Remote Sensing of Environment,
Journal Year:
2024,
Volume and Issue:
305, P. 114057 - 114057
Published: Feb. 27, 2024
Three-dimensional
(3D)
building
models
provide
horizontal
and
vertical
information
of
urban
development
patterns,
which
are
significant
to
urbanization
analysis,
solar
energy
planning,
carbon
reduction
sustainability.
Despite
that
many
popular
products
on
a
global
or
national
scale
proposed,
these
usually
focus
extraction
height
estimation
at
fairly
coarse
resolutions
while
categories
not
taken
into
consideration.
In
this
study,
we
extend
the
previous
work
in
two
aspects
involving
introduction
semantically
fine-grained
(i.e.,
12
rooftop
classes)
spatially
representations
individual
buildings
with
compact
polygons.
Specifically,
develop
novel
framework
for
generation
3D
models,
including
developing
network
joint
classification,
another
parallel
estimation,
post-processing
algorithm
fusion
results
from
independent
networks.
To
train
networks
improve
generalization,
construct
custom
large-scale
datasets
addition
existing
Urban
Building
Classification
(UBC)
dataset
2023
IEEE
Data
Fusion
Contest
(DFC
2023)
dataset.
Finally,
nation-scale
fine-GrAined
BuiLding
modEl
(GABLE)
product
is
derived
based
Beijing-3
satellite
images
(0.5–0.8
m)
our
proposed
framework.
GABLE
provides
polygon,
category
value
each
instance.
Further
analyses
conducted
uncover
distribution
terms
diversity,
density.
These
demonstrate
significance
values
GALBE,
potentials
far
beyond
these.
Earth system science data,
Journal Year:
2022,
Volume and Issue:
14(8), P. 3835 - 3873
Published: Aug. 29, 2022
Abstract.
There
is
a
scientific
consensus
on
the
need
for
spatially
detailed
information
urban
landscapes
at
global
scale.
These
data
can
support
range
of
environmental
services,
since
cities
are
places
intense
resource
consumption
and
waste
generation
concentrated
infrastructure
human
settlement
exposed
to
multiple
hazards
natural
anthropogenic
origin.
In
face
climate
change,
also
required
explore
future
urbanization
pathways
design
strategies
in
order
lock
long-term
resilience
sustainability,
protecting
from
decisions
that
could
undermine
their
adaptability
mitigation
role.
To
serve
this
purpose,
we
present
100
m-resolution
map
local
zones
(LCZs),
universal
typology
distinguish
areas
holistic
basis,
accounting
typical
combination
micro-scale
land
covers
associated
physical
properties.
The
LCZ
map,
composed
10
built
7
cover
types,
generated
by
feeding
an
unprecedented
number
labelled
training
earth
observation
images
into
lightweight
random
forest
models.
Its
quality
assessed
using
bootstrap
cross-validation
alongside
thematic
benchmark
150
selected
functional
independent
open-source
surface
cover,
imperviousness,
building
height,
heat.
As
each
type
with
generic
numerical
descriptions
key
canopy
parameters
regulate
atmospheric
responses
urbanization,
availability
globally
consistent
climate-relevant
description
important
prerequisite
supporting
model
development
creating
evidence-based
climate-sensitive
planning
policies.
This
dataset
be
downloaded
https://doi.org/10.5281/zenodo.6364594
(Demuzere
et
al.,
2022a).
Nature Communications,
Journal Year:
2023,
Volume and Issue:
14(1)
Published: July 6, 2023
Abstract
OpenStreetMap
(OSM)
has
evolved
as
a
popular
dataset
for
global
urban
analyses,
such
assessing
progress
towards
the
Sustainable
Development
Goals.
However,
many
analyses
do
not
account
uneven
spatial
coverage
of
existing
data.
We
employ
machine-learning
model
to
infer
completeness
OSM
building
stock
data
13,189
agglomerations
worldwide.
For
1,848
centres
(16%
population),
footprint
exceeds
80%
completeness,
but
remains
lower
than
20%
9,163
cities
(48%
population).
Although
inequalities
have
recently
receded,
partially
result
humanitarian
mapping
efforts,
complex
unequal
pattern
biases
remains,
which
vary
across
various
human
development
index
groups,
population
sizes
and
geographic
regions.
Based
on
these
results,
we
provide
recommendations
producers
analysts
manage
data,
well
framework
support
assessment
biases.
Computers Environment and Urban Systems,
Journal Year:
2022,
Volume and Issue:
95, P. 101809 - 101809
Published: May 4, 2022
Characterising
and
analysing
urban
morphology
is
a
continuous
task
in
data
science,
environmental
analyses,
many
other
domains.
