Geo-spatial Information Science,
Год журнала:
2025,
Номер
unknown, С. 1 - 18
Опубликована: Янв. 17, 2025
This
systematic
review
explores
the
utilization
of
crowdsourcing
for
geoinformation
in
enhancing
awareness
and
mitigating
terrorism-related
disasters.
Out
519
studies
identified
database
search,
108
were
deemed
eligible
analysis.
We
focused
on
articles
employing
various
forms
platforms,
such
as
Twitter
(now
known
X),
Facebook,
Telegram,
across
three
distinct
phases
disasters:
monitoring
detection,
onset,
post-incident
Notably,
we
placed
particular
emphasis
integration
Machine
Learning
(ML)
algorithms
studying
crowdsourced
terrorism
to
assess
current
state
research
propose
future
directions.
The
findings
revealed
that
emerged
predominant
platform
information.
Despite
prevalence
natural
language
processing
data
mining,
majority
did
not
incorporate
ML
their
analyses.
preference
qualitative
methods
can
be
attributed
multifaceted
nature
terrorism,
spanning
security,
governance,
politics,
religion,
law.
Our
advocacy
is
increased
from
domains
geography,
earth
observation,
big
data.
Simultaneously,
encourage
advancements
existing
enhance
accurate
real-time
detection
planned
onset
Sustainable Cities and Society,
Год журнала:
2023,
Номер
94, С. 104562 - 104562
Опубликована: Март 29, 2023
In
recent
years,
artificial
intelligence
(AI)
has
been
increasingly
put
into
use
to
address
cities'
economic,
social,
environmental,
and
governance
challenges.
Thanks
its
advanced
capabilities,
AI
is
set
become
one
of
local
governments'
principal
means
achieving
smart
sustainable
development.
utilisation
for
urban
planning,
nonetheless,
a
relatively
understudied
area
research,
particularly
in
terms
the
gap
between
theory
practice.
This
study
presents
comprehensive
review
areas
planning
which
technologies
are
contemplated
or
applied,
it
analysed
how
support
could
potentially
Regarding
methodological
approach,
this
systematic
literature
following
PRISMA
protocol.
The
obtained
insights
include:
(a)
Early
adopters'
real-world
applications
paving
way
wider
government
adoption;
(b)
Achieving
adoption
involves
collaboration
partnership
key
stakeholders;
(c)
Big
data
an
integral
element
effective
and;
(d)
Convergence
human
crucial
urbanisation
issues
adequately
achieve
These
highlight
importance
making
smarter
through
analytical
methods.
Neural Computing and Applications,
Год журнала:
2023,
Номер
35(31), С. 23103 - 23124
Опубликована: Сен. 7, 2023
Abstract
The
current
development
in
deep
learning
is
witnessing
an
exponential
transition
into
automation
applications.
This
can
provide
a
promising
framework
for
higher
performance
and
lower
complexity.
ongoing
undergoes
several
rapid
changes,
resulting
the
processing
of
data
by
studies,
while
it
may
lead
to
time-consuming
costly
models.
Thus,
address
these
challenges,
studies
have
been
conducted
investigate
techniques;
however,
they
mostly
focused
on
specific
approaches,
such
as
supervised
learning.
In
addition,
did
not
comprehensively
other
techniques,
unsupervised
reinforcement
techniques.
Moreover,
majority
neglect
discuss
some
main
methodologies
learning,
transfer
federated
online
Therefore,
motivated
limitations
existing
this
study
summarizes
techniques
supervised,
unsupervised,
reinforcement,
hybrid
learning-based
addition
each
category,
brief
description
categories
their
models
provided.
Some
critical
topics
namely,
transfer,
federated,
models,
are
explored
discussed
detail.
Finally,
challenges
future
directions
outlined
wider
outlooks
researchers.
Remote Sensing,
Год журнала:
2023,
Номер
15(5), С. 1316 - 1316
Опубликована: Фев. 27, 2023
Metropolitan
areas
worldwide
have
grown
rapidly
and
are
usually
surrounded
by
peri-urban
zones
that
neither
urban
nor
rural.
Despite
widespread
use
of
the
term
‘peri-urban’,
physical
determination
these
spaces
is
difficult
due
to
their
transient
nature
multiple
definitions.
While
many
identified
regionally
or
globally,
questions
persist
on
where
exactly
located,
what
most
apt
methods
delineate
its
boundaries.
The
answers
pertinent
towards
framing
targeted
policies
for
governing
dynamic
socio-spatial
transformations
in
zones.
This
paper
reviews
research
over
last
50-plus
years
discern
existing
methodologies
identification/demarcation
applications.
For
this,
a
total
3124
documents
studies
were
through
keyword
searches
Scopus
Google
Scholar
databases.
