The potential of optical and SAR time-series data for the improvement of aboveground biomass carbon estimation in Southwestern China’s evergreen coniferous forests
GIScience & Remote Sensing,
Journal Year:
2024,
Volume and Issue:
61(1)
Published: April 26, 2024
Accurate
assessments
of
forest
biomass
carbon
are
invaluable
for
managing
resources,
evaluating
effects
on
ecological
protection,
and
achieving
goals
related
to
climate
change
sustainable
development.
Currently,
the
integration
optical
synthetic
aperture
radar
(SAR)
data
has
been
extensively
utilized
in
estimating
aboveground
(AGC),
while
it
is
limited
by
using
single-phase
remote
sensing
images.
Time-series
data,
which
capture
interannual
dynamic
growth
seasonal
variations
photosynthetic
phenology
forests,
can
sufficiently
describe
characteristics.
However,
there
remains
a
gap
research
focusing
utilizing
satellite-based
time-series
AGC
estimation,
especially
SAR
sensors.
This
study
investigated
potential
AGC.
Here,
we
undertook
nine
quantitative
experiments
estimation
from
Landsat
8
Sentinel-1
tested
several
regression
algorithms
(including
multiple
linear
(MLR),
random
forests
(RF),
artificial
neural
network
(ANN),
extreme
gradient
boosting
(XGBoost))
explore
contributions
spatiotemporal
features
estimation.
The
results
suggested
that
XGBoost
algorithm
was
suitable
with
explanatory
solid
power
stable
performance.
temporal
representing
trends
periodic
characteristics
(such
as
coefficients
continuous
wavelet
transform)
were
more
valuable
than
spatial
both
sensor
types,
accounting
around
40%
~50%
variance
compared
17%
~25%.
combination
produced
best
performance
(R2
=
0.814,
RMSE
18.789
Mg
C/ha,
rRMSE
26.235%),
when
or
alone
(optical:
R2
0.657
35.317%;
SAR:
0.672
34.701%).
Feature
importance
analysis
also
verified
vegetation
indices,
SWIR
1/2
bands,
backscatter
VV
polarization
most
critical
variables
Furthermore,
incorporating
into
modeling
illustrated
be
effective
reducing
saturation
within
high-biomass
forests.
demonstrated
superiority
While
applicability
this
methodology
only
evergreen
coniferous
may
provide
viable
approach
needed
make
full
use
increasingly
better
free
satellite
estimate
high
accuracy,
supporting
policy
making
management
Language: Английский
Remote sensing supported analysis of the effect of wind erosion on local air pollution in arid regions: a case study from Iğdır province in eastern Türkiye
ENVIRONMENTAL SYSTEMS RESEARCH,
Journal Year:
2023,
Volume and Issue:
12(1)
Published: April 19, 2023
Abstract
PM
pollution
is
one
of
the
most
important
environmental
problems
worldwide.
One
sources
pollution,
which
has
a
negative
impact
on
human
health,
dust
that
enters
atmosphere,
especially
in
arid
regions.
Iğdır
Province,
located
east
Anatolia,
an
climate
character
and
was
selected
as
polluted
province
Europe
2021
2022
(in
terms
2.5
pollution).
In
this
study,
effect
wind
erosion-induced
air
investigated.
We
think
local
erosion
during
summer
season
(May–September)
effective
pollution.
Because
there
are
no
industrial
activities,
vehicular
traffic,
fuel
consumption
volcanic
activities
cause
around
Iğdır.
On
other
hand,
Türkiye’s
second
largest
area
two
areas
here,
storms
quite
frequent.
The
causes
erosion,
main
factors
period,
were
investigated
from
geographical
perspective
various
data
sets
utilized.
Then,
sites
examined
their
regional
distributions
indicated.
Research
findings
supported
by
remote
sensing
techniques
(quartz
index,
aerosol
density,
etc.).
All
obtained
support
idea
dominant
factor
high
level
area.
number
days
with
strong
winds
period
EU,
WHO
national
limit
values
exceeded
almost
every
day.
Language: Английский