As
the
availability
quality
of
on
them
have
been
increasing,
buildings
gained
more
attention.
However,
tools
facilitating
large-scale
studies,
together
with
an
interdisciplinary
consensus
metrics,
remain
scarce
often
inadequate.
We
present
Global
Building
Morphology
Indicators
(GBMI)
—
three-pronged
contribution
addressing
such
shortcomings:
(i)
comprehensive
list
hundreds
building
form
multi-scale
measures
derived
through
systematic
literature
review;
(ii)
methodology
tool
for
computation
these
metrics
database
suited
big
comparative
release
code
freely
open-source;
(iii)
we
carry
out
computations
using
high
performance
computing,
generating
public
repository
quantifying
selected
areas
around
world,
demonstrate
their
value
novel
analyses
comparing
morphological
parameters
across
cities.
GBMI
introduces
formalised,
structured,
modular,
extensible
method
to
compute,
manage,
disseminate
indicators
at
large
scale
resolution,
while
precomputed
dataset
facilitates
studies.
The
theory
implementation
traverse
multiple
scales:
level,
both
individual
contextual
ones
based
encircling
by
buffers,
aggregations
several
hierarchical
administrative
levels
grids.
Our
open
dataset,
comprising
billions
records
growing
scope
worldwide,
most
instance
parametrising
stock,
supporting
studies
analytics
range
disciplines.
Proceedings of the National Academy of Sciences,
Journal Year:
2022,
Volume and Issue:
119(46)
Published: Nov. 7, 2022
Information
on
urban
built-up
infrastructure
is
essential
to
understand
the
role
of
cities
in
shaping
environmental,
economic,
and
social
outcomes.
The
lack
data
heights
over
large
areas
has
limited
our
ability
characterize
its
spatial
variations
across
world.
Here,
we
developed
a
global
atlas
circa
2015
at
500-m
resolution
from
Sentinel-1
Ground
Range
Detected
satellite
data.
Results
show
extreme
gaps
per
capita
Global
South
compared
with
average,
even
larger
average
levels
North.
Per
infrastructures
some
countries
North
are
more
than
30
times
higher
those
South.
results
also
that
45
combined,
∼16%
population,
roughly
equivalent
114
South,
∼74%
population.
inequality
infrastructure,
as
measured
by
an
index,
most
countries,
but
largest
Our
analysis
reveals
scale
demand
required
order
meet
sustainable
development
goals.
Nature Cities,
Journal Year:
2024,
Volume and Issue:
1(9), P. 555 - 566
Published: Aug. 5, 2024
Abstract
We
present
a
new
study
examining
the
dynamics
of
global
urban
building
growth
rates
over
past
three
decades.
By
combining
datasets
for
1,550+
cities
from
several
space-borne
sensors—data
scatterometers
and
settlement-built
fraction
based
on
Landsat-derived
data—we
find
profound
shifts
in
how
expanded
1990s
to
2010s.
Cities
had
both
increasing
fractional
cover
microwave
backscatter
(correlating
with
volume),
but
decades,
decreased
most
regions
large
cities,
while
increased
essentially
all
cities.
The
divergence
increase
these
metrics
indicates
shift
lateral
expansion
more
vertical
development.
This
transition
has
happened
different
decades
extents
across
world’s
Growth
rate
increases
were
largest
Asian
toward
development
consequences
material
energy
use,
local
climate
living.
Engineering,
Journal Year:
2024,
Volume and Issue:
unknown
Published: March 1, 2024
Three-dimensional
(3D)
urban
structures
play
a
critical
role
in
informing
climate
mitigation
strategies
aimed
at
the
built
environment
and
facilitating
sustainable
development.
Regrettably,
there
exists
significant
gap
detailed
consistent
data
on
3D
building
space
with
global
coverage
due
to
challenges
inherent
collection
model
calibration
processes.
In
this
study,
we
constructed
structure
dataset
(GUS-3D),
including
volume,
height,
footprint
information,
500
m
spatial
resolution
using
extensive
satellite
observation
products
numerous
reference
samples.
Our
analysis
indicated
that
total
volume
of
buildings
worldwide
2015
exceeded
1
×
1012
m3.
Over
1985
period,
observed
slight
increase
magnitude
growth
(i.e.,
it
increased
from
166.02
km3
during
1985–2000
period
175.08
2000–2015
period),
while
expansion
magnitudes
two-dimensional
(2D)
(22.51
103
km2
vs.
13.29
km2)
extent
(157
133.8
notably
decreased.
This
trend
highlights
intensive
vertical
utilization
land.
