Journal of Environmental Informatics Letters,
Год журнала:
2024,
Номер
unknown
Опубликована: Янв. 1, 2024
Soil
erosion
is
a
significant
environmental
issue
in
most
mountainous
areas
and
further
exacerbated
due
to
ongoing
climatic
changes
anthropogenic
activities.
not
only
triggers
natural
disasters
like
landslides
but
also
degrades
the
fertile
topsoil
layers.
Therefore,
modeling
evaluation
of
soil
river
basins
are
highly
important.
The
Uma
Oya
River
Basin
(UORB),
Sri
Lanka
an
area
with
rich
biodiversity
important
for
agricultural
production.
Moreover,
this
frequently
discussed
developments
Project.
This
paper
presents
comprehensive
UORB
results
compared
two
decades
from
2000
2020.
Revised
Universal
Loss
Equation
(RUSLE)
was
used
determine
annual
rates.
In
addition,
spatial-temporal
variation
land
use
cover
assessed
UORB.
Results
revealed
that
extreme
scenarios
occur
when
forests
other
vegetation
lands
converted
farmlands.
We
found
loss
largely
happened
steep
slopes,
reduction
forest
covers,
growth
cultivation
lands.
Erosion-prone
basin
identified
conservation
strategies
discussed.
impact
climate
change
on
highlighted.
Discover Environment,
Год журнала:
2024,
Номер
2(1)
Опубликована: Апрель 20, 2024
Abstract
Human
LULCC
is
the
many
driver
of
environmental
changes.
Accurate
and
up-to-date
current
predicted
information
on
important
in
land
use
planning
natural
resource
management;
however,
Zambia,
detailed
insufficient.
Therefore,
this
study
assessed
dynamics
LULC
change
(2000–2020)
future
projections
(2020–2030)
for
Zambia.
The
ESA
CCI
cover
maps,
which
have
been
developed
from
Sentinel-2
images
were
used
study.
This
dataset
has
a
grid
spatial
resolution
300
m
2000,
2010
2020.
31
Classification
reclassified
into
ten
(10)
local
Classifications
using
r.class
module
QGIS
2.18.14.
2000
maps
to
simulate
2020
scenario
Artificial
Neural
Network
(Multi-layer
Perception)
algorithms
Modules
Land
Use
Change
Evaluation
(MOLUSCE)
plugin
predict
2030
classes.
reference
validate
model.
Predicted
against
observed
map,
Kappa
(loc)
statistic
was
0.9869.
patterns
successfully
simulated
ANN-MLP
with
accuracy
level
95%.
classes
2010–2020
calibration
period.
types
shows
an
increase
built-up
(71.44%)
decrease
cropland
(0.73%)
map.
Dense
forest
(0.19%),
grassland
(0.85%)
bare
(1.37%)
will
reduce
2020–2030.
However,
seasonally
flooded,
sparse
forest,
shrub
land,
wetland
water
body
marginally.
largest
other
types.
insights
show
that
can
be
LULCC,
generated
employed
National
Adaptation
Plans
at
regional
national
scale.
Thermal Science and Engineering,
Год журнала:
2023,
Номер
6(2), С. 2087 - 2087
Опубликована: Окт. 19, 2023
To
gain
a
deep
understanding
of
maintenance
and
repair
planning,
investigate
the
weak
points
distribution
network,
discover
unusual
events,
it
is
necessary
to
trace
shutdowns
that
occurred
in
network.
Many
incidents
happened
due
failure
thermal
equipment
schools.
On
other
hand,
most
important
task
electricity
companies
provide
reliable
stable
electricity,
which
minimal
blackouts
standard
voltage
should
accompany.
This
research
uses
seasonal
time
series
artificial
neural
network
approaches
models
predict
rate
one
used
two
areas
covered
by
greater
Tehran
company.
These
data
were
extracted
weekly
from
April
2019
March
2021
ENOX
incident
registration
software.
