Decoding spatial patterns of urban thermal comfort: Explainable machine learning reveals drivers of thermal perception
Environmental Impact Assessment Review,
Год журнала:
2025,
Номер
114, С. 107895 - 107895
Опубликована: Март 5, 2025
Язык: Английский
Investigating the Effects of 2D/3D Urban Morphology on Land Surface Temperature Using High-Resolution Remote Sensing Data
Buildings,
Год журнала:
2025,
Номер
15(8), С. 1256 - 1256
Опубликована: Апрель 10, 2025
Understanding
the
influence
of
urban
morphology
on
Land
Surface
Temperature
(LST)
is
essential
for
planning,
development,
and
mitigating
heat
island
effect.
Leveraging
high-resolution
remote
sensing
data,
this
study
systematically
extracted
64
2D
morphological
parameters
(UMPs)
28
3D
UMPs,
along
with
their
corresponding
summer
winter
LST
at
both
grid
level
(using
a
30
m
×
as
minimum
unit)
block
an
unit).
The
UMPs
were
derived
from
landscape
indices
land
cover,
while
included
building-related
(BUMPs)
tree-related
(TUMPs).
Ultimately,
multiple
statistical
methods
employed
to
investigate
complex
mechanisms
through
which
these
across
winter.
This
showed
following
results:
(1)
Most
significantly
correlated
in
seasons
grid/block
levels,
stronger
correlations
level.
(2)
Stepwise
regression
revealed
that
combining
enhanced
explanation,
achieving
R2
=
70.9%
(summer)
65.7%
(winter)
entire
area,
consistent
results
built-up
zones.
(3)
Relative
importance
analysis
identified
35
influential
features,
ranked
follows:
>
BUMPs
TUMPs.
highlights
UMPs’
dominance
confirming
significance.
These
findings
emphasize
need
integrated
design,
considering
planar
layouts
vertical
configurations
buildings/vegetation.
provides
practical
guidance
thermal
environment
mitigation
sustainable
development
optimized
spatial
planning.
Язык: Английский
Addressing the heat exposure risk shift towards new towns and rural areas: Potential strategies inspired by the heat network resilience
Building and Environment,
Год журнала:
2025,
Номер
unknown, С. 112592 - 112592
Опубликована: Янв. 1, 2025
Язык: Английский
Nonlinear Effects of Human Settlements on Seasonal Land Surface Temperature Variations at the Block Scale: A Case Study of the Central Urban Area of Chengdu
Land,
Год журнала:
2025,
Номер
14(4), С. 693 - 693
Опубликована: Март 25, 2025
The
land
surface
temperature
(LST)
in
the
central
urban
area
has
shown
a
consistent
upward
trend
over
years,
exacerbating
heat
island
(SUHI)
effect.
Therefore,
this
study
focuses
on
of
Chengdu,
using
blocks
as
research
scale.
Gradient
Boosting
Decision
Tree
(GBDT)
model
and
SHAP
values
are
employed
to
explore
nonlinear
effects
human
settlements
(HS)
LST
across
different
seasons.
results
show
that
(1)
At
block
scale,
overall
impact
HS
all
four
seasons
tracks
following
order:
built
environment
(BE)
>
landscape
pattern
(LP)
socio-economic
development
(SED).
(2)
LP
is
most
important
factor
affecting
summer,
while
BE
greatest
influence
during
spring,
autumn,
winter.
(3)
Most
indicators
exhibit
seasonal
variations
their
LST.
impervious
(ISA)
exhibits
significant
positive
autumn.
In
contrast,
nighttime
light
index
(NTL)
functional
mix
degree
(FMD)
exert
negative
Additionally,
normalized
difference
vegetation
(NDVI)
negatively
affects
both
spring
summer.
Moreover,
connectivity
(CNT)
density
(FPD)
demonstrate
notable
threshold
(4)
Certain
interaction
effects,
some
combinations
these
can
effectively
reduce
This
reveals
HS–LST
interactions
through
multidimensional
analysis,
offering
block-scale
planning
strategies
for
sustainable
thermal
optimization.
Язык: Английский
Optimizing green space configuration for mitigating land surface temperature: A case study of karst mountainous cities
Sustainable Cities and Society,
Год журнала:
2025,
Номер
unknown, С. 106345 - 106345
Опубликована: Март 1, 2025
Язык: Английский
Precise Mitigation Strategies for Urban Heat Island Effect in Hong Kong's New Towns using Automated Machine Learning
Sustainable Cities and Society,
Год журнала:
2025,
Номер
unknown, С. 106350 - 106350
Опубликована: Апрель 1, 2025
Язык: Английский
Novel Spatiotemporal Nonlinear Regression Approach for Unveiling the Impact of Urban Spatial Morphology on Carbon Emissions
Sustainable Cities and Society,
Год журнала:
2025,
Номер
unknown, С. 106381 - 106381
Опубликована: Апрель 1, 2025
Язык: Английский
The role of urban green space morphology and threshold in cooling efficiency: evidence from five cities, China
Journal of Cleaner Production,
Год журнала:
2025,
Номер
unknown, С. 145580 - 145580
Опубликована: Апрель 1, 2025
Язык: Английский
The Landscape Pattern Characteristics of Urban Built-up Land Significantly Influence Urban Thermal Comfort: Evidence from Large Cities in China
Sustainable Cities and Society,
Год журнала:
2025,
Номер
unknown, С. 106402 - 106402
Опубликована: Апрель 1, 2025
Язык: Английский
Research on the Root Cause Tracing Method of the Change in Access to Electricity Index Based on Data Mining
Energies,
Год журнала:
2025,
Номер
18(9), С. 2275 - 2275
Опубликована: Апрель 29, 2025
Superior
electricity-optimized
business
ecosystems
(EOBEs)
have
evolved
into
pivotal
determinants
in
catalyzing
industrial–commercial
prosperity.
The
access
to
electricity
index
(AEI)
constitutes
a
valid
instrument
for
assessing
the
EOBE.
To
realize
accurate
evaluation
of
EOBE
and
root
cause
tracing
its
changes,
this
paper
constructs
new
analytical
model
evaluating
monitoring
changes
First,
based
on
Business
Ready
(B-READY)
system,
considering
three
factors:
power
regulatory
quality,
public
service
level,
enterprises’
gain
efficiency.
Then,
uses
raw
data
collected
calculate
score
AEI
enable
an
assessment
Next,
priori
extract
coupling
features
indicators
combines
time
series
policy
construct
feature
matrix.
Finally,
characteristic
contribution
was
analyzed
using
support
vector
regression
(SVR)
Shapley’s
additive
interpretation
(SHAP)
value.
experiment
shows
that
factors
affecting
change
are
features,
decreasing
order
importance.
This
study
provides
reference
cases
improvement
ideas
optimization
Язык: Английский