Spatial Autocorrelation Analysis of CO and NO2 Related to Forest Fire Dynamics
ISPRS International Journal of Geo-Information,
Journal Year:
2025,
Volume and Issue:
14(2), P. 65 - 65
Published: Feb. 6, 2025
The
increasing
frequency
and
severity
of
forest
fires
globally
highlight
the
critical
need
to
understand
their
environmental
impacts.
This
study
applies
spatial
autocorrelation
techniques
analyze
dispersion
patterns
carbon
monoxide
(CO)
nitrogen
dioxide
(NO2)
emissions
during
2021
Manavgat
in
Türkiye,
using
Sentinel-5P
satellite
data.
Univariate
(UV)
Global
Moran’s
I
values
indicated
strong
for
CO
(0.84–0.93)
NO2
(0.90–0.94),
while
Bivariate
(BV)
(0.69–0.84)
demonstrated
significant
correlations
between
two
gases.
UV
Local
analysis
identified
distinct
High-High
(UV-HH)
Low-Low
(UV-LL)
clusters,
with
concentrations
exceeding
0.10000
mol/m2
exhibiting
wide
dispersion,
concentrations,
above
0.00020
mol/m2,
remained
localized
near
intense
fire
zones
due
its
shorter
atmospheric
lifetime.
BV
revealed
overlapping
BV-HH
(high
CO,
high
NO2)
BV-LL
(low
low
influenced
by
topography
meteorological
factors.
These
findings
enhance
understanding
gas
emission
dynamics
provide
insights
into
influence
combustion
processes
on
pollutant
dispersion.
Language: Английский
Investigating FWI Moisture Codes in Relation to Satellite-Derived Soil Moisture Data across Varied Resolutions
Fire,
Journal Year:
2024,
Volume and Issue:
7(8), P. 272 - 272
Published: Aug. 5, 2024
In
the
Mediterranean
region,
particularly
in
Antalya,
southern
Türkiye,
rising
forest
fire
risks
due
to
climate
change
threaten
ecosystems,
property,
and
lives.
Reduced
soil
moisture
during
growing
season
is
a
key
factor
increasing
risk
by
stressing
plants
lowering
fuel
content.
This
study
assessed
content
(FMC)
ten
fires
(2019–2021)
affecting
over
50
hectares.
The
Fire
Weather
Index
(FWI)
its
components
(FFMC,
DMC,
DC)
were
calculated
using
data
from
General
Directorate
of
Meteorology,
EFFIS
(8
km),
ERA5
(≈28
km)
satellite
sources.
Relationships
between
FMCs,
satellite-based
datasets
(SMAP,
SMOS),
land
surface
temperature
(LST)
(MODIS,
Landsat
8)
analyzed.
Strong
correlations
found
FWI
codes
moisture,
with
SMAP.
Positive
observed
LST
FWIs,
while
negative
evident
moisture.
Statistical
models
integrating
situ
(R:
−0.86,
−0.84,
−0.83
for
FFMC,
predicted
levels
extended
events
effectively,
model
accuracy
through
RMSE
(0.60–3.64%).
SMAP
(0–5
cm)
dataset
yielded
lower
0.60–2.08%,
aligning
higher
correlation.
underlines
critical
role
comprehensive
assessments
highlights
necessity
incorporating
modeled
management
strategies,
regions
lacking
monitoring.
Language: Английский
Spatio-temporal analysis and risk management of forest fires (West Algerian region)
Folia Forestalia Polonica,
Journal Year:
2024,
Volume and Issue:
66(4), P. 285 - 300
Published: Dec. 1, 2024
Abstract
The
forest
fires
constitute
a
major
danger
for
the
forests
in
Western
Algerian
region.
They
are
caused
by
combination
of
several
factors,
particularly
climatic
and
anthropogenic,
which
often
amplified
composition
vegetation
that
is
considered
highly
flammable
during
dry
season.
priority
action
to
deal
with
this
phenomenon
strengthen
monitoring
resources
apply
preventive
silvicultural
measures
avoid
outbreak
fires,
without
forgetting
efforts
educate
raise
public
awareness.
A
systematic
examination
data
retrieved
from
General
Forests
Directorate
Forest
Fires
stretching
between
2003
2017
reveals
spatiotemporal,
spatial
temporal
evolution
statistical
approach
applied
study
allowed
us
identify
periods
our
mostly
vulnerable
allowing
programing
an
plan
effective
fire
management.
map
produced
calculating
Fire
Danger
Index
can
be
decision-support
tool
managers
locate
areas
at
high
risk
order
take
limit
loss
natural
resources,
properties,
even
human
lives.
Language: Английский