Thermal hazards in urban spaces: A review of climate-resilient planning and design to reduce the heat stress
Aman Gupta,
No information about this author
Bhaskar De,
No information about this author
Sutapa Das
No information about this author
et al.
Urban Climate,
Journal Year:
2025,
Volume and Issue:
59, P. 102296 - 102296
Published: Jan. 25, 2025
Language: Английский
Combined Thermal Index Development for Urban Heat Island Detection in Area of Split, Croatia
Land,
Journal Year:
2025,
Volume and Issue:
14(1), P. 175 - 175
Published: Jan. 15, 2025
Urban
heat
islands
(UHIs)
are
a
phenomenon
of
temperature
rising
within
urban
areas
relative
to
their
rural
counterparts.
UHIs
becoming
an
increasingly
common
problem
in
large
cities,
which
appear
due
excessive
urbanization
and
reductions
natural
cover
vegetation.
This
negatively
affects
the
quality
life
residents
affected
city,
causing
discomfort,
reducing
air
quality,
increasing
energy
demand.
In
this
study,
were
detected
analyzed
city
Split,
Croatia,
using
data
from
Landsat
8
9
satellite
missions
ground-based
measurements
land
surface
temperatures,
conducted
July,
August,
September
2024.
research
compares
sensor-based
analysis
results
proposal
new
index:
Combined
Thermal
Index.
The
main
feature
index,
combines
measured
perceived
temperature,
is
improve
understanding
impact
(Split),
compared
existing
indices.
So
far,
LST
have
not
been
combined,
nor
they
combined
with
human
perception
important
case
because
it
these
people
who
will
ultimately
feel
rise
temperature.
Language: Английский
Leveraging urban AI for high-resolution urban heat mapping: Towards climate resilient cities
Environment and Planning B Urban Analytics and City Science,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 24, 2025
Urban
heat
island
(UHI)
effects
are
increasingly
recognised
as
a
significant
challenge
arising
from
urbanisation,
leading
to
elevated
temperatures
within
urban
areas
that
pose
risks
public
health
and
undermine
the
sustainability
of
cities.
Effective
UHI
management
requires
high-resolution
timely
mapping
temperature
patterns
guide
interventions.
Traditional
methods
for
often
lack
spatial
accuracy
efficiency
necessary
detailed
analysis,
especially
in
complex
environments.
This
study
integrates
artificial
intelligence
(Urban
AI)
by
presenting
U-Net
model
tailored
metropolitan
area
Adelaide,
South
Australia.
Trained
on
thermal
data
Australian
Government
Data
Directory,
captures
pixel-level
variations
across
diverse
landscapes,
including
densely
built
areas,
suburban
zones,
green
spaces.
Achieving
low
Mean
Squared
Error
(MSE)
0.0029
processing
each
map
less
than
30
seconds,
demonstrates
exceptional
computational
efficiency.
The
model,
an
AI
agent,
offers
scalable
tool
supporting
real-time
assessments
facilitating
targeted
mitigation
efforts.
By
bridging
gap
between
advanced
geospatial
modelling
practical
planning,
it
enables
data-driven
decisions
enhance
climate
resilience,
optimise
infrastructure,
improve
rapidly
urbanising
regions.
approach
highlights
transformative
potential
addressing
challenges,
delivering
precise
actionable
insights
support
sustainable
climate-adaptive
Language: Английский
Nature-Based Urbanism for Enhancing Senior Citizens’ Outdoor Thermal Comfort in High-Density Mediterranean Cities: ENVI-met Findings
Urban Science,
Journal Year:
2025,
Volume and Issue:
9(5), P. 152 - 152
Published: May 6, 2025
As
climate
change
intensifies
the
frequency
and
severity
of
urban
heatwaves,
elderly
populations
are
becoming
increasingly
vulnerable
to
outdoor
thermal
stress,
particularly
in
dense
Mediterranean
cities.
This
study
addresses
critical
need
for
micro-scale,
climate-responsive
design
strategies
that
enhance
comfort
aging
residents
historically
underserved
neighborhoods.
Focusing
on
refugee-built
area
Nikea
Greater
Athens,
this
research
explores
effectiveness
nature-based
solutions
(NBS)
mitigating
extreme
heat
through
spatial
interventions
tailored
needs
older
adults.
Using
ENVI-met
5.6.1,
two
scenarios
were
simulated:
a
baseline
scenario
reflecting
existing
conditions
an
optimal
incorporating
mature
tree
planting
water
features.
The
results
analyzed
across
three
key
time
points—morning,
peak
afternoon,
evening—to
capture
diurnal
variations.
findings
demonstrate
NBS
significantly
reduce
Physiological
Equivalent
Temperature
(PET),
with
improvements
exceeding
14
°C
shaded
zones.
highlights
value
fine-grained,
promoting
equity
supporting
adaptation
populations.
Language: Английский