Thereafter,
56
examined
explicitly
dealt
with
demarcating
Results
reveal
there
no
standout/generalized
method
demarcation.
Rather,
approaches
geographically
specific
vary
across
developed
developing
countries,
differences
land-use
patterns,
socioeconomic
drivers,
political
systems.
Thus,
we
recommend
‘pluralistic’
framework
determining
boundaries
at
regional–global
scale
enable
better
relevant
policies.
International Journal of Applied Earth Observation and Geoinformation,
Год журнала:
2024,
Номер
128, С. 103734 - 103734
Опубликована: Март 11, 2024
This
paper
brings
a
comprehensive
systematic
review
of
the
application
geospatial
artificial
intelligence
(GeoAI)
in
quantitative
human
geography
studies,
including
subdomains
cultural,
economic,
political,
historical,
urban,
population,
social,
health,
rural,
regional,
tourism,
behavioural,
environmental
and
transport
geography.
In
this
extensive
review,
we
obtain
14,537
papers
from
Web
Science
relevant
fields
select
1516
that
identify
as
studies
using
GeoAI
via
scanning
conducted
by
several
research
groups
around
world.
We
outline
applications
systematically
summarising
number
publications
over
years,
empirical
across
countries,
categories
data
sources
used
applications,
their
modelling
tasks
different
subdomains.
find
out
existing
have
limited
capacity
to
monitor
complex
behaviour
examine
non-linear
relationship
between
its
potential
drivers—such
limits
can
be
overcome
models
with
handle
complexity.
elaborate
on
current
progress
status
within
each
subdomain
geography,
point
issues
challenges,
well
propose
directions
opportunities
for
future
context
sustainable
open
science,
generative
AI,
quantum
revolution.
Sustainable Cities and Society,
Год журнала:
2023,
Номер
100, С. 105047 - 105047
Опубликована: Ноя. 8, 2023
Computer
vision
(CV)
technology,
a
key
subset
of
artificial
intelligence,
provides
powerful
tools
for
extracting
valuable
insights
from
visual
data,
which
is
crucial
component
the
urban
planning
process.
Despite
promising
potential
CV
in
planning,
its
applications
this
context
have
not
been
thoroughly
examined.
This
lack
scholarship
represents
critical
knowledge
gap
our
understanding
role
planning.
paper
aims
to
provide
consolidated
process
and
challenges
planners
face
during
adoption
CV.
The
conducts
systematic
literature
review
tackle
questions
how
applied
process,
what
are
adopting
techniques
process?
findings
revealed:
(a)
could
support
broad
range
tasks
including
data
collection
analysis,
issue
identification
prioritisation,
public
participation,
plan
design
adoption,
implementation
evaluation;
(b)
improve
decision-making
through
various
information,
but
limitations
need
be
considered,
and;
(c)
Utilisation
efforts
sustainable
development.
study
informs
policy-
plan-making
circles
by
providing
into
existing
prospective
contributions
transforms
augments
practices,
elaborates
adoption.
Energy and Built Environment,
Год журнала:
2023,
Номер
5(6), С. 957 - 969
Опубликована: Июль 23, 2023
As
the
world
continues
to
urbanize
at
an
unprecedented
rate,
energy
demand
in
cities
is
rising.
Buildings
account
for
over
75%
of
all
consumed
and
are
responsible
two-thirds
emissions.
Assessment
buildings
a
highly
integrative
endeavour,
bringing
together
interdisciplinary
fields
urban
studies,
along
with
host
technical
domains
namely,
geography,
engineering,
economics,
sociology,
planning.
In
last
decade,
several
building
modelling
tools
(UBEMs)
have
been
developed
estimation
as
well
prediction
cities.
These
models
useful
policymaking
they
can
evaluate
future
scenarios.
However,
data
acquisition
generating
input
database
UBEM
has
major
challenge.
this
review,
comprehensive
assessment
potential
remote
sensing
GIS
techniques
presented.
Firstly,
most
common
variables
identified
by
reviewing
recent
publications
on
then
studies
related
corresponding
these
explored.
More
than
140
research
papers
review
articles
relevant
applications
level
extraction
areas
investigated
purpose.
After
going
through
details
required
each
components
studying
possibility
acquiring
some
those
using
sensing,
it
inferred
that
satellite
Unmanned
Aerial
Vehicles
(UAVs)
strong
enhancing
space
but
their
applicability
limited.
Further,
challenges
usage
technologies
possible
solutions
also
presented
study.
It
recommended
utilise
existing
methodologies
extracting
information
from
UBEM,
newer
such
machine
learning
artificial
intelligence.
