Environmental Research Letters,
Journal Year:
2024,
Volume and Issue:
19(4), P. 044023 - 044023
Published: March 15, 2024
Abstract
Shoreline
predictions
are
essential
for
coastal
management.
In
this
era
of
increasing
amounts
data
from
different
sources,
it
is
imperative
to
use
observations
ensure
the
reliability
shoreline
forecasts.
Data
assimilation
has
emerged
as
a
powerful
tool
bridge
gap
between
episodic
and
imprecise
spatiotemporal
incomplete
mathematical
equations
describing
physics
dynamics.
This
research
seeks
maximize
potential
by
assessing
effectiveness
algorithms
considering
observational
characteristics
initial
system
knowledge
guide
models
towards
delivering
results
close
possible
real
world.
Two
statistical
(stochastic
ensemble
extended
Kalman
filters)
one
variational
algorithm
(4D-Var)
incorporated
into
an
equilibrium
cross-shore
model
one-line
longshore
model.
A
twin
experimental
procedure
conducted
determine
observation
requirements
these
in
terms
accuracy,
length
collection
campaign
sampling
frequency.
Similarly,
needed
ability
methods
track
nonstationarity
evaluated
under
synthetic
scenarios.
The
indicate
that
with
noisy
observations,
filter
variants
outperform
4D-Var.
However,
4D-Var
less
restrictive
tracks
nonstationary
parametrizations
more
accurately
processes.
findings
demonstrated
at
two
beaches
governed
processes
sources
used
calibration.
contribution,
assimilated
thus
far
modelling
extended,
applied
first
time
field
modelling,
guidelines
on
which
method
can
be
most
beneficial
available
provided.
Journal of Geophysical Research Earth Surface,
Journal Year:
2025,
Volume and Issue:
130(2)
Published: Jan. 30, 2025
Abstract
We
report
on
remote
sensing
techniques
developed
to
characterize
seasonal
shoreline
cycles
from
satellite‐derived
measurements.
These
are
applied
22‐yr
of
measurements
for
over
777
km
beach
along
California's
1,700‐km
coast,
which
the
general
understanding
is
that
shorelines
exhibit
winter‐narrow
and
summer‐recovery
seasonality.
find
approximately
90%
transects
significant
recurring
in
position.
Seasonal
excursions
twice
as
large
northern
central
California
(17.5–32.2
m)
than
southern
(7.3–15.9
m;
interquartile
ranges).
Clustering
analyses
were
effective
at
characterizing
temporal
patterns
seasonality,
revealing
∼459
(59%)
conditions,
whereas
∼189
(24%)
∼50
(6.4%)
spring‐narrow
summer‐narrow
respectively.
spring‐
conditions
most
common
California,
where
they
represent
half
total
length
shoreline.
Multivariate
reveal
wave
climate
geomorphic
setting
significantly
related
magnitude
timing
cycles.
Combinations
these
variables
explain
44%
seasonality
variance
complete
data
set
85%
a
subset
93
long
(>1
km)
continuous
beaches.
conclude
diversity
waves
cause
broad
range
Combined,
this
indicates
overly
generalized
“winter‐narrow/summer‐recovery”
conventions
beaches
not
expressed
universally
far
more
diverse
simple
canonical
rules.
Abstract
Coastal
morphological
changes
can
be
assessed
using
shoreline
position
observations
from
space.
However,
satellite-derived
waterline
(SDW)
and
(SDS;
SDW
corrected
for
hydrodynamic
contributions
outliers)
detection
methods
are
subject
to
several
sources
of
uncertainty
inaccuracy.
We
extracted
high-spatiotemporal-resolution
(~50
m-monthly)
time
series
mean
high
water
along
the
Columbia
River
Littoral
Cell
(CRLC),
located
on
US
Pacific
Northwest
coast,
Landsat
missions
(1984–2021).
examined
accuracy
SDS
mesotidal,
mildly
sloping,
high-energy
wave
climate
dissipative
beaches
CRLC
by
validating
them
against
20
years
quarterly
in
situ
beach
elevation
profiles.
found
that
heavily
depends
capability
identify
remove
outliers
correct
biases
stemming
tides
runup.
we
show
only
correcting
data
is
sufficient
accurately
measure
change
trends
CRLC.
