Research Square (Research Square),
Год журнала:
2023,
Номер
unknown
Опубликована: Ноя. 21, 2023
Abstract
In
the
hunt
for
seismic
precursors
with
GNSS
to
detect
earthquake-related
anomalies
in
ionosphere
are
proved
as
an
effective
strategy.
One
method
is
use
TEC
distinguish
between
and
induced
by
geo
magnetic
storm.
this
study,
data
of
four
sites
near
epicenter
November
30,
2018,
Alaska
earthquake
(Mw
7.1)
examined.
We
also
examined
from
Swarm
satellites
during
local
day
nighttime
further
support
EQ-induced
perturbations
ionosphere.
six
days
before
major
EQ,
stations'
displayed
considerable
disturbance
positive
crossing
upper
bound.
The
stations
EQ
detected
1
6
prior
EQ.
swarm
confirmed
these
findings.
On
other
hand,
retrieving
all
preparation
phase
weak
storm
(Kp
4,
Dst
−
50
nT),
we
discover
evidence
low-intensity
25–30
shock.
Further
research
shows
that
UTC
17:30
23:00
storm-induced
anomaly
(caused
=
-50
nT
Kp
4)
predominates
17:00
23:30.
phase,
primary
shock
helpful
separating
geomagnetic
anomalies.
Additionally,
using
monitoring,
work
contributes
growing
lithosphere-ionosphere
connection
concept.
Pure and Applied Geophysics,
Год журнала:
2024,
Номер
181(5), С. 1455 - 1478
Опубликована: Апрель 16, 2024
Abstract
In
this
study,
the
atmospheric
changes
for
9.0-magnitude
Tohoku
earthquake,
which
occurred
on
March
11,
2011,
are
analyzed.
The
2011
earthquake
was
preceded
by
a
large
foreshock
09,
with
magnitude
M
7.3
and
depth
32
km
at
02:45:20
UT
near
east
coast
of
Honshu,
Japan.
doesn’t
limit
its
effects
Earth’s
lithosphere,
hydrosphere
biosphere;
it
also
extends
to
atmosphere
because
gas
emissions,
produce
large-scale
seismic
waves
from
ground
release
gases
into
atmosphere.
anomalies
parameters
studied
using
one
models
Naval
Research
Laboratory
Mass
Spectrometer
Incoherent
Scatter
Extension
2000
(NRLMSISE-00)
model
data
analyze
Earthquake
2011.
atomic
oxygen
(O),
hydrogen
(H),
nitrogen
(N),
helium
(He),
argon
(Ar),
molecular
(O
2
),
(N
total
mass
density
(ρ),
neutral
temperature
(Tn),
exospheric
(Tex)
anomalous
(AO)
used
analysis
during
occurrence.
epicenter
geographical
location
latitude
38.30°
N
longitude
142.37°
E,
is
NRLMSISE-00
as
input
output
parameters.
To
compare
caused
5
days
before
after
considered.
detect
where
increased
or
decreased
day,
percentage
deviation
applied.
results
indicate
that
there
were
parameter
few
before,
following
Except
all
average
daily
values
positive
respect
main
shock
can
capture
well.
Remote Sensing,
Год журнала:
2024,
Номер
16(9), С. 1542 - 1542
Опубликована: Апрель 26, 2024
Studies
have
demonstrated
the
potential
of
satellite
thermal
infrared
observations
to
detect
anomalous
signals
preceding
large
earthquakes.
However,
lack
well-defined
precursory
characteristics
and
inherent
complexity
stochasticity
seismicity
continue
impede
robust
earthquake
forecasts.
This
study
investigates
pre-seismic
anomalies,
derived
from
five
satellite-based
geophysical
parameters,
i.e.,
skin
temperature,
air
total
integrated
column
water
vapor
burden,
outgoing
longwave
radiation
(OLR),
clear-sky
OLR,
as
valuable
indicators
for
global
We
employed
a
spatially
self-adaptive
multiparametric
anomaly
identification
scheme
refine
these
then
estimated
posterior
probability
an
occurrence
given
observed
anomalies
within
Bayesian
framework.
Our
findings
reveal
promising
link
between
signatures
seismicity,
with
elevated
forecast
probabilities
exceeding
0.1
significant
gains
in
some
strong
earthquake-prone
regions.
A
time
series
analysis
indicates
stabilization
after
approximately
six
years.
While
no
single
parameter
consistently
dominates,
each
contributes
information,
suggesting
avenue
multi-parametric
approach.
Furthermore,
novel
indices
incorporating
probabilistic
information
significantly
reduce
false
alarms
improve
recognition.
Despite
remaining
challenges
developing
dynamic
short-term
probabilities,
rigorously
testing
detection
algorithms,
improving
ensemble
strategies,
this
provides
compelling
evidence
play
key
role
The
ability
reliably
estimate
ever-present
threat
destructive
earthquakes,
holds
considerable
societal
ecological
importance
mitigating
risk
preparedness
strategies.
Remote Sensing,
Год журнала:
2023,
Номер
15(24), С. 5690 - 5690
Опубликована: Дек. 11, 2023
Earthquakes
occur
all
around
the
world,
causing
varying
degrees
of
damage
and
destruction.
are
by
their
very
nature
a
sudden
phenomenon
predicting
them
with
precise
time
range
is
difficult.
Some
phenomena
may
be
indicators
physical
conditions
favorable
for
large
earthquakes
(e.g.,
ionospheric
Total
Electron
Content
(TEC)).
