Urban Science,
Journal Year:
2025,
Volume and Issue:
9(2), P. 34 - 34
Published: Feb. 5, 2025
The
assessment
of
urban
heat
resilience
has
become
crucial
due
to
increasing
extreme
weather
events.
This
study
introduces
the
Running
Activity
Z-score
(RAZ)
index
based
on
running
activity
trajectory
data
evaluate
resilience.
Through
a
case
an
August
2022
heatwave
in
Beijing,
we
examined
index’s
sensitivity
and
explored
its
spatial
relationships
with
key
built
environment
factors,
including
plot
ratio,
green
coverage,
population
density,
blue
space
proximity.
Our
results
reveal
two
findings:
(1)
RAZ
serves
as
effective
real-time,
high-precision
indicator
impacts,
evidenced
by
extremely
low
values
consistently
coinciding
periods,
(2)
offers
valuable
insights
for
identifying
potential
areas
supporting
planning
decisions,
demonstrated
significant
correlations
factors
that
align
previous
studies
while
uncovering
more
detailed
relationships.
Although
effectively
complements
traditional
measurement
methods,
application
requires
careful
consideration
external
such
social
dynamics
climate
variability.
Abstract.
Understanding
urban
vertical
structures,
particularly
building
heights,
is
essential
for
examining
the
intricate
interaction
between
humans
and
their
environment.
Such
datasets
are
indispensable
a
variety
of
applications,
including
climate
modeling,
energy
consumption
analysis,
socioeconomic
activities.
Despite
importance
this
information,
previous
studies
have
primarily
focused
on
estimating
heights
regionally
grid
scale,
often
resulting
in
with
limited
coverage
or
spatial
resolution.
This
limitation
hampers
comprehensive
global
analyses
ability
to
generate
actionable
insights
finer
scales.
In
study,
we
developed
height
map
(3D-GloBFP)
at
footprint
scale
by
leveraging
Earth
Observation
(EO)
advanced
machine
learning
techniques.
Our
approach
integrated
multisource
remote
sensing
features
morphology
develop
estimation
models
using
eXtreme
Gradient
Boosting
(XGBoost)
regression
method
across
diverse
regions.
methodology
allowed
us
estimate
individual
buildings
worldwide,
culminating
creation
first
three-dimensional
(3-D)
footprints
(3D-GloBFP).
evaluation
results
show
that
perform
exceptionally
well
worldwide
R2
ranging
from
0.66
0.96
root
mean
square
errors
(RMSEs)
1.9
m
14.6
33
subregions.
Comparisons
other
demonstrate
our
3D-GloBFP
closely
matches
distribution
pattern
reference
heights.
derived
3-D
shows
distinct
regions,
countries,
cities,
gradually
decreasing
city
center
surrounding
rural
areas.
Furthermore,
findings
indicate
disparities
built-up
infrastructure
(i.e.,
volume)
different
countries
cities.
China
country
most
intensive
total
(5.28×1011
m3,
accounting
23.9
%
total),
followed
United
States
(3.90×1011
17.6
total).
Shanghai
has
largest
volume
(2.1×1010
m3)
all
representative
The
building-footprint
reveals
significant
heterogeneity
environments,
providing
valuable
dynamics
climatology.
dataset
available
https://doi.org/10.5281/zenodo.11319913
(Building
Americas,
Africa,
Oceania
3D-GloBFP)
(Che
et
al.,
2024a),
https://doi.org/10.5281/zenodo.11397015
Asia
2024b),
https://doi.org/10.5281/zenodo.11391077
Europe
2024c).
Geographical Journal,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Feb. 1, 2025
Abstract
Urbanisation
is
transitioning
from
disorderly
sprawl
to
compact
intensification,
accompanied
by
functional
differentiation
and
morphological
changes
spatially.
This
study
addresses
the
relationship
between
urban
functions
morphologies
at
block
scale
in
Hangzhou.
Leveraging
geo‐big
data,
we
adopt
a
points
of
interest
(POI)
weighting
method
map
four
essential
functions—residential,
commercial,
public
service,
industrial—at
traffic
analysis
zones
(TAZ)
scale.
Additionally,
estimate
indices
using
building
footprint
data
volume
data.
Our
investigation
reveals
intriguing
patterns:
residential,
service
exhibit
central
concentration
trend
diminishing
towards
periphery,
whereas
industrial
demonstrate
multi‐hotspot
distribution.
Morphological
like
patch
density
mean
while
size
shape
index,
presenting
pronounced
peripheral
distribution
trend.
Significantly,
nuanced
associations
were
elucidated.
Residential
tend
display
dense
small
patches,
commercial
areas
showcase
larger
volumes,
complex
shapes.
Furthermore,
construction
intensity‐based
heterogeneity
unveils
dynamics
morphologies,
particularly
high‐density
areas.
These
findings
underscore
importance
integrating
considerations
into
planning,
offering
fresh
perspective
for
zoning
planning.
Urban Science,
Journal Year:
2025,
Volume and Issue:
9(2), P. 34 - 34
Published: Feb. 5, 2025
The
assessment
of
urban
heat
resilience
has
become
crucial
due
to
increasing
extreme
weather
events.
This
study
introduces
the
Running
Activity
Z-score
(RAZ)
index
based
on
running
activity
trajectory
data
evaluate
resilience.
Through
a
case
an
August
2022
heatwave
in
Beijing,
we
examined
index’s
sensitivity
and
explored
its
spatial
relationships
with
key
built
environment
factors,
including
plot
ratio,
green
coverage,
population
density,
blue
space
proximity.
Our
results
reveal
two
findings:
(1)
RAZ
serves
as
effective
real-time,
high-precision
indicator
impacts,
evidenced
by
extremely
low
values
consistently
coinciding
periods,
(2)
offers
valuable
insights
for
identifying
potential
areas
supporting
planning
decisions,
demonstrated
significant
correlations
factors
that
align
previous
studies
while
uncovering
more
detailed
relationships.
Although
effectively
complements
traditional
measurement
methods,
application
requires
careful
consideration
external
such
social
dynamics
climate
variability.
