Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Янв. 6, 2025
Urban
overheating
significantly
affects
thermal
comfort
and
livability,
making
it
essential
to
understand
the
relationship
between
urban
form
land
surface
temperature
(LST).
While
horizontal
dimensions
of
have
been
widely
studied,
vertical
structures
their
impact
on
LST
remain
underexplored.
This
study
investigates
influence
three-dimensional
characteristics
LST,
using
ECOSTRESS
sensor
data
four
machine
learning
models.
Six
morphology
variables—building
density
(BD),
mean
building
height
(MH),
volume
(BVD),
gross
floor
area
(GFA),
ratio
(FAR),
sky
view
factor
(SVF)—are
analyzed
across
different
seasons
times
day.
The
results
reveal
that
MH,
BD,
FAR
are
season-stable
factors,
with
higher
MH
correlated
lower
((e.g.,
an
observed
reduction
approximately
3
°C
in
spring),
while
BD
is
associated
(e.g.,
increase
about
3.5
autumn).
In
contrast,
BVD,
GFA,
SVF
season-varying
factors
variable
impacts
depending
time
year.
Higher
BVD
generally
elevated
GFA
linked
LST.
These
associations
reflect
absolute
changes
measured
directly
from
data.
findings
offer
valuable
insights
into
complex
interactions
helping
inform
strategies
for
heat
mitigation
sustainable
planning.
Sustainable Cities and Society,
Год журнала:
2023,
Номер
97, С. 104740 - 104740
Опубликована: Июнь 25, 2023
This
paper
proposes
an
origami-based
adaptive
façade
for
reducing
potentially
harmful
reflected
solar
radiation
in
outdoor
urban
environments.
The
Walkie-Talkie
building
London
is
selected
as
case
study
due
to
numerous
reported
incidents
related
the
excessive
of
building.
performance
peak
at
pedestrian
level
investigated
by
means
computer
simulations.
simulations
are
based
on
hourly
irradiance
between
10AM
and
14
PM
a
day
August.
Initially
10
different
folded
states
three
Miura-fold
origami
units
were
adopted,
simulated
with
15-minute
intervals
each
state.
results
showed
that,
best
performing
can
reduce
61%
average,
up
90%
depending
specific
state
time
day.
Scientific Reports,
Год журнала:
2025,
Номер
15(1)
Опубликована: Янв. 6, 2025
Urban
overheating
significantly
affects
thermal
comfort
and
livability,
making
it
essential
to
understand
the
relationship
between
urban
form
land
surface
temperature
(LST).
While
horizontal
dimensions
of
have
been
widely
studied,
vertical
structures
their
impact
on
LST
remain
underexplored.
This
study
investigates
influence
three-dimensional
characteristics
LST,
using
ECOSTRESS
sensor
data
four
machine
learning
models.
Six
morphology
variables—building
density
(BD),
mean
building
height
(MH),
volume
(BVD),
gross
floor
area
(GFA),
ratio
(FAR),
sky
view
factor
(SVF)—are
analyzed
across
different
seasons
times
day.
The
results
reveal
that
MH,
BD,
FAR
are
season-stable
factors,
with
higher
MH
correlated
lower
((e.g.,
an
observed
reduction
approximately
3
°C
in
spring),
while
BD
is
associated
(e.g.,
increase
about
3.5
autumn).
In
contrast,
BVD,
GFA,
SVF
season-varying
factors
variable
impacts
depending
time
year.
Higher
BVD
generally
elevated
GFA
linked
LST.
These
associations
reflect
absolute
changes
measured
directly
from
data.
findings
offer
valuable
insights
into
complex
interactions
helping
inform
strategies
for
heat
mitigation
sustainable
planning.
