Development of a HAND-based flood risk assessment tool in Google Earth Engine for a data-scarce region in the US
Journal of Great Lakes Research,
Год журнала:
2025,
Номер
unknown, С. 102510 - 102510
Опубликована: Фев. 1, 2025
Язык: Английский
Challenges of earth remote sensing data during geological exploration
International Journal of Environmental Science and Technology,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 10, 2025
Язык: Английский
An Integrated Framework for Actionable Flood Warnings on Road Structures Using High Resolution Satellite Imagery
EarthArXiv (California Digital Library),
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 17, 2024
Floods
rank
among
the
most
devastating
natural
hazards
globally.
Unlike
many
other
calamities,
floods
typically
occur
in
densely
populated
regions,
resulting
immediate
and
long-term
adverse
impacts
on
communities,
including
fatalities,
injuries,
health
risks,
significant
economic
environmental
losses
annually.
Traditional
flood
models,
while
useful,
are
constrained
by
simplifying
assumptions,
numerical
approximations,
a
lack
of
sufficient
data
for
accurate
simulations.
Recent
advancements
data-efficient
Digital
Elevation
Model
(DEM)
Terrain
(DTM)
based
models
show
promise
overcoming
some
these
limitations.
However,
models'
reliance
DEM
or
DTM
renders
them
sensitive
to
dynamic
nature
Earth's
surface.
This
study
investigates
effectiveness
remote
sensing
imagery
inundation
mapping,
focusing
role
high-resolution
commercial
optical
PlanetScope
images
data-limited
scenarios.
To
address
early-stage
reflectance
issues
attributed
on-board
calibration
constellations,
we
introduced
novel
post-processing
workflow,
Quantile-based
Filling
Refining
(QFR).
Our
results
indicate
that
initial
extent
maps
produced
using
widely
adopted
Normalized
Difference
Water
Index
(NDWI)
were
inferior
manual
delineations
comparable
those
generated
only
Near-Infrared
(NIR)
band,
which
also
suffers
from
flaws.
NIR
band
processed
with
QFR
significantly
outperformed
delineations.
research
demonstrates
potential
precise
particularly
at
smaller
scales,
such
as
urban
areas.
Additionally,
it
underscores
workflow's
enhancing
prediction
accuracy,
offering
streamlined
scalable
method
improving
modeling
outcomes.
Язык: Английский
CataEx: a multi-task export tool for the Google Earth Engine data catalog
Environmental Modelling & Software,
Год журнала:
2024,
Номер
unknown, С. 106227 - 106227
Опубликована: Сен. 1, 2024
Язык: Английский
Typical battlefield infrared background detection method based on multi band fusion
Deleted Journal,
Год журнала:
2024,
Номер
6(12)
Опубликована: Дек. 2, 2024
Intelligent
battlefield
environment
recognition
is
crucial
for
active
camouflage
technology.
Enhancing
detection
capabilities
various
environments
essential
target
survival.
Traditional
systems,
relying
on
single
visible
light
or
infrared
bands,
face
challenges
like
low
performance
and
limited
information
use
due
to
lighting
conditions,
making
them
inadequate
all-weather
detection.
This
study
presents
a
multi-modal
feature
fusion
network
model
using
typical
background
database.
It
employs
coordinated
attention
mechanism
spatial
optimizes
dense
dual-path
networks
improve
the
of
optical
images.
The
achieves
97.57%
accuracy,
4.16%
higher
than
best
single-modal
results.
boosts
accuracy
by
2.68%.
Thus,
effectively
integrates
data,
showing
strong
in
classifying
detecting
backgrounds.
Язык: Английский