Ultimately,
strong
agreement
with
data,
facilitating
spatiotemporal
analysis
coastal
highlighting
an
overall
accretion
signal
during
past
four
decades.
Scientific Reports,
Journal Year:
2025,
Volume and Issue:
15(1)
Published: March 28, 2025
Coastal
erosion,
intensified
by
sea
level
rise,
poses
significant
threats
to
coastal
communities
in
Hawaiʻi
and
similar
island
communities.
This
study
projects
long-term
shoreline
change
on
the
Hawaiian
Island
of
O'ahu
using
data-assimilated
CoSMoS-COAST
model.
models
four
key
processes:
(1)
Alongshore
transport,
(2)
Recession
due
(3)
Cross-shore
transport
waves,
(4)
Residual
processes
represented
a
linear
trend
term.
marks
first
application
for
an
oceanic
equatorial
with
narrow
beaches
dynamic
wave
climate.
The
model
is
informed
novel
combination
data
derived
from
high-resolution
imagery
Planet,
Sentinel-2,
Landsat
satellites,
wave-climate
hindcasts
specific
Hawai'i,
regional
beach-slope
surveys.
On
northern
Oʻahu
beach,
achieved
root
mean
square
error
9.4
m
between
observations
output.
predicts
that
81%
O'ahu's
sandy
beach
coastline
could
experience
loss
2100;
39.8%
this
happening
2030.
represents
increase,
43.3%,
net
landward
compared
previous
erosion
forecasts,
0.3
rise
(2050).
Additionally,
such
as
cross-shore
equilibrium
alongshore
sediment
play
large
contribution
gross
within
next
decade,
particularly
O
'ahu's
north
west
shores.
In
long
term,
we
find
recession
residual
dominate,
but
dynamic,
wave-driven
(longshore
transport)
still
account
34%
present
2100.
We
assert
are
crucial
addition
accurate
modeling
environments.
These
findings
have
implications
planning
development,
suggesting
updates
policies
rely
upon
forecasting,
highlights
importance
incorporating
other
Pacific
islands.
Coastal Engineering,
Journal Year:
2023,
Volume and Issue:
188, P. 104426 - 104426
Published: Nov. 13, 2023
The
definition
of
the
shoreline
position
from
satellite
imagery
is
great
interest
among
coastal
monitoring
techniques.
Understanding
reality
mapped
by
resulting
shorelines
and
defining
their
accuracy
paramount
importance.
assessment
described
in
this
paper
constitutes
a
validation
obtained
using
novel
tool
SAET
(Shoreline
Analysis
Extraction
Tool)
for
automatic
extraction.
applying
different
parameters
available
are
assessed
9
test
sites
with
diverse
morphology
oceanographic
conditions
along
Atlantic
European
Western
Mediterranean
coasts.
reference
data
large
segments
(covering
up
to
about
240
km)
nearly
coincident
very
high-resolution
images.
Different
image
processing
levels
extraction
methods
have
been
tested,
showing
key
role
position.
When
approximate
Automated
Water
Index
images
without
shadows
(AWEInsh)
0
threshold
generally
best
segmentation
method.
In
turn,
employment
mathematical
morphological
operations
dilation
or
erosion
considerably
improves
results
certain
typologies.
On
contrary,
atmospherically-corrected
has
smaller
influence
on
SDSs.
Results
support
idea
that
magnitude
errors
strongly
related
specific
conditions-
general,
lowest
appear
low-energetic
microtidal
sites,
contrary
energetic
mesotidal
coasts
gentle
slopes.
range
between
3.7
m
13.5
RMSE
(root-mean-square
error)
types
when
selecting
most
appropriate
parameters.
identified
shows
similar
better
other
tools.
