Journal of Computational Methods in Sciences and Engineering,
Год журнала:
2024,
Номер
25(2), С. 1461 - 1476
Опубликована: Ноя. 17, 2024
Forest
fires,
due
to
their
multitude
of
influencing
factors,
complex
disaster
scene
environment,
and
the
randomness
special
fire
behaviors,
pose
issues
in
emergency
rescue
training,
such
as
insufficient
realism
scenarios,
significant
safety
hazards,
difficulties
behavior
quantification
monitoring.
This
study
applies
virtual
reality
(VR)
technology
develop
a
forest
training
system,
establishing
three
main
modules:
situation
deduction,
teaching
assessment.
The
system
implements
dynamic
deduction
typical
types
effectively
improving
simulation
level
scenarios.
It
constructs
scene,
weather
combustible
material
library,
tool
equipment
action
rule
realizing
interaction
between
real-time
under
scenarios
based
on
operating
procedure.
also
structures
monitoring
assessment
process,
achieving
quantitative
detection
post-evaluation
effects.
To
evaluate
system’s
efficacy,
pretesting
post-testing
controlled
experiments
were
conducted
verify
learning
outcomes
trainees.
experimental
results
show
that
after
undergoing
5
days
VR
with
daily
sessions
lasting
30
minutes,
improvements
observed
trainees’
cognition
concerning
theory,
operational
skills,
firefighting
strategies,
determined
by
repeated
measures
analysis
variance
(ANOVA).
These
statistically
significant,
promoting
knowledge
acquisition
transfer
more
than
traditional
methods
(
p
<
0.05*).
In
addition,
according
subjective
feedback
trainees,
84.2%
participants
satisfied
overall
using
this
system.
Despite
some
limitations
restrict
generalizability
conclusions,
offers
new
perspective
training.
Moreover,
it
provides
valuable
insights
references
for
development
various
programs
modernization
China’s
forces.
Land,
Год журнала:
2025,
Номер
14(3), С. 530 - 530
Опубликована: Март 3, 2025
The
frequent
occurrence
of
disasters
has
brought
significant
challenges
to
increasingly
complex
urban
systems.
Resilient
city
planning
and
construction
emerged
as
a
new
paradigm
for
dealing
with
the
growing
risks.
Infrastructure
systems
like
transportation,
lifelines,
flood
control,
drainage
are
essential
operation
during
disasters.
It
is
necessary
measure
how
risks
affect
these
systems’
resilience
at
different
spatial
scales.
This
paper
develops
an
infrastructure
risk
evaluation
index
system
in
areas
based
on
characteristics.
Then,
comprehensive
established
risk–resilience
coupling
mechanism.
overall
characteristics
then
identified.
transmission
level
causes
effects
analyzed
principle
scale.
Additionally,
enhancement
strategies
under
scenarios
proposed.
In
empirical
study
Zhengzhou
City,
shows
clustering
area.
high
central
low
periphery.
Specifically,
it
relatively
southern
northwestern
parts
airport
economy
zone
(AEZ)
center.
leading
driving
factors
drought,
hazardous
materials,
infectious
diseases,
epidemics,
while
include
transportation
networks,
sponge
construction,
municipal
pipe
fire
protection.
proposes
“risk-resilience”
framework
evaluate
analyze
multi-hazard
multi-system
across
multi-level
provides
strategies,
complementing
existing
individual
dimensional
or
studies.
findings
could
offer
visualized
results
support
decision-making
Zhengzhou’s
resilient
outline
special
provide
references
assessment
similar
cities.
Applied Sciences,
Год журнала:
2024,
Номер
14(2), С. 634 - 634
Опубликована: Янв. 11, 2024
This
study
introduces
the
Risk-Informed
Asset-Centric
(RIACT)
process,
a
novel
approach
aimed
at
enhancing
safety
and
resilience
of
urban
infrastructures
against
natural
man-made
disasters.