Applied Energy,
Год журнала:
2023,
Номер
350, С. 121765 - 121765
Опубликована: Авг. 25, 2023
The
transportation
sector
accounts
for
61.5%
of
global
oil
consumption
and
is
responsible
29%
the
world's
total
energy
demand.
Passenger
utilizes
around
50%–60%
used
transportation-related
activities.
Accurate
prediction
future
essential
governments
to
make
well-informed
decisions
regarding
infrastructure
development
utilization,
which
supports
United
Nations'
Sustainable
Development
Goals
(SDGs)
advances
shift
a
net-zero
carbon
economy.
With
expected
increase
in
population,
vehicles,
economic
growth,
it
predict
demand
ensure
sustainable
urban
transportation.
This
crucial
not
only
prosperity
but
also
promoting
human
health
mitigating
emissions.
Therefore,
plays
vital
role
designing
making
informed
investment
policy
decisions.
study
proposes
novel
methodology
investigates
application
machine
learning
stacking
ensemble
method
with
hyperparameter
tuning
multicollinearity
removal
Turkey
based
on
historic
data
from
1975–2019.
dataset
includes
GDP,
year,
vehicle
miles
traveled,
price,
passenger
ton-miles
traveled
as
features.
A
performance
evaluation
comparison
19
algorithms
first
carried
out
find
best
candidate
models,
including
eXtreme
Gradient
Boosting
algorithm.
uses
all
features
two
them
during
training
phase,
takes
into
consideration
4-fold
cross-validation.
combination
permutation
importance
hierarchical
clustering
algorithm
Spearman
rank-order
correlations
dimensionality
reduction
dataset.
Extra
Tree
Regressor
ADABoost
Regressor,
are
both
placed
second
level
suggested
meta-regressors
that
proposed
ensembles
because
they
perform
better
compared
single
In
total,
eight
models
–
four
each
were
developed
investigated
considering
separately.
Six
metrics
R-squared,
MSE,
MAE,
RMSE,
RMSLE,
MAPE
assess
models.
Trees
can
be
meta-regressor
model
achieves
an
R-squared
value
approximately
0.99
when
taken
consideration.
When
considered
same
achieve
accuracy
0.98.
These
findings
have
potential
contribute
more
accurate
results,
can,
turn,
lead
improved
strategies
managing
Additionally,
this
research
support
advancement
alternative
technologies
promote
development,
ultimately
helping
move
towards
Buildings,
Год журнала:
2023,
Номер
13(3), С. 644 - 644
Опубликована: Фев. 28, 2023
Characterising
and
predicting
socio-spatial
experience
has
long
been
a
key
research
question
in
space
syntax
research.
Due
to
the
lack
of
synthesised
knowledge
about
it,
this
review
conducts
first
systematic
scoping
on
relationships
between
spatial
properties
experiential
values.
Adopting
“Preferred
Reporting
Items
for
Systematic
reviews
Meta-Analyses”
(PRISMA)
framework,
identifies
38
studies
that
examine
experiences
architectural,
medical,
urban
spaces.
The
data
arising
from
are
used
identify
trends
sub-field
research,
including
growth
methods
applications
analytics
since
2016
methodological
approaches,
characteristics,
factors
experience.
identified
using
framework
employs
mixture
descriptive,
correlation,
regression
dynamic
effects
configurations
human
experiences.
Arising
results
review,
article
further
collective,
predictive
model
consisting
five
syntactic
predictors
three
categories
This
article,
finally,
examines
gaps
limitations
body
suggests
future
directions.
Artificial Intelligence in Agriculture,
Год журнала:
2024,
Номер
13, С. 45 - 63
Опубликована: Июнь 26, 2024
Machine
learning
and
deep
are
subsets
of
Artificial
Intelligence
that
have
revolutionized
object
detection
classification
in
images
or
videos.
This
technology
plays
a
crucial
role
facilitating
the
transition
from
conventional
to
precision
agriculture,
particularly
context
weed
control.
Precision
which
previously
relied
on
manual
efforts,
has
now
embraced
use
smart
devices
for
more
efficient
detection.
However,
several
challenges
associated
with
detection,
including
visual
similarity
between
crop,
occlusion
lighting
effects,
as
well
need
early-stage
Therefore,
this
study
aimed
provide
comprehensive
review
application
both
traditional
machine
learning,
combination
two
methods,
across
different
crop
fields.
The
results
show
advantages
disadvantages
using
learning.
Generally,
produced
superior
accuracy
compared
under
various
conditions.
required
selection
right
features
achieve
high
classifying
conditions
consisting
early
growth
effects.
Moreover,
precise
segmentation
stage
would
be
cases
occlusion.
had
advantage
achieving
real-time
processing
by
producing
smaller
models
than
thereby
eliminating
additional
GPUs.
development
GPU
is
currently
rapid,
so
researchers
often
accurate
identification.