ISPRS International Journal of Geo-Information,
Год журнала:
2023,
Номер
12(12), С. 482 - 482
Опубликована: Ноя. 28, 2023
Climate
change
is
expected
to
result
in
increased
occurrences
of
extreme
weather
events
such
as
heat
waves
and
cold
spells.
Urban
planning
responses
are
crucial
for
improving
the
capacity
cities
communities
deal
with
significant
temperature
variations
across
seasons.
This
study
aims
investigate
relationship
between
urban
fluctuations
morphology
throughout
four
Through
quadrant
statistical
analyses,
built-environment
factors
identified
that
moderate
or
exacerbate
seasonal
land
surface
temperatures
(LSTs).
The
focus
on
Seoul,
South
Korea,
a
case
study,
LST
values
calculated
at
both
grid
(100
m
×
100
m)
street
block
levels,
incorporating
vegetation
density,
use
patterns,
albedo,
two-
three-dimensional
building
forms,
gravity
indices
large
forests
water
bodies.
analysis
reveals
spatial
segregation
areas
demonstrating
high
adaptability
(cooler
summers
warmer
winters)
those
displaying
vulnerability
(hotter
colder
winters),
differences
forms.
Spatial
regression
analyses
demonstrate
higher
density
proximity
bodies
play
key
roles
moderating
LSTs,
leading
cooler
winters.
Building
characteristics
have
constant
impact
LSTs
all
seasons:
horizontal
expansion
increases
LST,
while
vertical
reduces
LST.
These
findings
consistent
grid-
block-level
analyses.
emphasizes
flexible
role
natural
environment
temperatures.
Land,
Год журнала:
2025,
Номер
14(3), С. 476 - 476
Опубликована: Фев. 25, 2025
Urban
morphology
significantly
influences
residents’
noise
perceptions,
yet
the
impact
across
different
spatial
and
temporal
scales
remains
unclear.
This
study
investigates
scale-dependent
relationship
between
urban
perception
in
New
York
City
using
complaint
rates
(NCR)
as
a
proxy
for
perceived
levels.
A
multi-scale
analysis
framework
was
applied,
including
four
(100
m,
200
500
1000
m)
three
classifications
(daytime/nighttime/dawn,
weekdays/weekends,
seasonal
divisions).
Statistical
analyses,
Spearman
correlation,
Moran’s
I
test,
Geographically
Weighted
Regression
(GWR),
examined
spatiotemporal
heterogeneity.
Results
show:
(1)
NCR
indicators
vary
aggregations.
(2)
Correlations
generally
strengthen
with
larger
units,
revealing
scale
effect.
Temporal
variations,
e.g.,
residential
land
ratio
(RES)
greenery
percentage
(SVI
Green),
show
stronger
correlations
summer
than
winter.
(3)
The
index
revealed
significant
clustering
at
m
scale.
Multi-temporal
GWR
variations
morphology-noise
relationships
contexts;
areas,
building
density
exacerbates
complaints
more
during
non-working
periods
working
hours.
enhances
understanding
of
sound
environments,
offering
insights
required
precise
planning
policies.