Remote Sensing,
Journal Year:
2024,
Volume and Issue:
16(24), P. 4794 - 4794
Published: Dec. 23, 2024
Approximately
1
million
tons
of
green
tides
decompose
naturally
in
the
Yellow
Sea
China
every
year,
releasing
large
quantities
nutrients
that
disrupt
marine
ecological
balance
and
cause
significant
environmental
consequences.
Currently,
identification
areas
affected
by
primarily
relies
on
certain
methods,
such
as
ground
sampling
biochemical
analysis,
which
limit
ability
to
quickly
dynamically
identify
decomposition
regions
at
spatial
temporal
scales.
While
multi-source
remote
sensing
data
can
monitor
extent
tides,
accurately
identifying
algal
remains
a
challenge.
Therefore,
satellite
were
integrated
with
key
parameters,
carbon-to-nitrogen
ratio
(C/N),
develop
method
for
tide
(DRIM).
The
DRIM
shows
high
accuracy
areas,
validated
through
regional
repetition
rates
UAV
measurements.
Results
indicate
annual
C/N
threshold
is
1.2.
identified
primary
from
2015
2020,
concentrated
mainly
southeastern
region
Shandong
Peninsula,
covering
an
area
approximately
1909.4
km2.
In
2015,
2016,
2017,
largest,
average
duration
35
days.
Our
provides
more
detailed
classification
dissipation
phase,
offering
reliable
scientific
support
accurate
monitoring
management
disasters.
Frontiers in Marine Science,
Journal Year:
2025,
Volume and Issue:
12
Published: Jan. 28, 2025
In
recent
years,
Ulva
prolifera
green
tide,
as
a
large-scale
marine
ecological
phenomenon,
has
occurred
frequently
in
coastal
areas
such
the
Yellow
Sea
and
East
China
Sea,
significantly
affecting
ecosystems
fishery
resources.
With
continuous
advancement
of
remote
sensing
technologies,
these
technologies
have
become
indispensable
tools
for
monitoring
tides.
This
review
provides
comprehensive
overview
advances
band
indices
detecting
tides,
including
spatiotemporal
distribution
analysis,
area
biomass
estimation,
drift
trajectory
modeling,
investigations
their
driving
mechanisms.
Additionally,
it
identifies
limitations
unresolved
challenges
current
approaches,
constraints
on
data
resolution,
algorithmic
biases,
environmental
variability.
The
potential
integrating
multi-source
with
parameters
deep
learning
techniques
is
discussed,
emphasizing
roles
improving
accuracy
reliability
predicting
aims
to
guide
future
research
efforts
technological
innovations
this
field.
Ecosphere,
Journal Year:
2024,
Volume and Issue:
15(4)
Published: April 1, 2024
Abstract
Estuaries
are
productive
ecosystems
that
vulnerable
to
human
impacts
and
environmental
disturbances.
often
inhabited
by
foundation
species
facilitate
other
organisms
creating
modifying
habitats.
However,
spatiotemporal
variability
underpinning
drivers
of
facilitation
from
estuarine
poorly
studied,
especially
in
the
context
monitoring
conservation.
Here,
we
combined
analyses
satellite,
drone,
camera
images,
close‐up
field
sampling
quadrats
individuals,
laboratory
microscopy,
quantify
co‐occurrences
between
cockle
Austrovenus
stutchburyi
green
macroalga
Ulva
spp.,
their
associated
invertebrate
communities,
across
spatial
resolutions
gradients
a
New
Zealand
estuary.
We
found
higher
abundance
winter
at
site
near
ocean.
Furthermore,
was,
space
time,
attached
,
either
live
or
dead
shells,
suggesting
hierarchy
primary
(cockle)
secondary
(macroalgae)
species.
Finally,
provided
better
habitat
for
mobile
invertebrates
than
thereby
increased
diversity
through
density‐dependent
cascade,
which
also
was
consistent
time.
Overall,
our
study
showed
cascades
can
be
indirectly
inferred
monitored
remote
sensing
using
supplementary
imaging
methods,
integration
data
scales
allows
researchers
understand
consequences
These
insights
may
aid
development
efficient
strategies
ultimately
improve
management
ecosystems.
Frontiers in Marine Science,
Journal Year:
2025,
Volume and Issue:
12
Published: March 28, 2025
The
ecological
impacts
of
expanding
nearshore
aquaculture
demand
accurate
monitoring
and
a
mechanistic
understanding
underlying
drivers.
This
study
employed
Landsat
remote
sensing
images
spanning
2000
to
2023
U-Net
deep
learning
model
extract
spatiotemporal
patterns
laver
in
Haizhou
Bay,
China,
while
also
investigating
the
natural,
technological,
socioeconomic
factors
influencing
its
growth.