Journal of Marine Science and Engineering,
Journal Year:
2024,
Volume and Issue:
12(1), P. 139 - 139
Published: Jan. 10, 2024
The
coastal
environment
is
vulnerable
to
natural
hazards
and
human-induced
stressors.
assessment
management
of
risks
have
become
a
challenging
task,
due
many
environmental
socio-economic
risk
factors
together
with
the
complex
interactions
that
might
arise
through
pressures.
This
work
evaluates
combined
effect
climate-related
stressors
on
low-lying
areas
by
applying
multi-risk
scenario
analysis
Bayesian
Network
(BN)
approach
for
Venice
coast.
Based
available
open-source
remote
sensing
data
detecting
shoreline
changes,
developed
BN
model
was
trained
validated
oceanographic
variables
2015–2019
timeframe,
allowing
us
understand
dynamics
local-scale
erosion
related
water
quality
parameters.
Three
“what-if”
scenarios
were
carried
out
analyze
relationships
between
boundary
conditions,
evolution,
results
demonstrate
changes
in
sea
surface
height
significant
wave
may
significantly
increase
probability
high-erosion
high-accretion
states.
Moreover,
altering
direction,
show
higher-risk
class.
outcome
this
study
allowed
identify
current
future
scenarios,
supporting
local
authorities
developing
adaptation
plans.
Earth Surface Processes and Landforms,
Journal Year:
2024,
Volume and Issue:
49(8), P. 2405 - 2423
Published: May 14, 2024
Abstract
Public
satellite
platforms
offer
regular
observations
for
global
coastal
monitoring
and
climate
change
risk
management
strategies.
Unfortunately,
shoreline
positions
derived
from
imagery,
representing
changes
in
intertidal
topography,
are
noisy
subject
to
tidal
bias
that
requires
correction.
The
seaward‐most
vegetation
boundary
reflects
a
indicator
which
shifts
on
event–decadal
timescales,
informs
practitioners
of
storm
damage,
sediment
availability
landform
health.
We
present
validate
new
open‐source
tool
VedgeSat
identifying
edges
(VEs)
high
(3
m)
moderate
(10–30
resolution
imagery.
methodology
is
based
the
CoastSat
toolkit,
with
streamlined
image
processing
using
cloud‐based
data
via
Google
Earth
Engine.
Images
classified
newly
trained
vegetation‐specific
neural
network,
VEs
extracted
at
subpixel
level
dynamic
Weighted
Peaks
thresholding.
performed
validation
against
ground
surveys
manual
digitisation
aerial
imagery
across
eroding
accreting
open
coasts
estuarine
environments
site
Scotland.
Smaller‐than‐pixel
detection
was
achieved
83%
Sentinel‐2
(Root
Mean
Square
Error
9.3
m).
An
overall
RMSE
19.0
m
Landsat
5
&
8,
PlanetScope
images.
Performance
varied
by
geomorphology,
highest
accuracies
sandy
owing
spectral
contrast
less
false
positives
vegetation.
can
be
readily
applied
tandem
waterlines
near‐globally,
support
adaptation
decisions
historic
trends
whole
shoreface,
even
normally
data‐scarce
areas.
The Journal of Open Source Software,
Journal Year:
2024,
Volume and Issue:
9(99), P. 6683 - 6683
Published: July 1, 2024
Fitzpatrick
et
al.,
(2024).
CoastSeg:
an
accessible
and
extendable
hub
for
satellite-derived-shoreline
(SDS)
detection
mapping.
Journal
of
Open
Source
Software,
9(99),
6683,
https://doi.org/10.21105/joss.06683
Proceedings of the National Academy of Sciences,
Journal Year:
2024,
Volume and Issue:
121(32)
Published: July 29, 2024
Climate
change
is
an
existential
threat
to
the
environmental
and
socioeconomic
sustainability
of
coastal
zone
impacts
will
be
complex
widespread.
Evidence
from
California
across
United
States
shows
that
climate
impacting
communities
challenging
managers
with
a
plethora
stressors
already
present.
