Buildings,
Год журнала:
2025,
Номер
15(4), С. 628 - 628
Опубликована: Фев. 18, 2025
Landscape
visual
evaluation
is
a
key
method
for
assessing
the
value
of
landscape
resources.
This
study
aims
to
enhance
environment
and
sensory
quality
urban
landscapes
by
establishing
standards
comfort
natural
landscapes.
Using
line-of-sight
multi-factor
analysis
algorithms,
assesses
spatial
visibility
exposure
building
clusters
in
core
areas
Harbin,
identifying
viewpoints
with
high
potential.
Focusing
on
landmark
3D
models
surrounding
landscape’s
environment,
uses
city’s
sky,
greenery,
water
features
as
elements
evaluating
By
integrating
GIS
data,
big
data
street-view
photos,
image
semantic
recognition,
algorithms
extract
both
objective
subjective
values
at
observation
points,
followed
mathematical
modeling
quantitative
analysis.
The
explores
coupling
relationship
between
physical
perceived
visibility.
results
show
that
effectively
reveals
buildings
landscapes,
providing
scientific
support
planning
contributing
development
more
distinctive
attractive
space.
International Journal of Applied Earth Observation and Geoinformation,
Год журнала:
2024,
Номер
132, С. 104067 - 104067
Опубликована: Авг. 1, 2024
It
is
crucial
to
clarify
the
nonlinear
effects
of
urban
multidimensional
characteristics
on
land
surface
temperature
(LST).
However,
combined
consideration
green
space
(UGS),
water
bodies,
buildings,
and
socio-economic
factors
limited.
And
diurnal
differences
in
their
thermal
have
been
less
considered.
In
this
study,
central
Beijing
was
taken
as
study
area.
Local
climate
zones
(LCZ)
were
firstly
applied
reveal
spatiotemporal
heterogeneity
LST.
Then,
interpretable
machine
learning
methods
utilized
quantitatively
characteristics,
i.e.,
UGS,
building
landscape
features,
features.
The
results
indicated
that
built
type
LCZs
a
higher
average
LST
compared
natural
LCZs.
simultaneously
influenced
by
buildings'
density
height
characteristics.
Daytime
mainly
affected
proportions
trees,
while
nighttime
more
key
exhibit
Whether
during
day
or
night,
impact
coverage
greater
than
height,
consistently
exhibiting
warming
effect.
While,
body
edge
both
exhibited
reversal
trend
between
night.
Our
also
emphasized
importance
trees
UGS
provided
recommendations
for
planning
based
sensitivity
contribution
considerations.
These
findings
can
help
regulate
promote
sustainable
development.
Heliyon,
Год журнала:
2024,
Номер
10(3), С. e24912 - e24912
Опубликована: Янв. 23, 2024
Previous
studies
have
provided
valuable
insights
into
the
impact
of
green
space
(GS)
on
land
surface
temperature
(LST).
However,
there
is
a
need
for
in-depth
comparative
research
changing
landscape
patterns
in
cities
and
their
effects
urban
thermal
environment.
This
study
investigates
spatial
arrangement
GS
influence
impervious
surfaces
LST
areas,
examining
cooling
warming
landscapes
Beijing
Islamabad.
The
aims
to
assess
using
moving
window
1
km2
analyze
overall
effect
Using
Gaofen
(GF–2)
Landsat–8
satellite
data,
we
examined
biophysical
properties
core
areas.
results
indicate
significant
difference
mean
5.44
°C
3.31
between
Islamabad,
respectively.
barren
Islamabad
experience
higher
3.39
compared
Beijing,
which
accounts
1.39
°C.
In
configuration
metrics
show
no
LST,
while
edge
density
(ED)
exhibits
slightly
negative
trend.
contrast,
city
shape
index
(LSI),
patch
(PD),
number
patches
(NP)
LST.
(0.1–0.5
ha)
more
pronounced,
that
15–20
ha
shows
(TD)
5.01
was
observed
from
3.3
Considering
Islamabad's
lush
scape
this
suggests
may
an
increase
future
due
urbanization.
study's
findings
assist
policy-makers
designing
sustainable
layouts
effectively
address
planning
considerations.
Sustainable Cities and Society,
Год журнала:
2024,
Номер
111, С. 105518 - 105518
Опубликована: Май 12, 2024
The
vertical
expansion
of
urbanization
has
increased
the
morphological
heterogeneity
urban
landscape,
affecting
physical
and
emotional
wellbeing
dwellers
by
obstructing
view
greenery.
In
this
study,
multisource
spatial
data
was
used
to
calculate
building
green
index
(BGVI).
Baidu
Street
View
(BSV)
images
were
collected
for
comparison
with
corresponding
BGVI
results.
A
random
forest
model
analyze
contributions
marginal
effects
multiple
influencing
factors
on
BGVI.
results
indicated
that
approximately
76.10%
sampled
sites
had
a
higher
than
street
index,
indicating
buildings'
superiority
visible
greenery
in
height.
western
edge
research
region
frequently
highest
Meanwhile,
hotspot
regions
primarily
located
west,
which
more
consistent
distribution
high
value
zones.
area
within
maximum
distance,
average
height
most
influential
according
analysis
IncNodePurity.
As
quantitative
measure
dwellers'
visual
accessibility
space,
will
contribute
planning
development
landscape
architecture.
