European Journal of Remote Sensing,
Journal Year:
2024,
Volume and Issue:
57(1)
Published: Nov. 27, 2024
Data
from
the
new
hyperspectral
satellite
missions
such
as
EnMAP
are
anticipated
to
refine
leaf
area
index
(LAI)
or
canopy
closure
(CC)
monitoring
in
conifer-dominated
forest
areas.
We
compared
contemporaneous
multispectral
and
images
Sentinel-2
MSI
(S2)
assessed
whether
offer
added
value
estimating
LAI,
effective
LAI
(LAIeff),
CC
a
European
boreal
area.
The
estimations
were
performed
using
univariate
multivariate
generalized
additive
models.
models
utilized
field
measurements
of
38
plots
an
extensive
set
vegetation
indices
(VIs)
derived
data.
best
for
each
three
response
variables
had
small
differences
between
two
sensors,
but
general,
more
well-performing
VIs
which
was
reflected
better
model
performances.
performing
with
data
~1–6%
lower
relative
RMSEs
than
S2.
Wavelengths
near
green,
red-edge,
shortwave
infrared
regions
frequently
LAIeff,
Because
could
estimate
better,
results
suggest
that
may
be
useful
S2,
biophysical
coniferous-dominated
forests.
Science of Remote Sensing,
Journal Year:
2024,
Volume and Issue:
10, P. 100148 - 100148
Published: July 23, 2024
This
paper
describes
the
selected
algorithm
for
ESA
climate
change
initiative
vegetation
parameters
project.
Multi-
and
hyper-spectral,
multi-angular,
or
multi-sensor
top-of-canopy
reflectance
data
call
an
efficient
generic
retrieval
system
which
can
improve
consistent
of
standard
canopy
as
albedo,
Leaf
Area
Index
(LAI),
Fraction
Absorbed
Photosynthetically
Active
Radiation
(fAPAR)
their
uncertainties,
exploit
information
to
retrieve
additional
(e.g.
leaf
pigments).
We
present
a
sub-canopy
(OptiSAIL),
is
based
on
model
comprising
SAIL
(canopy
reflectance),
PROSPECT-D
(leaf
properties),
TARTES
(snow
soil
(soil
anisotropy,
moisture
effect),
cloud
contamination
model.
The
inversion
gradient
uses
codes
created
by
Automatic
Differentiation.
full
per
pixel
covariance-matrix
retrieved
computed.
For
this
demonstration,
single
observation
from
Sentinel-3
SY_2_SYN
(synergy)
product
used.
results
are
compared
with
MODIS
4-day
LAI/fAPAR
PhenoCam
site
photography.
OptiSAIL
produces
generally
credible
results,
at
least
matching
quality
technically
quite
different
product.
computationally
rate
150
s−1
(7
ms
pixel)
thread
current
desktop
CPU
using
observations
26
bands.
Not
all
well
determined
in
situations.
Significant
correlations
between
found,
sign
magnitude
over
time.
appears
meet
design
goals
puts
real-time
processing
kind
into
reach.
European Journal of Remote Sensing,
Journal Year:
2024,
Volume and Issue:
57(1)
Published: Nov. 27, 2024
Data
from
the
new
hyperspectral
satellite
missions
such
as
EnMAP
are
anticipated
to
refine
leaf
area
index
(LAI)
or
canopy
closure
(CC)
monitoring
in
conifer-dominated
forest
areas.
We
compared
contemporaneous
multispectral
and
images
Sentinel-2
MSI
(S2)
assessed
whether
offer
added
value
estimating
LAI,
effective
LAI
(LAIeff),
CC
a
European
boreal
area.
The
estimations
were
performed
using
univariate
multivariate
generalized
additive
models.
models
utilized
field
measurements
of
38
plots
an
extensive
set
vegetation
indices
(VIs)
derived
data.
best
for
each
three
response
variables
had
small
differences
between
two
sensors,
but
general,
more
well-performing
VIs
which
was
reflected
better
model
performances.
performing
with
data
~1–6%
lower
relative
RMSEs
than
S2.
Wavelengths
near
green,
red-edge,
shortwave
infrared
regions
frequently
LAIeff,
Because
could
estimate
better,
results
suggest
that
may
be
useful
S2,
biophysical
coniferous-dominated
forests.
