Forests,
Journal Year:
2024,
Volume and Issue:
15(12), P. 2185 - 2185
Published: Dec. 12, 2024
Airborne
LiDAR
(ALS)
and
terrestrial
(TLS)
data
integration
provides
complementary
perspectives
for
acquiring
detailed
3D
forest
information.
However,
challenges
in
registration
arise
due
to
feature
instability,
low
overlap,
differences
cross-platform
point
cloud
density.
To
address
these
issues,
this
study
proposes
an
automatic
method
based
on
the
consistency
of
single-tree
position
distribution
multi-species
complex
scenes.
In
method,
positions
are
extracted
as
points
using
Stepwise
Multi-Form
Fitting
(SMF)
technique.
A
novel
matching
is
proposed
by
constructing
a
polar
coordinate
system,
which
achieves
fast
horizontal
registration.
Then,
Z-axis
translation
determined
through
Cloth
Simulation
Filtering
(CSF)
grid-based
methods.
Finally,
Iterative
Closest
Point
(ICP)
algorithm
employed
perform
fine
The
experimental
results
demonstrate
that
high
accuracy
across
four
plots
varying
complexity,
with
root-mean-square
errors
0.0423
m,
0.0348
0.0313
0.0531
m.
significantly
improved
compared
existing
methods,
time
efficiency
enhanced
average
90%.
This
offers
robust
accurate
performance
diverse
environments.
Photonics,
Journal Year:
2024,
Volume and Issue:
11(2), P. 153 - 153
Published: Feb. 5, 2024
The
clutter
suppression
effect
of
ground
objects
significantly
impacts
the
detection
and
tracking
performance
avian
lidar
on
low-altitude
bird
flock
targets.
It
is
imperative
to
simulate
point
cloud
data
in
explore
effective
methods
for
suppressing
caused
by
lidar.
traditional
ray-tracing
method
enhanced
this
paper
efficiently
obtain
simulation
results
objects.
By
incorporating
a
beam
constraint
light-energy
constraint,
screening
efficiency
rays
improved,
making
them
more
suitable
simulating
large
scenes
with
narrow
beams.
In
paper,
collision
scheme
proposed
based
constraints,
aiming
enhance
detection.
experimental
demonstrate
that,
comparison
other
conventional
methods,
yields
that
exhibit
greater
conformity
actual
lidar-collected
terms
shape
characteristics
intensity
features.
Additionally,
speed
enhanced.
Geo-spatial Information Science,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 22
Published: Dec. 17, 2024
Accurate
extraction
of
tree
parameters
is
vital
for
the
calculation
high-quality
forest
volume
or
biomass.
The
Light
Detection
and
Ranging
(Lidar)
technology
with
its
ability
to
acquire
three-dimensional
stand
structures
an
important
data
source
extracting
parameters.
However,
complex
due
dense
canopy
abundant
understory
vegetation
can
seriously
affect
performance
This
study
selected
Chinese
fir
plantations
examine
how
different
structure
conditions
affected
parameter
based
on
integration
handheld
laser
scanning
(HLS)
airborne
(ALS)
data.
also
explored
developing
models
using
extracted
height
crown
width,
directly
calculated
variables
from
point
clouds
estimate
diameter
at
breast
(DBH)
stem
volume.
methods
mainly
consisted
two
parts:
(1)
Selecting
appropriate
identify
seed
points
segmentation,
subsequently
parameters;
(2)
Taking
height,
tree-level
cloud
metrics
as
independent
establish
regression
random
estimating
DBHs
volumes.
Results
showed
that
were
accurately
relative
root
mean
square
error
(RMSEr)
7.1%−10.5%
RMSEr
12.3%−16.8%
under
conditions;
As
became
complex,
direct
HLS
a
challenging
task.
DBH
estimation
model
width
proved
feasible;
(3)
In
complex-understory
condition,
utilizing
achieved
good
28.0%.
research
provides
new
insights
ALS
data,
offering
potential
replacement
field
measurements
DBH,
plantations.
Land,
Journal Year:
2024,
Volume and Issue:
13(11), P. 1856 - 1856
Published: Nov. 7, 2024
This
study
evaluated
whether
tree
object
segmentation
using
remote
sensing
techniques
could
be
effectively
conducted
according
to
the
green
structures
of
urban
forests.
The
used
were
handheld
LiDAR
and
UAV-based
photogrammetry.
data
collected
from
both
methods
merged
complement
each
other’s
limitations.
area
classified
into
three
types
based
on
distance
between
canopy
trees
presence
shrubs.
ability
individually
classify
within
was
then
evaluated.
evaluation
method
assess
success
rate
by
comparing
actual
number
trees,
which
visually
counted
in
field,
with
objects
study.
To
perform
semantic
objects,
a
preprocessing
step
extract
only
related
through
techniques.
steps
included
merging,
noise
removal,
separation
DTM
DSM,
areas
structures.
analysis
results
showed
that
recognition
not
efficient
when
complex
mixed,
highest
present,
canopies
did
overlap.
Therefore,
observing
high-density
areas,
algorithm’s
variables
should
adjusted
narrow
range,
additional
observations
winter
are
needed
compensate
for
obscured
leaves.
By
improving
collection
systematizing
structures,
process
can
enhanced.
Forests,
Journal Year:
2024,
Volume and Issue:
15(12), P. 2185 - 2185
Published: Dec. 12, 2024
Airborne
LiDAR
(ALS)
and
terrestrial
(TLS)
data
integration
provides
complementary
perspectives
for
acquiring
detailed
3D
forest
information.
However,
challenges
in
registration
arise
due
to
feature
instability,
low
overlap,
differences
cross-platform
point
cloud
density.
To
address
these
issues,
this
study
proposes
an
automatic
method
based
on
the
consistency
of
single-tree
position
distribution
multi-species
complex
scenes.
In
method,
positions
are
extracted
as
points
using
Stepwise
Multi-Form
Fitting
(SMF)
technique.
A
novel
matching
is
proposed
by
constructing
a
polar
coordinate
system,
which
achieves
fast
horizontal
registration.
Then,
Z-axis
translation
determined
through
Cloth
Simulation
Filtering
(CSF)
grid-based
methods.
Finally,
Iterative
Closest
Point
(ICP)
algorithm
employed
perform
fine
The
experimental
results
demonstrate
that
high
accuracy
across
four
plots
varying
complexity,
with
root-mean-square
errors
0.0423
m,
0.0348
0.0313
0.0531
m.
significantly
improved
compared
existing
methods,
time
efficiency
enhanced
average
90%.
This
offers
robust
accurate
performance
diverse
environments.
