Rapid
socio-economic
development
and
imbalanced
ecosystem
conservation
have
heightened
the
risk
of
species
extinction,
reduced
urban
climate
adaptability,
threatened
human
health
well-being.
Constructing
ecological
green
space
networks
is
an
effective
strategy
for
maintaining
security.
However,
most
studies
primarily
addressed
biodiversity
needs,
with
limited
focus
on
coordinating
street
spaces
in
settlement
planning.
This
study
examines
area
within
Chengdu’s
Third
Ring
Road,
employing
following
methodologies:
(1)
constructing
regional
network
using
Morphological
Spatial
Pattern
Analysis
(MSPA),
Integrated
Valuation
Ecosystem
Services
Trade-offs
(InVEST)
model,
circuit
theory;
(2)
analyzing
view
index
(GVI)
through
machine
learning
semantic
segmentation
techniques;
(3)
identifying
key
areas
coordinated
bivariate
spatial
correlation
analysis.
The
results
showed
that
Road
exhibits
high
landscape
fragmentation,
41
sources
94
corridors
identified.
Ecological
pinch
points
were
located
near
rivers
surrounding
woodlands,
while
barrier
concentrated
dense
buildings
complex
transportation
networks.
Higher
GVI
values
observed
around
university
campuses,
parks,
river-adjacent
streets,
lower
found
commercial
hubs.
To
coordinate
construction
spaces,
central
First
northwestern
region
Second
Roads
identified
as
priority
restoration
areas,
northern,
western,
southeastern
designated
protection
areas.
adopts
a
multi-scale
perspective
to
identify
restoration,
aiming
provide
new
insights
advancing
civilization
high-density
Land,
Год журнала:
2025,
Номер
14(2), С. 220 - 220
Опубликована: Янв. 22, 2025
As
an
important
type
of
linear
cultural
heritage
and
a
waterfront
landscape
that
integrates
both
artificial
natural
elements,
canals
provide
the
public
with
multidimensional
perceptual
experience
encompassing
aesthetics,
culture,
nature.
There
remains
lack
refined,
micro-level
studies
on
canal
landscapes
from
perspective
visual
preference.
This
study
focuses
typical
segment
Grand
Canal
in
China,
specifically
ancient
section
Yangzhou.
We
employed
SegFormer
image
semantic
segmentation
techniques
to
interpret
features
150
panoramic
images,
quantitatively
identifying
environmental
characteristics
canal.
Four
dimensions
were
constructed:
aesthetic
preference,
hydrophilic
Through
questionnaire
survey
various
statistical
analyses,
we
revealed
relationships
between
preferences
for
characteristics.
The
main
findings
include
following:
(1)
Aesthetic
preference
is
positively
correlated
cultural,
natural,
preferences,
while
shows
negative
correlation
preferences.
(2)
influenced
by
combination
blue-green
elements
factors.
Natural
primarily
affected
increased
vegetation
visibility,
associated
higher
proportion
facilities
high-quality
pavements,
linked
larger
water
surface
areas,
fewer
barriers,
better
quality.
(3)
are
spatial
differences
across
different
urban
old
city
exhibiting
aesthetic,
than
new
suburban
areas.
Finally,
this
proposes
strategies
optimising
enhancing
quality
canals,
aiming
sustainable
practical
guidance
future
planning
management
these
sites.
Land,
Год журнала:
2025,
Номер
14(3), С. 610 - 610
Опубликована: Март 13, 2025
The
mental
health
of
university
students
has
received
much
attention
due
to
the
various
pressures
studies,
life,
and
employment.
Several
studies
have
confirmed
that
campus
public
spaces
contain
multiple
restorative
potentials.
Yet,
space
is
still
not
ready
meet
students’
new
need
for
percetions.
Renewal
practices
integrate
multi-issues
are
becoming
more
important,
further
clarification
measurement
methods
optimization
pathways
also
needed.
This
study
applied
semantic
segmentation
technique
deep
learning
model
extract
feature
indicators
outdoor
based
on
street
view
image
(SVI)
data.
subjective
evaluation
small-scale
SVIs
was
obtained
using
perceived
scale-11
(PRS-11)
questionnaire.
On
this
basis,
benefit
models
were
established,
including
explanatory
predictive
models.
used
Pearson’s
correlation
linear
regression
analysis
identify
key
affecting
benefits,
XGBoost
1.7.3
algorithm
predict
scores
scale.
accessibility
results
from
sDNA
then
overlayed
form
a
comprehensive
assessment
matrix
restoration
benefits
dimensions
“areas
with
potential”.
In
way,
three
types
spatial
(LRB-HA,
HRB-LA,
LRB-LA)
sequential
orders
temporal
(short-term,
medium-term,
long-term)
combined
propose
dual
control
accessibility.
provides
methodological
guidelines
empirical
data
regeneration
promotes
efficiency.
addition,
it
can
offer
positive
references
neighborhood-scale
urban
design
sustainable
development.