Widespread
action
could
taken
would
sustain
California's
ecosystems
communities.
In
this
perspective,
we
highlight
main
sustainability:
compound
effects
episodic
events
amplified
ongoing
change,
which
present
unprecedented
challenges
state.
We
two
key
for
in
zone:
1)
accelerating
sea-level
rise
combined
storm
impacts,
2)
continued
warming
oceans
marine
heatwaves.
Cascading
these
types
compounding
occur
within
context
stressed
system
has
experienced
extensive
alterations
due
intensive
development,
resource
extraction
harvesting,
spatial
containment,
other
human
use
pressures.
There
are
critical
components
used
address
immediate
concerns,
including
comanagement
strategies
include
diverse
groups
organizations,
strategic
planning
integrated
large
areas,
rapid
implementation
solutions,
cohesive
policy
relevant
research
agenda
coast.
Much
been
started
state,
but
scale
increased,
timelines
accelerated.
The
ideas
information
presented
here
intended
help
expand
discussions
sharpen
focus
on
how
encourage
iconic
region.
Earth s Future,
Journal Year:
2024,
Volume and Issue:
12(12)
Published: Dec. 1, 2024
Abstract
This
study
assesses
the
vulnerability
of
Arctic
coastal
settlements
and
infrastructure
to
erosion,
Sea‐Level
Rise
(SLR)
permafrost
warming.
For
first
time,
we
characterize
coastline
retreat
consistently
along
at
regional
scale
for
Northern
Hemisphere.
We
provide
a
new
method
automatically
derive
long‐term
change
rates
coasts.
In
addition,
identify
total
number
associated
that
could
be
threatened
by
marine
terrestrial
changes
using
remote
sensing
techniques.
extended
Coastal
Infrastructure
data
set
(SACHI)
include
road
types,
airstrips,
artificial
water
reservoirs.
The
analysis
coastline,
Ground
Temperature
(GT)
Active
Layer
Thickness
(ALT)
from
2000
2020,
in
addition
with
SLR
projection,
allowed
exposed
2030,
2050,
2100.
validated
SACHI‐v2,
GT
ALT
sets
through
comparisons
in‐situ
data.
60%
detected
is
built
on
low‐lying
coast
(10
m
a.s.l).
results
show
2100,
45%
all
will
affected
21%
erosion.
On
average,
increasing
0.8°C
per
decade,
6
cm
decade.
become
positive
77%
area.
Our
highlight
circumpolar
international
amplitude
problem
emphasize
need
immediate
adaptation
measures
current
future
environmental
counteract
deterioration
living
conditions
ensure
sustainability.
Coastal Engineering,
Journal Year:
2024,
Volume and Issue:
189, P. 104473 - 104473
Published: Jan. 24, 2024
Beach
loss
is
a
growing
global
challenge
that
threatens
the
safety
of
coastal
communities,
health
ecosystems,
recreational
amenities,
and
regional
economies
dependent
on
tourism.
Spatial
gradients
in
longshore
sediment
transport,
or
divergence
drift
(DoD),
primary
driver
beach
width
change
over
multi-annual
time
scales,
but
response
any
particular
can
be
challenging
to
characterize
predict.
Here
we
present
new
method
DoD
using
non-uniform
segmentation
coastline
informed
by
spatial
distribution
transport
potential,
including
location
physical
barriers
identified
orthoimagery,
both
maxima
reversals
potential
derived
from
nearshore
wave
data.
The
demonstrates
improved
capacity
predict
trends
at
sandy
beaches
compared
methods
rely
uniform
coastline.
In
an
application
southern
California
where
satellite
data
documents
two
decades
trends,
correctly
predicts
sign
93%
transects
within
littoral
cell
achieves
linear
correlation
between
exceeding
0.8.
Moreover,
find
minimum
five
years
are
required
establish
consistently
strong
correlations
changes.
Conversely,
use
shown
unreliable
for
estimating
due
sensitivities
shoreline
segment
size.
This
work
shows
leverage
satellite-based
characterization
dynamics
relevant
erosion
management.