For
this
purpose,
after
pre-processing
data,
appropriate
final
model
was
presented
with
help
Minitab
MATLAB
Also,
average
air
temperature,
rainfall,
wind
speed
selected
as
input
variables
The
mean
square
error
has
been
evaluate
proposed
models’
rate.
results
show
performed
better
than
multi-layer
perceptron
predicting
target
can
be
future
periods.
Remote Sensing,
Год журнала:
2024,
Номер
16(16), С. 3059 - 3059
Опубликована: Авг. 20, 2024
Degradation
and
desertification
represent
serious
threats,
as
they
present
severe
environmental
socio-economic
consequences,
demanding
immediate
action.
Although
a
recognized
methodology
for
assessing
degradation
is
missing,
remote
sensing
has
been
powerful
support
its
accessibility
efficacy.
The
aim
of
this
study
to
examine
the
application
land
soil
desertification.
A
total
278
research
papers
retrieved
from
Scopus/Web
Science
database
published
over
past
decade
have
analyzed.
From
analysis
scientific
publications,
rising
interest
these
topics
dominance
China
registered.
Established
satellite
data,
Landsat,
MODIS,
despite
limitations
in
accuracy
resolution,
remain
popular
due
easy
access.
This
restricts
broader
scales
limits
practical
applications
like
management.
prevalent
use
vegetation
indexes,
while
convenient,
can
be
misleading
their
indirect
connection
health.
Consequently,
vegetation-based
models
may
not
fully
capture
complexities
involved.
To
improve
understanding,
suggests
shift
towards
multi-indexes
move
away
relying
solely
on
readily
available
data
products.
Moreover,
fusion
methods
could
provide
more
holistic
view.
Remote Sensing,
Год журнала:
2024,
Номер
16(13), С. 2390 - 2390
Опубликована: Июнь 28, 2024
Soil
erosion
represents
a
complex
ecological
issue
that
is
present
on
global
level,
with
negative
consequences
for
environmental
quality,
the
conservation
and
availability
of
natural
resources,
population
safety,
material
security,
both
in
rural
urban
areas.
To
mitigate
harmful
effects
soil
erosion,
map
can
be
created.
Broadly
applied
Balkan
Peninsula
region
(Serbia,
Bosnia
Herzegovina,
Croatia,
Slovenia,
Montenegro,
North
Macedonia,
Romania,
Bulgaria,
Greece),
Erosion
Potential
Method
(EPM)
an
empirical
model
widely
process
creating
maps.
In
this
study,
innovation
identification
mapping
processes
was
made,
coefficient
types
extent
slumps
(φ),
representing
one
most
sensitive
parameters
EPM.
The
(φ)
consisted
applying
remote
sensing
methods
satellite
images
from
Landsat
mission.
research
area
which
were
obtained
thematic
maps
(coefficient
φ)
created
Federation
Herzegovina
Brčko
District
(situated
Herzegovina).
Google
Earth
Engine
(GEE)
platform
employed
to
retrieve
7
Enhanced
Thematic
Mapper
plus
(ETM+)
8
Operational
Land
Imager
Thermal
Infrared
Sensor
(OLI/TIRS)
imagery
over
period
ten
years
(from
1
January
2010
31
December
2020).
performed
based
Bare
Index
(BSI)
by
equation
fractional
bare
cover.
spatial–temporal
distribution
cover
enabled
definition
values
field.
An
accuracy
assessment
conducted
190
reference
samples
field
using
confusion
matrix,
overall
(OA),
user
(UA),
producer
(PA),
Kappa
statistic.
Using
OA
85.79%
obtained,
while
UA
ranged
33%
100%,
PA
50%
100%.
Applying
statistic,
0.82
indicating
high
level
accuracy.
time
series
multispectral
each
month
crucial
element
monitoring
occurrence
various
(surface,
mixed,
deep)
Additionally,
it
contributes
significantly
decision-making,
strategies,
plans
domain
control
work,
development
identifying
erosion-prone
areas,
defense
against
torrential
floods,
creation
at
local,
regional,
national
levels.