The
RIACT
method
stands
out
for
its
comprehensive
analysis
potential
disruptions
to
areas,
encompassing
their
susceptibility
disasters,
vulnerability
factors,
recovery
capabilities.
study’s
primary
focus
is
on
Portugal’s
308
municipalities,
assessing
preparedness
ability
recover
from
earthquake
events.
Methodologically,
involved
employing
geographic
information
system
(GIS)
mapping
evaluate
risks,
combining
data
regional
risk
demographic
economic
profiles,
capacities.
provides
detailed
understanding
each
municipality’s
strengths
areas
in
need
improvement,
encouraging
collaborative
framework
sharing
implementing
best
practices.
results
reveal
significant
variations
across
different
regions,
highlighting
tailored
strategies.
Conclusively,
not
only
enhances
individual
municipalities
but
also
contributes
broader
national
strategy
resilience,
offering
valuable
insights
effective
disaster
management
planning.
Sustainable Cities and Society,
Год журнала:
2024,
Номер
112, С. 105632 - 105632
Опубликована: Июнь 28, 2024
Urban
coastal
communities
are
among
the
most
vulnerable
to
flood
hazards,
with
these
threats
set
increase
under
climate
change.
Knowledge
of
how
uncertainty
shapes
passive
or
proactive
local
decision-making
processes
adaptation
remains
sparse
–
significant
potential
inform
resilient
and
sustainable
futures.
To
understand
decision
dynamics,
we
developed
a
serious
game
simulate
governance
roles,
resources,
assets
involved
in
managing
risk
uncertain
scenarios.
Using
data
on
actions
workshops
conducted
Philippines,
identify
three
distinct
archetypes
collective
decision-making:
(1)
Hierarchical
Alliances;
(2)
Passive
Enthusiasts
(3)
Deliberative
Strategists.
We
then
examine
respond
situational,
temporal,
choice,
outcome
uncertainties
present
change
scenarios,
uncovering
six
strategies
used
act,
reduce,
supress,
forestall
uncertainties:
(a)
resource
sharing;
(b)
coordination;
(c)
early
action;
(d)
mobilising
values;
(e)
transferring
accountability;
(f)
balancing.
Our
results
show
different
perform
decisions,
offering
new
guidance
structure
mechanisms
planning
impacts.
Natural hazards and earth system sciences,
Год журнала:
2025,
Номер
25(1), С. 287 - 304
Опубликована: Янв. 20, 2025
Abstract.
The
European
Commission
Disaster
Risk
Management
Knowledge
Centre
(DRMKC)
has
developed
and
hosts
a
web
platform,
the
Data
Hub
(RDH),
designed
to
facilitate
access
sharing
of
curated,
EU-wide
risk
data,
tools,
methodologies,
ultimately
supporting
disaster
management
(DRM)
initiatives.
Based
on
RDH
we
propose
methodology
for
identification
regions
with
multi-hazard
exposure
at
pan-European
level
(EU27+UK).
This
aims
support
decision-making
processes
both
national
subnational
levels
in
EU.
By
employing
meta-analysis
approach
aggregating
hotspots
single
hazards,
provide
an
objective,
statistically
robust
assessment
landscape
finest
spatial
subdivision
level,
local
administrative
units
(LAUs).
Our
results
suggest
that
21.4
%
LAUs
are
exposed
multiple
natural
affecting
around
87
million
people
(18.8
population).
Furthermore,
nearly
half
this
population
is
more
than
three
hazards.
We
find
beyond
density,
income
(i.e.
high,
medium,
low)
primary
driver
influences
status
within
rural
urban
areas.
On
average,
higher
living
high-income
areas
or
low-income
further
validate
our
by
comparing
them
empirical
data
fatalities
events,
revealing
relatively
high
correlation
between
significant
(r=0.59).
providing
detailed
scale,
study
contributes
better
integration
risks
plans.