Key
findings
include:
achieved
an
overall
accuracy
approximately
98.9%
F
1
score
around
0.887,
significantly
outperforming
traditional
classification
methods
(MLE,
SVM,
NN)
by
effectively
reducing
spectral
confusion.
area
followed
“growth-peak-decline”
pattern,
peaking
2018
at
10,872.45
hm²,
with
strong
correlation
local
government
data.
Among
natural
factors,
only
2-meter
temperature
showed
significant
positive
expansion,
other
like
sea
surface
wind
speed
had
minimal
impact,
suggesting
that
region’s
environmental
stability
supports
large-scale
production.
Technological
advancements,
such
as
deep-sea
farming
shellfish-algae
intercropping,
contributed
industry
growth,
policy
changes
after
2019
resulted
reduction
area.
Economic
interactions
played
central
role
spatial
restructuring,
GDP
positively
correlating
expansion
during
growth
phase
(2000-2018),
but
negatively
decoupling
adjustment
(2019-2023).
research
provides
comprehensive
framework
for
sustainable
management
coastal
integrating
data
analysis
multiple
driving
forces.
Remote Sensing,
Journal Year:
2024,
Volume and Issue:
16(16), P. 2934 - 2934
Published: Aug. 10, 2024
The
recurring
occurrence
of
green
tides
as
an
ecological
disaster
has
been
reported
annually
in
the
Yellow
Sea.
While
remote
sensing
technology
effectively
tracks
scale,
extent,
and
duration
tide
outbreaks,
there
is
limited
research
on
underlying
driving
mechanisms
drift
transport
determination
leeway
coefficient.
This
study
investigates
mechanism
evaluates
feasibility
estimating
coefficient
by
analyzing
velocities
obtained
from
Geostationary
Ocean
Color
Imager-II
(GOCI-II)
images
using
maximum
cross-correlation
(MCC)
technique
method
across
various
time
intervals
alongside
ocean
current
wind
speed
data.
results
reveal
following:
(1)
Significant
spatial
variations
movement,
with
a
distinct
boundary
at
34°40′N.
(2)
Short-term
primarily
influenced
tidal
forces,
while
currents,
especially
combined
Ekman
geostrophic
component,
predominantly
govern
net
transport.
(3)
Compared
to
1,
3,
7
h
intervals,
25
interval
feasible
for
moderate-resolution
geostationary
images,
yielding
values
consistent
previous
studies.
offers
new
insights
into
exploring
through
sensing-driven
velocity.
Frontiers in Marine Science,
Journal Year:
2024,
Volume and Issue:
11
Published: July 19, 2024
In
recent
years,
the
periodic
outbreak
of
green
tides
in
coastal
areas
China,
caused
by
combined
effects
environmental
changes
and
human
activities,
has
been
attracting
extensive
attention
due
to
serious
negative
impacts
on
marine
ecosystem.
study,
samples
Ulva
linza
,
a
tide
species,
were
cultivated
under
two
light
intensities
(LL:
80
μmol
photons
m
-2
s
-1
;
HL:
300
)
three
stocking
densities
(LD:
0.2
g
L
MD:1
HD:2
explore
photosynthetic
physiological
responses
nutrients
absorption
capacity.
The
results
showed
that
high
low
density
significantly
increased
growth
rate
U.
linza.
Under
HLLD,
maximum
was
43.13%
day
energy
captured
per
unit
reaction
center
for
electron
transfer
(ET
0
/RC)
highest.
higher
decreased
relative
(rETR
max
especially
among
groups
subjected
high-light
condition.
HL
condition,
HD
also
utilization
efficiency
(α)
.
contents
chlorophyll
b
carotenoids
lower
HLLD
group
compared
other
treatment
groups.
P
uptake
prominently
inhibited
density,
minimum
17.94
μM
FW
LLLD
2.74
LLHD
group,
respectively.
Lower
improved
N
but
had
no
effect
it.
These
suggest
synergistically
promote
which
is
likely
enhanced
nutrient
uptake.
And
inhibitory
growth,
particularly
conditions,
may
be
competition
nutrients.
late
stage
outbreak,
an
increase
accumulation
could
help
suppress
sustained
tides,
Adaptation
to
climate
change
is
crucial
for
marine
life
as
these
changes
have
profound
effects
on
organisms.
We
investigated
genetical
mechanism
underlying
the
tolerance
of
Ulva
prolifera
(Chlorophyta),
a
macroalgae,
combine
high
temperature
and
light
intensity
stress.
In
total,
81,729
differentially
expressed
genes
(DEGs)
were
identified
between
control
treatment
groups.
At
mRNA
level,
upregulated
DEGs
enriched
in
spliceosome,
ribosome,
proteasome,
peroxisome
pathways.
Genes
linked
spliceosome
pathway
played
role
ability
U.
adapt
challenging
situations
across
all
comparison
Additionally,
pathways
associated
with
ribosomes,
proteasomes,
peroxisomes
significantly
increased
response
elevated
Autophagy
was
only
stress
after
24
hours,
not
48
hours.
These
results
provide
new
insights
into
molecular
responses
conditions.