Land,
Год журнала:
2024,
Номер
13(10), С. 1626 - 1626
Опубликована: Окт. 7, 2024
Understanding
the
driving
mechanisms
behind
surface
urban
heat
island
(SUHI)
effects
is
essential
for
mitigating
degradation
of
thermal
environments
and
enhancing
livability.
However,
previous
studies
have
primarily
concentrated
on
central
areas,
lacking
a
comprehensive
analysis
entire
metropolitan
area
over
distinct
time
periods.
Additionally,
most
relied
regression
models
such
as
ordinary
least
squares
(OLS)
or
logistic
regression,
without
adequately
analyzing
spatial
heterogeneity
factors
influencing
effects.
Therefore,
this
study
aims
to
explore
in
Guangzhou-Foshan
across
different
The
Local
Climate
Zones
(LCZs)
method
was
employed
analyze
landscape
characteristics
structure
metropolis
years
2013,
2018,
2023.
Furthermore,
Geographically
Weighted
Regression
(GWR),
Multi-scale
(MGWR),
Geographical
Detector
(GD)
were
utilized
investigate
interactions
between
(land
cover
factors,
environmental
socio-economic
factors)
Surface
Urban
Heat
Island
Intensity
(SUHII),
maximizing
explanation
SUHII
all
Three
main
findings
emerged:
First,
exhibited
significant
heterogeneity,
with
non-linear
relationship
SUHII.
Second,
SUHI
displayed
core-periphery
pattern,
Large
lowrise
(LCZ
8)
compact
3)
areas
showing
highest
levels
core
zones.
Third,
land
emerged
influential
metropolis.
These
results
indicate
that
exhibit
notable
varying
negative
can
be
leveraged
mitigate
locations.
Such
offer
crucial
insights
future
policy-making.
Applied Geography,
Год журнала:
2024,
Номер
164, С. 103216 - 103216
Опубликована: Фев. 6, 2024
The
rapid
growth
of
heatwaves'
severity
have
increasingly
endangered
citizens’
health
in
the
last
decade.
Evidence
points
to
environmental
injustice
heatwaves:
inequal
heatwave
exposure
among
socioeconomic
groups.
Failing
use
an
adequate
indicator
thermal
comfort
at
a
large
scale,
previous
studies
not
adequately
scrutinized
justice
heatwaves
and
their
variations
across
large-scale
territory.
This
study
is
novel
unprecedented
analysis
psychological
equivalent
temperature
(PET),
comprehensive
measure
comfort,
groups
urban-rural
gradient
Netherlands,
as
proxy
for
factors
affecting
vulnerability.
results
show
that
inequality
(measured
by
Gini
coefficient)
higher
less
urbanized
areas.
It
shows
population
aged
25–44,
immigrants,
tenants,
females
are
most
heat-exposed
all
levels
urbanization.
However,
25–44
more
likely
be
overexposed
areas,
immigrants
rural
open
discussion
on
necessity
location-specific
policies
protecting
different
also
paves
way
future
using
broader
PET
simulations
expanding
scope
include
citizens'
daily
movements.
Sustainable Cities and Society,
Год журнала:
2024,
Номер
113, С. 105677 - 105677
Опубликована: Июль 17, 2024
Urban
land
cover
types
influence
the
urban
microclimates.
However,
recent
work
indicates
magnitude
of
cover's
microclimate
is
affected
by
aridity.
Moreover,
this
variation
in
cooling
and
warming
potentials
can
substantially
alter
exposure
areas
to
extreme
heat.
Our
goal
understand
both
relative
influences
on
local
air
temperature,
as
well
how
these
vary
during
periods
To
do
so
we
apply
predictive
machine
learning
models
an
extensive
in-situ
1
m
dataset
across
eight
U.S.
cities
spanning
a
wide
aridity
gradient
typical
heat
conditions.
We
demonstrate
tree
canopy
buildings
linearly
scales
with
regional
aridity,
while
turf
impervious
surfaces
does
not.
These
interactions
lead
consistently
mitigate
temperature
increases
arid
cities,
humid
regions
varied,
suggesting
that
mitigation
possible,
but
also
aggravate
or
have
no
significant
effect.
Journal of Urban Planning and Development,
Год журнала:
2024,
Номер
150(2)
Опубликована: Янв. 17, 2024
The
surface
urban
heat
island
(SUHI)
phenomenon,
predominantly
influenced
by
factors
associated
with
the
built-up
environment,
is
prominent
in
large
metropolitan
areas.
To
effectively
mitigate
escalating
thermal
environment
challenges
arising
during
cities'
developmental
planning,
rigorously
examining
spatial
interdependencies
between
and
SUHI
phenomenon
imperative.
Employing
Beijing's
primary
area
as
a
case
study,
this
research
addresses
gap
systematic
analysis
of
correlations
within
effect
domain.
study
leverages
Landsat-8
satellite
data
spanning
2016–2020,
Sentinel-2
land-use
classification
data,
2020
digital
elevation
model
(DEM)
integrating
them
geospatial
processing
techniques
to
probe
multifaceted
associations
1
×
1-km
grid-based
local-scale
model.
This
investigation
distinguished
developing
Comprehensive
Built-up
Environment
System
Index,
synthesized
through
multisource
multidimensional
methodologies.
culminates
following
key
findings:
(1)
Between
2016
2020,
manifested
an
ascending
spiral
trend
effect,
morphology
exhibiting
nonuniformity
across
four
seasons.
(2)
In
historical
summer
scenarios
area,
architectural
roadway
environments
demonstrated
consistently
positive
correlation
effect.
(3)
Excluding
average
number
floors
parameter,
all
remaining
parameters
exhibited
significant
association
fluctuations.
