Drones,
Год журнала:
2024,
Номер
8(12), С. 710 - 710
Опубликована: Ноя. 28, 2024
Small
lakes
play
an
essential
role
in
maintaining
regional
ecosystem
stability
and
water
quality.
However,
turbidity
these
is
increasingly
influenced
by
anthropogenic
activities,
which
presents
a
challenge
for
traditional
monitoring
methods.
This
study
explores
the
feasibility
of
using
consumer-grade
UAVs
equipped
with
RGB
cameras
to
monitor
small
within
Taihu
Lake
Basin
eastern
China.
By
collecting
imagery
situ
measurements,
we
developed
validated
models
prediction.
band
indices
were
used
combination
three
machine
learning
models,
namely
Interpretable
Feature
Transformation
Regression
(IFTR),
Random
Forest
(RF),
Extreme
Gradient
Boosting
(XGBoost).
Results
showed
that
utilizing
combinations
R,
G,
B,
ln(R)
bands
achieved
highest
accuracy,
IFTR
model
demonstrating
best
performance
(R²
=
0.816,
RMSE
3.617,
MAE
2.997).
The
confirms
can
be
effective,
low-cost
tool
high-resolution
lakes,
providing
valuable
insights
sustainable
quality
management.
Future
research
should
investigate
advanced
algorithms
additional
spectral
features
further
enhance
prediction
accuracy
adaptability.
Heliyon,
Год журнала:
2025,
Номер
11(4), С. e42622 - e42622
Опубликована: Фев. 1, 2025
Water
quality
of
irrigation
water
is
an
essential
factor
for
public
safety
and
farm
sustainability.
Imaging
surface
sources
from
unmanned
aerial
vehicles
(UAVs)
has
become
important
source
information.
variables
(WQVs)
in
ponds
have
been
shown
to
persistent
spatial
patterns.
The
objective
this
work
was
test
the
hypothesis
that
(a)
patterns
can
be
found
reflectance
remote
sensing
indices
UAV-based
multispectral
imagery
ponds,
(b)
those
significantly
correlate
with
WQVs.
We
utilized
data
sampling,
in-situ
sensing,
imaging
a
commercial
4-ha
pond
Maryland.
Seventeen
were
measured
on
permanent
grid
during
season
concurrently
MicaSense
RedEdge
camera
at
five
wavelengths.
Twenty-four
computed.
Spatial
determined
using
mean
relative
difference
method.
appeared
reflect
differences
distances
banks,
closeness
creek
meeting
pond,
degree
stagnancy,
dominant
wind
directions,
geese
congregation
site.
High
(>0.8)
Spearman
correlation
coefficients
turbidity,
photosynthetic
pigments,
organic
carbon
water.
These
variables'
had
similarities
AFAI,
TCARI,
TCI,
MCARI.
Patterns
E.
coli
strongly
correlated
pattern
red
wavelength.
Given
high
spatiotemporal
variability
WQVs
determining
useful
design
surveys
or
monitoring
aspects
quality.
Journal of Environmental Quality,
Год журнала:
2025,
Номер
unknown
Опубликована: Март 31, 2025
Abstract
Quantification
of
Escherichia
coli
in
water
is
commonly
used
to
understand
a
surface
source's
suitability
for
produce
irrigation.
Location,
season,
and
physicochemical
quality
impact
the
levels
E.
irrigation
ponds.
Water
samples
were
collected
periodically
at
three
ponds
Southeast
Georgia
along
sampling
grid
from
July
2021
through
September
2023
quantified
with
simultaneous
collection
relevant
parameters.
Mean
relative
differences
(MRDs)
calculated
each
point
determine
across
locations.
varied
significantly
area
(perimeter,
surface,
subsurface)
pond.
The
log
most
probable
number
100
mL
−1
(EC
MRD)
values
ranged
−0.25
0.33
Pond
1,
−1.5
0.65
2,
−1.25
3.
In
EC
MRD
correlated
positively
chlorophyll
turbidity,
negatively
dissolved
organic
matter,
oxygen
(DO),
specific
conductance,
pH
MRDs.
MRDs
chlorophyll,
DO,
phycocyanin,
pH,
temperature.
3,
nitrate
MRD.
This
work
showed
analysis
may
reveal
stable
patterns
factors
that
these
ponds,
though
no
universal
covariates
identified
could
estimate
levels.
These
findings
provide
context
managers
wishing
augment
measurements
other
factors,
or
better
represent
variable
