtze
River
Delta
in
China,
known
for
its
intricate
water
network,
achieving
harmonious
development
between
humans
and
nature
rural
areas
is
imperative.
However,
identification
of
water-net
landscape
characteristics
relationship
sustainability
these
remain
unclear.
The
aim
this
study
was
to
bridge
gap
by
proposing
a
novel
framework
investigating
from
typo-morphological
perspective.
Specifically,
through
regression
analysis,
influence
multilevel
spatial
on
selected
as
research
focus.
First,
metrics
were
introduced
delineate
characteristics,
including
single
multiple
elements
types,
using
deep
learning
methods
achieve
automatic
classification.
Subsequently,
employing
an
improved
entropy
method,
we
comprehensively
quantified
indicators
economic,
social,
ecological
dimensions.
Finally,
ordinary
least
squares
(OLS)
model
two
variation
coefficient
models,
namely,
geographically
weighted
(GWR)
multiscale
(MGWR),
used
quantitatively
analyze
sustainability.
Significant
performances
obtained
with
adjusted
R2
values
0.33,
0.35,
0.4
at
each
characteristic
level.
GWR
MGWR,
which
incorporated
all
metrics,
0.84
0.88,
respectively.
results
demonstrate
that
highly
depends
proposed
exhibits
heterogeneity.
findings
improve
our
understanding
provide
important
planning
decision-making
references
sustainable
areas.
Environmental Research Communications,
Journal Year:
2024,
Volume and Issue:
6(7), P. 075027 - 075027
Published: July 1, 2024
Abstract
With
the
worldwide
growing
threat
of
flooding,
assessing
flood
risks
for
human
societies
and
associated
social
vulnerability
has
become
a
necessary
but
challenging
task.
Earlier
research
indicates
that
islands
usually
face
heightened
due
to
higher
population
density,
isolation,
oceanic
activities,
while
there
is
an
existing
lack
experience
in
island-focused
risk
under
complex
interactions
between
geography
socioeconomics.
In
this
context,
our
study
employs
high-resolution
hazard
data
principal
component
analysis
(PCA)
method
comprehensively
assess
exposure
Prince
Edward
Island
(PEI),
Canada,
where
limited
been
delivered
on
assessments.
The
findings
reveal
exposed
populations
are
closely
related
distribution
areas,
with
increasingly
severe
impact
from
current
future
climate
conditions,
especially
island’s
north
shore.
Exposed
buildings
exhibit
concentrated
at
different
levels
community
centers,
change
projected
significantly
worsen
building
compared
population,
possibly
urban
agglomeration
effect.
most
populated
cities
towns
show
highest
vulnerabilities
PEI,
results
reflect
relatively
less
economic
structure
islands.
Recommendations
management
coming
stage
include
necessity
particular
actions,
recognizing
centers
as
critical
sites
responses,
incorporating
hazards
into
planning
mitigate
impacts
continuous
urbanization
ecosystem
services
prevention.
