Traitement du signal,
Journal Year:
2023,
Volume and Issue:
40(4), P. 1501 - 1509
Published: Aug. 31, 2023
In
the
realm
of
geological
and
mineral
exploration,
remote
sensing
technology
has
emerged
as
a
pivotal
high-tech
instrument.However,
effective
interpretation
images,
especially
in
context
heterogeneous
data
processing,
noise,
identification
fine
granularity,
remains
challenge.In
this
study,
novel
method
for
elements
within
imagery
was
introduced.Firstly,
feature
tensor
migration
technique
anchored
on
Coupled
Heterogeneous
Tucker
Decomposition
(CH-Tucker
decomposition)
presented.Through
technique,
multi-source
were
effectively
processed
fused.Notably,
associated
features
from
varying
resolutions
angles
seamlessly
coupled.Subsequently,
an
optical
image
processing
model
founded
RFDNet
network
established.This
demonstrated
robustness
against
noise
data,
thereby
enabling
with
higher
degree
granularity.The
proposed
methodology
exhibited
capacity
to
extract
element
information
comprehensively
remarkable
accuracy.Thus,
research
offers
both
valuable
theoretical
insights
practical
evidence
furtherance
exploration.
E3S Web of Conferences,
Journal Year:
2024,
Volume and Issue:
594, P. 06002 - 06002
Published: Jan. 1, 2024
Population
growth
is
a
significant
problem
in
the
amount
of
land
change
that
occurs.
The
Code
River
watershed
Yogyakarta
has
experienced
urbanization
due
to
lack
for
housing,
even
though
vital
role
community
activities
as
center
government,
economy,
tourism
and
history.
In
determining
width
border,
it
adapts
morphological
demographic
conditions.
Satellite
data
processing
utilizes
deep
learning
using
Object
Based
Image
Analysis
(OBIA)
method.
results
obtained
are
boundaries
varying
from
3
m
10
m.
object
evaluation
carried
out,
completeness
rate
83.5%
quality
69.1%.
number
buildings
detected
boundary
area
1178.
midstream
an
with
dense
building
conditions
compared
downstream
upstream.
use
dominated
by
residential
MSME
although
there
other
such
hospitals,
buildings,
farms,
schools,
factories.
Since
2017
Cartagena
UNESCO
World
Heritage
has
threatened
to
be
categorized
as
"in
Danger"
by
UNESCO.
This
research
analyzes
two
main
critical
aspects,
Governance
and
Current
state
of
the
Site.
Regarding
Governance,
study
aims
identify
strengths,
weaknesses,
opportunities
treats
in
Exemplary
heritage
management
systems
are
studied
propose
an
adaptable
approach
specifically
for
Cartagena.
On
other
hand,
a
comprehensive
analysis
is
conducted
utilizing
photographic
report
that
highlights
major
issues
arising
from
inadequate
management.
Hyperspectral
images
obtained
previous
employed
vegetation
asbestos-cement
roofs
within
cultural
The
reveals
ambiguity
surrounding
decision-making
authority
management,
distributed
between
Mayor's
Office
Ministry
Culture,
primary
challenge.
fragmentation
resulted
duplicated
efforts
lack
coordinated
action,
significantly
compromising
conservation
protection
Moreover,
twelve
current
shortcomings
identified
through
authors'
five-year
on-site
regular
visits,
reports
observation.
To
address
prevailing
concerns,
new
line
command
proposed
most
effective
means
tackling
these
challenges.
Additionally,
general
recommendations
presented
mitigate
existing
problems
prevent
classification
Cartagena's
"at
risk"
near
future.
provides
scientific
perspective,
drawing
upon
years
experience
studying
residing
city,
devoid
political
influences
or
conflicts
interest.
Traitement du signal,
Journal Year:
2023,
Volume and Issue:
40(4), P. 1501 - 1509
Published: Aug. 31, 2023
In
the
realm
of
geological
and
mineral
exploration,
remote
sensing
technology
has
emerged
as
a
pivotal
high-tech
instrument.However,
effective
interpretation
images,
especially
in
context
heterogeneous
data
processing,
noise,
identification
fine
granularity,
remains
challenge.In
this
study,
novel
method
for
elements
within
imagery
was
introduced.Firstly,
feature
tensor
migration
technique
anchored
on
Coupled
Heterogeneous
Tucker
Decomposition
(CH-Tucker
decomposition)
presented.Through
technique,
multi-source
were
effectively
processed
fused.Notably,
associated
features
from
varying
resolutions
angles
seamlessly
coupled.Subsequently,
an
optical
image
processing
model
founded
RFDNet
network
established.This
demonstrated
robustness
against
noise
data,
thereby
enabling
with
higher
degree
granularity.The
proposed
methodology
exhibited
capacity
to
extract
element
information
comprehensively
remarkable
accuracy.Thus,
research
offers
both
valuable
theoretical
insights
practical
evidence
furtherance
exploration.