International Journal of Applied Earth Observation and Geoinformation,
Год журнала:
2023,
Номер
125, С. 103601 - 103601
Опубликована: Дек. 1, 2023
Significant
advancements
in
Earth
Observation
(EO)
technologies,
encompassing
global
remote
sensing
and
environment
sensor
networks,
have
greatly
progressed
the
field
of
earth
science.
The
management
EO
sensors
is
crucial
collecting
effective
changing
data
real-time.
Over
past
few
decades,
Sensor
Management
(SM)
Multi-Sensor
(MSM)
been
extensively
applied
to
research
reviewed
previous
studies.
demands
for
become
highly
complex
with
advent
web
era,
necessitating
Integration
(MSIM),
which
an
advanced
development
MSM.
concept
MSIM
its
methods
discussed
worldwide,
prototypes
exhibited
remarkable
potential
applications.
However,
yet
be
a
long
time.
This
work
provides
detailed
overview
emergence
specifies
four
key
methods.
also
examines
typical
applications
EO.
Then,
this
identifies
future
directions
research.
review
concludes
that
has
emerged
as
novel
indispensable
paradigm
set
play
significant
role
advancement
science
practical
future.
Sustainability,
Год журнала:
2024,
Номер
16(19), С. 8337 - 8337
Опубликована: Сен. 25, 2024
This
review
paper
explores
Urban
Digital
Twins
(UDTs)
and
their
crucial
role
in
developing
smarter
cities,
focusing
on
making
urban
areas
more
sustainable
well-planned.
The
methodology
adopted
an
extensive
literature
across
multiple
academic
databases
related
to
UDTs
smart
sustainability,
environments,
conducted
by
a
bibliometric
analysis
using
VOSviewer
identify
key
research
trends
qualitative
through
thematic
categorization.
shows
how
can
significantly
change
cities
are
managed
planned
examining
examples
from
like
Singapore
Dubai.
study
points
out
the
main
hurdles
gathering
data,
connecting
systems,
handling
vast
amounts
of
information,
different
technologies
work
together.
It
also
sheds
light
what
is
missing
current
research,
such
as
need
for
solid
rules
effectively,
better
cooperation
between
various
city
deeper
look
into
affect
society.
To
address
gaps,
this
highlights
necessity
interdisciplinary
collaboration.
calls
establishing
comprehensive
models,
universal
standards,
comparative
studies
among
traditional
UDT
methods.
Finally,
it
encourages
industry,
policymakers,
academics
join
forces
realizing
sustainable,
cities.
Future Internet,
Год журнала:
2024,
Номер
16(2), С. 47 - 47
Опубликована: Янв. 30, 2024
Smart
cities,
leveraging
advanced
data
analytics,
predictive
models,
and
digital
twin
techniques,
offer
a
transformative
model
for
sustainable
urban
development.
Predictive
analytics
is
critical
to
proactive
planning,
enabling
cities
adapt
evolving
challenges.
Concurrently,
techniques
provide
virtual
replica
of
the
environment,
fostering
real-time
monitoring,
simulation,
analysis
systems.
This
study
underscores
significance
systems
support
test
scenarios
that
identify
bottlenecks
enhance
smart
city
efficiency.
paper
delves
into
crucial
roles
citizen
report
prediction,
technologies
at
neighborhood
level.
The
integrates
extract,
transform,
load
(ETL)
processes,
artificial
intelligence
(AI)
methodology
process
interpret
streams
derived
from
interactions
with
city’s
coordinate-based
problem
mapping
platform.
Using
an
interactive
GeoDataFrame
within
methodology,
dynamic
entities
facilitate
simulations
based
on
various
scenarios,
allowing
users
visualize,
analyze,
predict
response
system
approach
reveals
antecedent
patterns,
trends,
correlations
physical
level
each
area,
leading
improvements
in
functionality,
resilience,
resident
quality
life.
