Applying a 1D Convolutional Neural Network in Flood Susceptibility Assessments—The Case of the Island of Euboea, Greece
Remote Sensing,
Год журнала:
2023,
Номер
15(14), С. 3471 - 3471
Опубликована: Июль 10, 2023
The
main
scope
of
the
study
is
to
evaluate
prognostic
accuracy
a
one-dimensional
convolutional
neural
network
model
(1D-CNN),
in
flood
susceptibility
assessment,
selected
test
site
on
island
Euboea,
Greece.
Logistic
regression
(LR),
Naïve
Bayes
(NB),
gradient
boosting
(GB),
and
deep
learning
(DLNN)
are
benchmark
models
used
compare
their
performance
with
that
1D-CNN
model.
Remote
sensing
(RS)
techniques
collect
necessary
related
data,
whereas
thirteen
flash-flood-related
variables
were
as
predictive
variables,
such
elevation,
slope,
plan
curvature,
profile
topographic
wetness
index,
lithology,
silt
content,
sand
clay
distance
faults,
river
network.
Weight
Evidence
method
was
applied
calculate
correlation
among
flood-related
assign
weight
value
each
variable
class.
Regression
analysis
multi-collinearity
assess
collinearity
Shapley
Additive
explanations
rank
features
by
importance.
evaluation
process
involved
estimating
ability
all
via
classification
accuracy,
sensitivity,
specificity,
area
under
success
rate
curves
(AUC).
outcomes
confirmed
provided
higher
(0.924),
followed
LR
(0.904)
DLNN
(0.899).
Overall,
1D-CNNs
can
be
useful
tools
for
analyzing
using
remote
high
predictions.
Язык: Английский
Bibliometric Analysis of Spatial Technology for World Heritage: Application, Trend and Potential Paths
Remote Sensing,
Год журнала:
2023,
Номер
15(19), С. 4695 - 4695
Опубликована: Сен. 25, 2023
World
heritage
sites
are
monuments
and
natural
landscapes
recognised
by
all
humanity
as
being
of
outstanding
significance
universal
value.
Spatial
technology
provides
new
ideas
for
the
conservation
sustainable
development
world
sites.
Using
a
bibliometric
analysis,
this
study
extracted
401
relevant
documents
from
Web
Science
database
1990–2022.
Meta
information,
such
abstracts,
keywords
papers
were
cleaned
using
package
analysed
applications,
partnerships
trends
existing
spatial
technologies
The
results
show
“4D”
characteristics
space
in
sites:
(1)
Development:
applications
have
gradually
developed
with
an
annual
growth
rate
10.22%
during
period
(2)
Discrepancy:
More
than
70
per
cent
countries
not
been
able
to
fully
apply
on
ground
at
(3)
Desirability:
Shared
exchanges
between
research
institutions
rare,
more
cooperation
expected,
especially
transnationals.
(4)
Diversity:
future
outlook
will
be
multidisciplinary,
multi-method
integrated
research.
Язык: Английский