The
TEC
an
important
parameter
used
to
detect
pre-earthquake
changes
measuring
disturbances
space
weather
indices,
such
as
global
geomagnetic
index
(Kp),
storm
duration
distribution
(Dst),
sunspot
number
(R),
(Ap-index),
solar
wind
speed
(Vsw),
activity
(F10.7),
have
also
been
changes.
In
this
study,
feasibility
6th-day
earthquake
prediction
deep
neural
network
technique
using
previous
five
consecutive
days
investigated.
For
purpose,
two-staged
approach
developed.
first
stage,
various
preprocessing
steps,
namely
signal
improvement
time-frequency
representation-based
image
construction,
performed.
second
multi-input
convolutional
(CNN)
model
designed
trained
in
end-to-end
fashion.
This
CNN
has
total
six
inputs,
inputs
2D
sixth
1D
vector.
images
vector
input
concatenated
indices.
branches
contain
convolution,
batch
normalization,
Rectified
Linear
Unit
(ReLU)
activation
layers,
branch
contains
ReLU
layer.
outputs
flattened
then
concatenated.
And
classification
performed
via
fully
connected,
softmax,
respectively.
experimental
work,
magnitude
Mw5.0
above
that
occurred
Turkey
between
2012
2019
dataset.
data
were
recorded
National
Permanent
GNSS
Network-Active
(TNPGN-Active)
Global
Navigation
Satellite
System
(GNSS)
stations.
before
marked
“precursor
days”
after
“normal
days”.
total,
75%
dataset
train
proposed
method
25%
testing.
accuracy,
sensitivity,
specificity,
F1-score
values
obtained
performance
evaluations.
results
promising,
89.31%
accuracy
obtained.
Remote Sensing,
Год журнала:
2024,
Номер
16(11), С. 1839 - 1839
Опубликована: Май 22, 2024
This
paper
presents
a
multi-parameter
ionospheric
disturbance
analysis
of
the
total
electron
content
(TEC),
density
(Ne),
temperature
(Te),
and
critical
frequency
foF2
variations
preceding
two
significant
earthquake
events
(2015
Mw
7.5
2023
6.3)
that
occurred
in
Afghanistan.
The
from
various
ground
stations
low-Earth-orbit
satellite
measurements
involved
employing
sliding
interquartile
method
to
process
TEC
data
Global
Ionospheric
Maps
(GIMs),
comparing
revisit
trajectories
identify
anomalies
Ne
Te
Swarm
satellites,
applying
machine
learning-based
envelope
estimation
for
GPS-derived
measurements,
utilizing
least
square
ionograms
obtained
available
base
Ionosphere
Radio
Observatory
(GIRO).
After
excluding
potential
influences
caused
by
solar
geomagnetic
activities,
following
phenomena
were
revealed:
(1)
GIM-TEC
displayed
positive
one
day
before
2015
earthquake,
while
on
shock
days
(7,
11,
15)
6.3
earthquake;
(2)
observations
(Ne
Te)
earthquakes
followed
almost
same
appearance
rates
as
GIM-TEC,
negative
correlation
between
values
was
found,
with
clearer
at
night;
(3)
there
prominent
8
3
h
selected
GPS
stations,
which
nearest
preparation
area.
anomalous
height
plasma
verified
analyzing
foF2,
confirmed
perturbations.
Unusual
disturbances
indicate
imminent
pre-seismic
events,
provides
opportunity
provide
aid
prediction
natural
hazard
risk
management
Afghanistan
nearby
regions.
Remote Sensing,
Год журнала:
2023,
Номер
15(19), С. 4852 - 4852
Опубликована: Окт. 7, 2023
The
air
temperature
changes
in
the
Palu
MW7.5
earthquake
Indonesia
on
28
September
2018
were
analyzed,
based
additive
tectonic
stress
caused
by
celestial
tidal-generating
forces
(ATSCTF)
and
data
from
National
Center
for
Environmental
Prediction
(NCEP).
This
paper
explored
variation
characteristics
of
three-dimensional
stratified
seismic
activity
coupling
relationship
between
tidal
force.
background
information
calculation
was
obtained
force
changes,
increment
method
used
to
study
evolution
process
different
periods
area.
results
found
that
acting
critical
state
faults
may
be
an
important
external
factor
inducing
earthquakes,
there
indeed
a
significant
increase
anomaly
during
earthquake.
also
summarized
abnormal
activity:
closer
land’s
surface
has
greater
amplitude
wider
area
than
upper
air.
VFAST Transactions on Software Engineering,
Год журнала:
2024,
Номер
12(1), С. 133 - 151
Опубликована: Март 31, 2024
In
this
article,
impact
of
climatic
anomalies
and
artificial
hydraulic
loading
on
earthquake
generation
has
been
studied
using
federated
learning
(FL)
technique
a
model
for
the
prediction
proposed.
Federated
Learning
being
one
most
recent
techniques
machine
(ML)
guarantees
that
proposed
possesses
intrinsic
ability
to
handle
all
concerns
related
data
involving
privacy,
availability,
security,
network
latency
glitches
involved
in
by
restricting
transmission
during
different
stages
training.
The
main
objective
study
is
determine
stresses
increase
decrease
regional
seismicity.
Experimental
verification
carried
out
within
100
km
radial
area
from
34.708o
N,
72.5478o
E
Western
Himalayan
region.
Regional
atmospheric
temperature,
air
pressure,
rainfall,
water
level
reservoir
seismicity
collected
hourly
bases
1985
till
2022.
research,
four
client
stations
at
points
selected
have
established
train
local
models
calculating
time
lag
correlation
between
multiple
parameters.
These
are
transmitted
central
server
where
global
trained
generating
alert
with
ten
days
lead
alarming
specific
reported
high
among
parameters
about
expected
earthquake.
