Hydrology,
Journal Year:
2021,
Volume and Issue:
8(3), P. 131 - 131
Published: Sept. 1, 2021
Precision
agriculture
has
been
at
the
cutting
edge
of
research
during
recent
decade,
aiming
to
reduce
water
consumption
and
ensure
sustainability
in
agriculture.
The
proposed
methodology
was
based
on
crop
stress
index
(CWSI)
applied
Greece
within
ongoing
project
GreenWaterDrone.
innovative
approach
combines
real
spatial
data,
such
as
infrared
canopy
temperature,
air
relative
humidity,
thermal
image
taken
above
field
using
an
aerial
micrometeorological
station
(AMMS)
a
(IR)
camera
installed
unmanned
vehicle
(UAV).
Following
initial
calibration
phase,
where
ground
(GMMS)
crop,
no
equipment
needed
be
maintained
field.
Aerial
measurements
were
transferred
time
sophisticated
databases
applications
over
existing
mobile
networks
for
further
processing
estimation
actual
requirements
specific
level,
dynamically
alerting/informing
local
farmers/agronomists
irrigation
necessity
additionally
potential
risks
concerning
their
fields.
supported
services
address
farmers’,
agricultural
scientists’,
stakeholders’
needs
conform
regional
management
sustainable
policies.
As
preliminary
results
this
study,
we
present
indicative
original
illustrations
data
from
applying
assess
UAV
functionality
while
evaluate
standardize
all
system
processes.
Agricultural Water Management,
Journal Year:
2023,
Volume and Issue:
283, P. 108317 - 108317
Published: April 18, 2023
Recent
advances
in
remote
sensing
and
machine
learning
show
potential
for
improving
irrigation
use
efficiency.
In
this
study,
two
independent
methods
to
determine
the
dose
processing
tomatoes
were
calibrated,
validated,
tested
an
experiment.
The
first
method
used
multispectral
imagery
acquired
from
unoccupied
aerial
vehicle
(UAV)
estimate
FAO-56
crop
coefficient,
Kc.
second
artificial
neural
network
(ANN)
trained
on
eddy
covariance
measurements
of
latent
heat
flux
meteorological
variables
a
nearby
station.
An
experiment
was
conducted,
where
farmer
instructed
through
mobile
application
with
updated
recommendations.
Evapotranspiration
estimated
by
new
set
as
UAV
ANN
treatments.
best-practice
irrigation,
commonly
regional
farmers,
control
treatment
(100%),
guided
expert
soil
sensors
feedback.
Derivatives
at
50%,
75%,
125%
tested.
Yield,
water
efficiency
(WUE),
Brix
level
measured
analyzed.
Results
that
both
methods,
ANN,
evapotranspiration
derive
near-perfect
agreement
total
amount
rate.
Furthermore,
there
no
significant
differences
between
best
practice
experimental
treatments
yield
(117
ton/ha),
water-use
(31.7
kg/m3),
(4.5°Bx).
These
results
demonstrate
advanced
techniques
quantify
requirements
support
management.
Journal of Integrative Agriculture,
Journal Year:
2023,
Volume and Issue:
23(5), P. 1523 - 1540
Published: May 24, 2023
In
order
to
further
improve
the
ability
of
unmanned
aerial
vehicle
(UAV)
remote-sensing
for
quickly
and
accurately
monitoring
growth
winter
wheat
under
film
mulching,
this
research
used
treatments
ridge
ridge–furrow
full
flat
cropping
mulching
wheat.
Based
on
fuzzy
comprehensive
evaluation
(FCE)
method,
four
agronomic
parameters
(leaf
area
index,
aboveground
biomass,
plant
height,
leaf
chlorophyll
content)
were
calculate
index
(CGEI)
wheat,
14
visible
near-infrared
spectral
indices
calculated
using
purification
technology
process
image
data
obtained
by
multispectral
UAV.
Four
machine
learning
algorithms,
partial
least
squares,
support
vector
machines,
random
forests,
artificial
neural
network
networks
(ANN),
build
model
with
accuracy
mapping
spatial
temporal
distribution
status.
The
results
showed
that
CGEI
constructed
based
FCE
method
could
objectively
comprehensively
evaluate
crop
status,
inversion
ANN
was
higher
than
single
parameters,
coefficient
determination
0.75,
root
mean
square
error
8.40,
absolute
value
6.53.
Spectral
eliminate
interference
background
effects
caused
soil,
effectively
improving
best
effect
achieved
after
purification.
provided
a
theoretical
reference
UAV
monitor
status
mulching.
Hydrology,
Journal Year:
2021,
Volume and Issue:
8(3), P. 131 - 131
Published: Sept. 1, 2021
Precision
agriculture
has
been
at
the
cutting
edge
of
research
during
recent
decade,
aiming
to
reduce
water
consumption
and
ensure
sustainability
in
agriculture.
The
proposed
methodology
was
based
on
crop
stress
index
(CWSI)
applied
Greece
within
ongoing
project
GreenWaterDrone.
innovative
approach
combines
real
spatial
data,
such
as
infrared
canopy
temperature,
air
relative
humidity,
thermal
image
taken
above
field
using
an
aerial
micrometeorological
station
(AMMS)
a
(IR)
camera
installed
unmanned
vehicle
(UAV).
Following
initial
calibration
phase,
where
ground
(GMMS)
crop,
no
equipment
needed
be
maintained
field.
Aerial
measurements
were
transferred
time
sophisticated
databases
applications
over
existing
mobile
networks
for
further
processing
estimation
actual
requirements
specific
level,
dynamically
alerting/informing
local
farmers/agronomists
irrigation
necessity
additionally
potential
risks
concerning
their
fields.
supported
services
address
farmers’,
agricultural
scientists’,
stakeholders’
needs
conform
regional
management
sustainable
policies.
As
preliminary
results
this
study,
we
present
indicative
original
illustrations
data
from
applying
assess
UAV
functionality
while
evaluate
standardize
all
system
processes.