Furthermore,
identified
heterogeneity
provision
inequality
across
cities
worldwide.
is
particularly
pronounced
many
populous
Asian
cities,
which
has
been
overlooked
previous
studies
economic
inequality.
The
GUS-3D
shows
great
potential
deepen
our
understanding
creates
new
horizons
for
studies.
Journal of Remote Sensing,
Journal Year:
2024,
Volume and Issue:
4
Published: Jan. 1, 2024
Building,
as
an
integral
aspect
of
human
life,
is
vital
in
the
domains
urban
management
and
analysis.
To
facilitate
large-scale
planning
applications,
acquisition
complete
reliable
building
data
becomes
imperative.
There
are
a
few
publicly
available
products
that
provide
lot
data,
such
Microsoft
Open
Street
Map.
However,
East
Asia,
due
to
more
complex
distribution
buildings
scarcity
auxiliary
there
lack
these
regions,
hindering
application
Asia.
Some
studies
attempt
simulate
information
using
incomplete
local
footprints
through
regression.
reliance
on
inaccurate
introduces
cumulative
errors,
rendering
this
simulation
highly
unreliable,
leading
limitations
achieving
precise
research
Asian
region.
Therefore,
we
proposed
comprehensive
mapping
framework
view
complexity
conducted
extraction
2,897
cities
across
5
countries
Asia
yielded
substantial
dataset
281,093,433
buildings.
The
evaluation
shows
validity
our
product,
with
average
overall
accuracy
89.63%
F1
score
82.55%.
In
addition,
comparison
existing
further
high
quality
completeness
data.
Finally,
conduct
spatial
analysis
revealing
its
value
supporting
urban-related
research.
for
article
can
be
downloaded
from
https://doi.org/10.5281/zenodo.8174931
.
International Journal of Applied Earth Observation and Geoinformation,
Journal Year:
2022,
Volume and Issue:
112, P. 102859 - 102859
Published: June 17, 2022
3D
building
models
are
an
established
instance
of
geospatial
information
in
the
built
environment,
but
their
acquisition
remains
complex
and
topical.
Approaches
to
reconstruct
often
require
existing
(e.g.
footprints)
data
such
as
point
clouds,
which
scarce
laborious
acquire,
limiting
expansion.
In
parallel,
street
view
imagery
(SVI)
has
been
gaining
currency,
driven
by
rapid
expansion
coverage
advances
computer
vision
(CV),
it
not
used
much
for
generating
city
models.
Traditional
approaches
that
can
use
SVI
reconstruction
multiple
images,
while
practice,
only
few
street-level
images
provide
unobstructed
a
building.
We
develop
from
single
image
using
image-to-mesh
techniques
modified
CV
domain.
regard
three
scenarios:
(1)
standalone
single-view
reconstruction;
(2)
aided
top
delineating
footprint;
(3)
refinement
models,
i.e.
we
examine
enhance
level
detail
block
(LoD1)
common.
The
results
suggest
trained
supporting
able
overall
geometry
building,
first
scenario
may
derive
approximate
mass
useful
infer
urban
form
cities.
evaluate
demonstrating
usefulness
volume
estimation,
with
mean
errors
less
than
10%
last
two
scenarios.
As
is
now
available
most
countries
worldwide,
including
many
regions
do
have
footprint
and/or
data,
our
method
rapidly
cost-effectively
without
requiring
any
information.
Obtaining
hitherto
did
any,
enable
number
analyses
locally
time.
International Journal of Geographical Information Science,
Journal Year:
2022,
Volume and Issue:
37(1), P. 36 - 67
Published: Aug. 1, 2022
Urban
morphology
is
important
in
a
broad
range
of
investigations
across
the
fields
city
planning,
transportation,
climate,
energy,
and
urban
data
science.
Characterising
buildings
with
set
numerical
metrics
fundamental
to
studying
form.
Despite
rapid
developments
3D
geoinformation
science,
growing
availability,
most
studies
simplify
their
2D
footprint,
when
taking
height
into
account,
they
at
assume
one
value
per
building,
i.e.
simple
3D.
We
take
first
step
elevating
building
full/true
3D,
uncovering
use
higher
levels
detail,
account
detailed
shape
building.
foundation
new
research
line
on
by
providing
comprehensive
metrics,
implementing
them
openly
released
software,
generating
an
open
dataset
containing
for
823,000
Netherlands,
demonstrating
case
where
clusters
architectural
patterns
are
analysed
through
time.
Our
experiments
suggest
added
complement
existing
counterparts,
reducing
ambiguity,
advanced
insights.
Furthermore,
we
provide
comparative
analysis
using
different
detail
models.