IntechOpen eBooks,
Год журнала:
2022,
Номер
unknown
Опубликована: Июнь 24, 2022
The
objective
of
spatial
analysis
techniques
is
to
describe
the
patterns
existing
in
data
and
establish,
preferably
quantitatively,
relationships
between
different
geographic
variables.
notion
a
Geographic
Information
Systems
(GIS)
environment
encompasses
idea
integrating
alphanumeric
attributes
translating
it
into
series
functions
related
selection
search,
on
one
hand,
with
modeling,
other.
There
have
been
substantial
advances
GIS,
mainly
form
more
faithfully
apprehending
inherent
phenomenon,
something
that
was
proven
impossible
do
non-spatial
techniques.
Nowadays,
involves
set
used
analyze
model
variables
distribution
space
and/or
time.
new
era
must
also
consider
possibilities
artificial
intelligence
simulation
(geosimulation)
processes
computerized
environments
(geocomputation)
close
relationship
models
developed
real
situations.
GIS
emerged
as
useful
tools
modeling
processes,
helping
answer
questions
about
time
variability
landscape
structure,
study
behavior
fire,
predict
areas
urban
expansion,
propagation
phenomena,
animal
movement
behavior,
determine
periods
high
risk
flooding,
among
other
phenomena.
GIS
Spatial
Analysis
critical
book
provides
methodologies
combine
potential
(including
Big
Data)
applications.
It
gives
readers
comprehensive
overview
current
state-of-the-art
methods
analysis,
focusing
both
philosophical
theoretical
foundations
for
flexible
framework
world,
problems
such
complexity
uncertainty.
Sustainable Cities and Society,
Год журнала:
2024,
Номер
104, С. 105301 - 105301
Опубликована: Фев. 23, 2024
Numerous
studies
have
explored
influencing
factors
in
COVID-19,
yet
empirical
evidence
on
spatiotemporal
dynamics
of
COVID-19
inequalities
concerning
both
socioeconomic
and
environmental
at
an
intra-urban
scale
is
lacking.
This
study,
therefore,
focuses
neighborhood-level
spatial
the
incidences
relation
to
for
Berlin-Neukölln,
Germany,
covering
six
pandemic
periods
(March
2020
December
2021).
Spatial
Bayesian
negative
binomial
mixed-effect
models
were
employed
identify
risk
patterns
different
periods.
We
identified
that
(1)
relative
risks
varied
across
time
space,
with
sociodemographic
exerting
a
stronger
influence
over
features;
(2)
as
most
predictors,
population
migrant
backgrounds
was
positively
associated,
65
negatively
associated
incidence;
(3)
certain
neighborhoods
consistently
faced
elevated
incidence.
study
highlights
potential
structural
health
within
communities,
lower
status
higher
incidence
diverse
Our
findings
indicate
locally
tailored
interventions
citizens
are
essential
address
foster
more
sustainable
urban
environment.
ISPRS International Journal of Geo-Information,
Год журнала:
2022,
Номер
11(3), С. 152 - 152
Опубликована: Фев. 22, 2022
Exploring
the
spatial
patterns
of
COVID-19
transmission
and
its
key
determinants
could
provide
a
deeper
understanding
evolution
pandemic.
The
goal
this
study
is
to
investigate
in
different
periods
Singapore,
as
well
their
relationship
with
demographic
built-environment
factors.
Based
on
reported
cases
from
23
January
30
September
2020,
we
divided
research
time
into
six
phases
used
autocorrelation
analysis,
ordinary
least
squares
(OLS)
model,
multiscale
geographically
weighted
regression
(MGWR)
dominance
analysis
explore
influencing
factors
each
phase.
results
showed
that
differed
across
time,
imported
presented
random
pattern,
whereas
local
clustered
pattern.
Among
selected
variables,
supermarket
density,
elderly
population
hotel
business
land
proportion,
park
density
may
be
particular
fitting
indicators
explaining
pandemic
development
Singapore.
Furthermore,
associations
between
changed
dynamically
over
time.
This
provides
policymakers
valuable
information
for
developing
targeted
interventions
certain
areas
periods.
COVID,
Год журнала:
2023,
Номер
3(11), С. 1648 - 1662
Опубликована: Окт. 29, 2023
The
goal
of
this
study
is
to
analyze
associations
between
COVID-19
transmission
and
meteorological
indicators
in
cities
the
Black
Sea
region
Turkey,
located
specifically
dampest
area,
with
excess
rainfall
recurring
fog.
In
particular,
working
hypothesis
that
widespread
new
coronavirus
SARS-CoV-2
(leading
airborne
disease
COVID-19)
can
be
explained
by
specific
weather
conditions,
namely
high
levels
air
humidity.
Statistical
evidence
here
does
not
seem,
general,
support
accelerated
studied
humidity
because
different
meteorological,
environmental,
demographic,
socioeconomic
factors
also
plays
a
critical
role
dynamics
investigated
region.
main
implications
our
findings
are
demographic
structure
population,
climate
indicators,
organization
health
system,
environmental
(e.g.,
pollution,
etc.)
should
considered
through
systemic
approach
when
designing
effective
national
regional
pandemic
plans
directed
implement
policies
for
facing
variants
and/or
diseases,
order
reduce
their
negative
effects
on
health,
social
economic
systems.
Heliyon,
Год журнала:
2024,
Номер
10(2), С. e24702 - e24702
Опубликована: Янв. 1, 2024
The
contagious
COVID-19
has
recently
emerged
and
evolved
into
a
world-threatening
pandemic
outbreak.
After
pursuing
rigorous
prophylactic
measures
two
years
ago,
most
activities
globally
reopened
despite
the
emergence
of
lethal
genetic
strains.
In
this
context,
assessing
mapping
activity
characteristics-based
hot
spot
regions
facilitating
infectious
transmission
is
essential.
Hence,
our
research
question
is:
How
can
potential
hotspots
risk
be
defined
intra-cities
based
on
spatial
planning
commercial
in
particular?
research,
Zayed
October
cities,
Egypt,
characterized
by
various
activities,
were
selected
as
testbeds.
First,
we
analyzed
each
activity's
morphological
characteristics
infection
Centre
for
Disease
Control
Prevention
(CDCP)
criteria
Kriging
Interpolation
method.
Then,
using
Google
Mobility,
previous
reports,
semi-structured
interviews,
points
interest
population
flow
combined
with
last
step
interrelated
horizontal
layers
determining
hotspots.
A
validation
study
compared
generated
map,
cases,
land
use
distribution
logistic
regression
(LR)
Pearson
coefficients
(rxy).
Through
visual
analytics,
findings
indicate
central
areas
both
including
incompatible
concentrated
have
high-risk
peaks
(LR
=
0.903,
rxy
0.78)
medium
urban
density
districts,
indicating
that
alone
insufficient
public
health
reduction.
Health
perspective-based
configuration
advised
assessment
tool
along
appropriate
decision-making
shaping
pandemic-resilient
cities.
