Nature-Based Solutions to Enhance Urban Resilience in the Climate Change and Post-Pandemic Era: A Taxonomy for the Built Environment
Buildings,
Год журнала:
2024,
Номер
14(7), С. 2190 - 2190
Опубликована: Июль 16, 2024
Global
environmental
and
health
issues
such
as
climate
change
the
COVID-19
pandemic
have
highlighted
weaknesses
of
current
urban
systems,
including
poor
availability
accessibility
green
public
spaces
in
cities.
Nature-based
Solutions
are
configured
promising
solutions
to
increase
resilience
built
environment
by
addressing
issues,
promoting
psycho-physical
well-being
users
proposing
for
protection
ecosystems.
Following
a
systematic
review
scientific
literature
using
PRISMA
methodology,
this
study
aims
provide
taxonomic
framework
that
is
applicable
building
scales,
highlighting
key
benefits
challenges
achieving
resilience.
This
proposes
holistic
multifunctional
approach
will
prove
be
useful
tool
researchers
policy
makers
incorporate
greening
strategies
into
regeneration
redevelopment
processes.
The
application
still
seems
limited.
It
therefore
necessary
raise
awareness
issue
among
citizens
promote
close
co-operation
between
different
actors
territorial
decision-making
Язык: Английский
How does the perception of informal green spaces in urban villages influence residents’ complaint Sentiments? a Machine learning analysis of Fuzhou City, China
Ecological Indicators,
Год журнала:
2024,
Номер
166, С. 112376 - 112376
Опубликована: Июль 18, 2024
Язык: Английский
What to do with the spaces in between? The social-ecological value of informal green space and the challenge of planning the unplanned
Landscape and Urban Planning,
Год журнала:
2025,
Номер
259, С. 105372 - 105372
Опубликована: Апрель 10, 2025
Язык: Английский
How does high temperature weather affect tourists’ nature landscape perception and emotions? A machine learning analysis of Wuyishan City, China
PLoS ONE,
Год журнала:
2025,
Номер
20(5), С. e0323566 - e0323566
Опубликована: Май 15, 2025
Natural
landscapes
are
crucial
resources
for
enhancing
visitor
experiences
in
ecotourism
destinations.
Previous
research
indicates
that
high
temperatures
may
impact
tourists’
perception
of
and
emotions.
Still,
the
potential
value
natural
landscape
regulating
emotions
under
high-temperature
conditions
remains
unclear.
In
this
study,
we
employed
machine
learning
models
such
as
LSTM-CNN,
Hrnet,
XGBoost,
combined
with
hotspot
analysis
SHAP
methods,
to
compare
reveal
impacts
elements
on
different
temperature
conditions.
The
results
indicate:
(1)
Emotion
prediction
spatial
a
significant
increase
proportion
negative
conditions,
reaching
30.1%,
emotion
hotspots
concentrated
downtown
area,
whereas,
non-high
accounted
14.1%,
more
uniform
distribution.
(2)
Under
four
most
influential
factors
were
Color
complexity
(0.73),
Visual
entropy
(0.71),
Greenness
(0.68),
Aquatic
rate
(0.6).
contrast,
(0.6),
Openness
(0.56),
(0.55),
(0.55).
(3)
Compared
enhanced
positive
effects
environmental
emotions,
(0.94),
(0.84),
Enclosure
(0.71)
showing
stable
impacts.
Additionally,
aquatic
had
emotional
regulation
effect
(contribution
1.05),
effectively
improving
overall
experience.
This
study
provides
data
foundation
optimizing
destinations,
integrating
advantages
various
proposing
framework
collection,
comparison,
evaluation
It
thoroughly
explores
enhance
sustainable
planning
recommendations
conservation
ecosystems
ecotourism.
Язык: Английский
Habitat connectivity modeling for urban conservation planning: A case study of pileated woodpecker (Dryocopus pileatus) in Hamilton County, Ohio, USA
Ecological Indicators,
Год журнала:
2025,
Номер
176, С. 113656 - 113656
Опубликована: Май 31, 2025
Язык: Английский
Bridging the land use gap: Examining tree canopy cover and connectivity by land use in 10 U.S. cities
Urban forestry & urban greening,
Год журнала:
2024,
Номер
unknown, С. 128626 - 128626
Опубликована: Ноя. 1, 2024
Язык: Английский
Considering Habitat Connectivity in Local Conservation Planning: A Case Study of Hamilton County, Ohio
Опубликована: Янв. 1, 2024
Язык: Английский
Views Rather than Radiosity: A Study on Urban Cover View Factor Mapping and Utilization
Remote Sensing,
Год журнала:
2024,
Номер
16(24), С. 4618 - 4618
Опубликована: Дек. 10, 2024
Urban
tree
canopies
are
a
vital
component
of
green
infrastructure,
especially
in
the
context
accelerating
urban
heat
island
effect
and
global
climate
change.
Quantifying
canopy
cover
relation
to
land
use
changes
is
therefore
crucial.
However,
accurately
evaluating
visual
remains
challenge.
In
this
study,
we
introduced
Cover
View
Factor
(VF)
Potential
Influence
Intensity
Grade
(PIIG)
for
(TC)
mapping
using
airborne
Light
Detection
Ranging
(LiDAR)
remote-sensing
three-dimensional
point
clouds
(3DPCs)
from
Incheon
metropolitan
area,
South
Korea.
The
results
demonstrated
that
LiDAR
3DPCs
effectively
segmented
non-sky
views.
Furthermore,
PIIG
map,
derived
TC
VF
showed
significant
correlation
between
surface
risks
energy
consumption
patterns.
Areas
with
lower
grades
tended
have
higher
greater
vulnerability
risks,
while
areas
exhibited
opposite
trend.
Nevertheless,
further
exploration
complex
collection
sufficient
ground-based
evidence
crucial
practical
application.
Further
remote
sensing
research
should
support
management
agriculture
promote
sustainable
greening
response
evolving
environmental
needs.
Язык: Английский