Smart Cities,
Год журнала:
2025,
Номер
8(1), С. 23 - 23
Опубликована: Фев. 5, 2025
The
rapid
evolution
of
smart
city
technologies
has
expanded
digital
twin
(DT)
applications
from
industrial
to
urban
contexts.
However,
current
twins
(UDTs)
remain
predominantly
focused
on
the
physical
aspects
environments
(“spaces”),
often
overlooking
interwoven
social
dimensions
that
shape
concept
“place”.
This
limitation
restricts
their
ability
fully
represent
complex
interplay
between
and
systems
in
settings.
To
address
this
gap,
paper
introduces
(SDT),
which
integrates
into
UDTs
bridge
divide
technological
lived
experience.
Drawing
an
extensive
literature
review,
study
defines
key
components
for
transitioning
SDTs,
including
conceptualization
modeling
human
interactions
(geo-individuals
geo-socials),
applications,
participatory
governance,
community
engagement.
Additionally,
it
identifies
essential
analytical
tools
implementing
outlines
research
gaps
practical
challenges,
proposes
a
framework
integrating
dynamics
within
UDTs.
emphasizes
importance
active
participation
through
governance
model
offers
comprehensive
methodology
support
researchers,
technology
developers,
policymakers
advancing
SDT
applications.
Abstract
This
study
focuses
on
the
application
of
deep
learning
for
transforming
semantic
point
clouds
into
Building
Information
Models
(BIM)
to
create
a
Heritage
Digital
Twin,
centering
Taoping
Village,
site
historical
and
cultural
significance
in
Sichuan,
China.
Utilizing
advanced
technologies
such
as
unmanned
aerial
vehicles
terrestrial
laser
scanning,
we
capture
detailed
cloud
data
village.
A
pivotal
element
our
methodology
is
KP-SG
neural
network,
which
exhibits
outstanding
overall
performance,
particularly
excelling
accurately
identifying
11
categories.
Among
those
categories,
buildings
vegetation,
achieves
recognition
rates
81%
83%
respectively,
2.53%
improvement
mIoU
compared
KP-FCNN.
accuracy
critical
constructing
accurate
BIM
models
facilitating
comprehensive
architecture
landscape
analysis.
Additionally,
KP-SG’s
superior
segmentation
capability
contributes
creation
high-fidelity
3D
models,
enriching
virtual
reality
experiences.
We
also
introduce
digital
twin
platform
that
integrates
diverse
datasets,
their
information,
visualization
tools.
designed
support
process
automation
decision-making
provide
immersive
experiences
tourists.
Our
approach,
integrating
platform,
marks
significant
advancement
preserving
understanding
traditional
villages
like
demonstrates
transformative
potential
heritage
conservation.
Smart
cities,
leveraging
advanced
data
analytics,
predictive
models,
and
digital
twin
techniques,
offer
a
transformative
model
for
sustainable
urban
development.
Predictive
analytics
plays
crucial
role
in
proactive
planning,
enabling
cities
to
adapt
evolving
challenges.
Concurrently,
techniques
provide
virtual
replica
of
the
environment,
fostering
real-time
monitoring,
simulation,
analysis
systems.
This
research
underscores
significance
systems
support
test
scenarios
that
identify
bottlenecks
enhance
smart
city
efficiency.
The
paper
delves
into
roles
citizen
report
prediction,
technologies
at
neighborhood
level.
study
integrates
ETL/ELT
processes,
AI
methodology
process
interpret
streams
derived
from
interactions
with
city's
coordinate-based
problem
mapping
platform.
By
employing
an
interactive
GeoDataFrame
within
methodology,
dynamic
entities
facilitate
simulations
based
on
various
scenarios.
approach
enables
users
visualize,
analyze,
predict
response
system
Consequently,
antecedent
patterns,
trends,
correlations
are
visualized
physical
level
each
area,
leading
improvements
functionality,
resilience,
resident
quality
life.