Buildings,
Год журнала:
2024,
Номер
14(4), С. 1025 - 1025
Опубликована: Апрель 6, 2024
While
transit-oriented
development
(TOD)
has
been
widely
adopted
in
urban
design
alongside
the
expansion
of
metro
transit,
creation
pedestrian-friendly
environments
often
overlooked
during
implementation.
This
resulted
a
lower
walking
advantage
around
transit
stations.
To
address
this
issue
and
encourage
public
transport
use
station
areas,
study
undertook
quantitative
comparative
analysis
pedestrian
environment
five
Chongqing
areas.
The
focused
on
three
key
dimensions:
“comprehensive
evaluation”,
“basic
scale”,
“structural
quality”.
comprehensive
evaluation
considered
factors
such
as
catchment
area
ratio,
POI
kernel
density
distribution,
crowd
agglomeration.
basic
scale
dimension
comprised
floor
building
density,
road
quantity
entrances
exits.
Finally,
structural
quality
included
land
type
mixing
degree,
function
intersection
connectivity,
median
street
length,
route
directness,
green
view
index.
Based
these
analyses,
proposes
series
strategies
including
transportation.
for
advocate
“developing
compact
diverse
use”,
“strengthening
attraction
center”,
“positioning
large
projects
edge”,
“restricting
private
transportation
capabilities”.
consist
“increasing
density”,
“traffic
calming
organization”,
“subdivision
types”,
“three-dimensional
traffic
system”.
These
aim
to
create
more
humanized
environmentally
friendly
environment,
proactively
rise
challenge
climate
change,
thereby
cultivating
sustainable
development.
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Дек. 4, 2024
Urban
greening
plays
a
crucial
role
in
maintaining
environmental
sustainability
and
enhancing
people's
well-being.
However,
limited
by
the
shortcomings
of
traditional
methods,
studying
heterogeneity
nonlinearity
between
factors
green
view
index
(GVI)
still
faces
many
challenges.
To
address
concerns
nonlinearity,
spatial
heterogeneity,
interpretability,
an
interpretable
machine
learning
framework
incorporating
Geographically
Weighted
Random
Forest
(GWRF)
model
SHapley
Additive
exPlanation
(Shap)
is
proposed
this
paper.
In
paper,
we
combine
multi-source
big
data,
such
as
Baidu
Street
View
data
remote
sensing
images,
utilize
semantic
segmentation
models
geographic
processing
techniques
to
study
global
local
interpretation
Beijing
region
with
GVI
key
indicator.
Our
research
results
show
that:
(1)
Within
Sixth
Ring
Road
Beijing,
shows
significant
clustering
phenomenon
positive
correlation
linkage,
at
same
time
exhibits
differences;
(2)
Among
variables,
increase
coverage
rate
has
most
effect
on
GVI,
while
building
density
strong
negative
GVI;
(3)
The
performance
GWRF
predicting
excellent
far
exceeds
that
comparison
models.;
(4)
Whether
it
rate,
urban
built
environment
or
socioeconomic
factors,
their
influence
non-linear
characteristics
certain
threshold
effect.
With
help
these
influences
explicit
effects,
quantitative
analyses
are
provided,
which
can
assist
planners
making
more
scientific
rational
decisions
when
allocating
resources.
Land,
Год журнала:
2025,
Номер
14(2), С. 289 - 289
Опубликована: Янв. 30, 2025
Despite
the
widespread
use
of
street
view
imagery
for
Green
View
Index
(GVI)
analyses,
variations
in
sampling
methodologies
across
studies
and
potential
impact
these
differences
on
results,
including
associated
errors,
remain
largely
unexplored.
This
study
aims
to
investigate
effectiveness
various
GVI
calculation
methods,
with
a
focus
analyzing
point
selection
coverage
angles
results.
Through
systematic
review
extensive
relevant
literature,
we
synthesized
six
predominant
methods:
four-quadrant
method,
six-quadrant
eighteen-quadrant
panoramic
fisheye
method
pedestrian
method.
We
further
evaluated
strengths
weaknesses
each
approach,
along
their
applicability
different
research
domains.
In
addition,
address
limitations
existing
methods
specific
contexts,
developed
novel
technique
based
three
120°
images
experimentally
validated
its
feasibility
accuracy.
The
results
demonstrate
method’s
high
reliability,
making
it
valuable
tool
acquiring
images.
Our
findings
that
choice
significantly
influences
calculations,
underscoring
necessity
researchers
select
optimal
approach
context.
To
mitigate
errors
arising
from
initial
angles,
this
introduces
concept,
“Green
Circle”,
which
enhances
precision
calculations
through
meticulous
segmentation
observational
particularly
complex
urban
environments.