Remote Sensing,
Journal Year:
2022,
Volume and Issue:
14(10), P. 2475 - 2475
Published: May 21, 2022
Inland
surface
water
is
often
the
most
accessible
freshwater
source.
As
opposed
to
groundwater,
replenished
in
a
comparatively
quick
cycle,
which
makes
this
vital
resource—if
not
overexploited—sustainable.
From
global
perspective,
plentiful.
Still,
depending
on
region,
availability
severely
limited.
Additionally,
climate
change
and
human
interventions
act
as
large-scale
drivers
cause
dramatic
changes
established
dynamics.
Actions
have
be
taken
secure
sustainable
usage.
This
requires
informed
decision
making
based
reliable
environmental
data.
Monitoring
inland
dynamics
therefore
more
important
than
ever.
Remote
sensing
able
delineate
number
of
ways
by
using
optical
well
active
passive
microwave
sensors.
In
review,
we
look
at
proceedings
within
discipline
reviewing
233
scientific
works.
We
provide
an
extensive
overview
used
sensors,
spatial
temporal
resolution
studies,
their
thematic
foci,
distribution.
observe
that
wide
array
available
sensors
datasets,
along
with
increasing
computing
capacities,
shaped
field
over
last
years.
Multiple
analysis-ready
products
are
for
investigating
area
dynamics,
but
so
far
none
offer
high
resolution.
Modeling Earth Systems and Environment,
Journal Year:
2023,
Volume and Issue:
9(3), P. 3151 - 3173
Published: Jan. 7, 2023
Abstract
Land
cover
change
has
posed
significant
concerns
to
biodiversity
and
climate
in
Bangladesh
globally.
Despite
the
country’s
designation
of
forest
regions
as
protected
areas
conserve
their
valuable
resources,
deforestation
conversion
remained
unabated.
Fashiakhali
Wildlife
Sanctuary
(FKWS),
a
area
Chittagong
Hill
Tracts,
its
surrounding
forested
impact
have
experienced
considerable
changes
over
years,
yet
are
deficient
extensive
assessment.
This
study
evaluated
land
use
(LULC)
FKWS
almost
3
decades
(1994–2021)
using
multispectral
remotely
sensed
data.
The
Landsat
images
1994,
2001,
2010,
2021
were
classified
maximum
likelihood
algorithm
analyzed
for
detection.
comparative
potential
vegetation
indices,
including
Normalized
Difference
Vegetation
Index
(NDVI)
Soil
Adjusted
(SAVI),
assessment,
relationship
between
Surface
Temperature
(LST)
NDVI
was
also
assessed.
A
loss
around
1117.17
ha
(16%)
recorded
1994
2021,
with
hugest
proportion
867.78
(12.24%)
deforested
first
period
(1994–2001).
Agricultural
declined
by
593.73
(8.37%)
within
entire
period,
despite
initial
increase
392.04
(5.53%)
2001
being
primary
driver
earlier
deforestation.
However,
recent
decade
(2010–2021),
settlement
expansion
963.90
(13.59%)
due
massive
human
migration
contributed
most
remarkable
overall
1731.51
(24.42%).
Furthermore,
provided
better
more
accurate
assessment
than
SAVI
recommended
aid
quick
evaluation
monitoring
future
impacts
agriculture,
settlement,
other
sorts
on
cover.
In
tandem
widely
acknowledged
issue
increased
temperature
change,
an
absolute
negative
correlation
found
LST,
confirming
area.
ENVIRONMENTAL SYSTEMS RESEARCH,
Journal Year:
2024,
Volume and Issue:
13(1)
Published: Aug. 14, 2024
A
precise
and
up-to-date
Land
Use
Cover
(LULC)
valuation
serves
as
the
fundamental
basis
for
efficient
land
management.
Google
Earth
Engine
(GEE),
with
its
numerous
machine
learning
algorithms,
is
now
most
advanced
open-source
global
platform
rapid
accurate
LULC
classification.
Thus,
this
study
explores
dynamics
of
changes
between
1993
2023
using
Landsat
imagery
algorithms
in
(GEE)
platform.
Focus
group
discussion
key
informant
interviews
were
also
used
to
get
further
data
regarding
dynamics.
Support
Vector
Machine
(SVM),
Random
Forest
(RF),
Classification
Regression
Trees
(CART)
demonstrated
Six
types
(agricultural
land,
grazingland,
shrubland,
built-up
area,
forest
bareland)
identified
mapped
1993,
2003,
2013,
2023.
The
overall
accuracy
kappa
coefficient
that
RF
images
comprising
auxiliary
variables
(spectral
indices
topographic
data)
performed
better
than
SVM
CART.
Despite
being
common
type
LULC,
agricultural
shows
a
trend
shrinking
during
period.
area
bareland
exhibits
progressive
expansion.
amount
shrubland
has
decreased
over
last
20
years,
whereas
grazinglands
have
exhibited
expanding
trends.
Population
growth,
expansion,
fuelwood
collection,
charcoal
production,
areas
illegal
settlement
intervention
are
among
causes
shifts.
This
provides
reliable
information
about
patterns
Robit
watershed,
which
can
be
develop
frameworks
watershed
management
sustainability.
Remote Sensing,
Journal Year:
2018,
Volume and Issue:
10(12), P. 2053 - 2053
Published: Dec. 17, 2018
Land
cover
and
its
dynamic
information
is
the
basis
for
characterizing
surface
conditions,
supporting
land
resource
management
optimization,
assessing
impacts
of
climate
change
human
activities.
In
extraction,
traditional
convolutional
neural
network
(CNN)
method
has
several
problems,
such
as
inability
to
be
applied
multispectral
hyperspectral
satellite
imagery,
weak
generalization
ability
model
difficulty
automating
construction
a
training
database.
To
solve
these
this
study
proposes
new
type
deep
based
on
Landsat-8
Operational
Imager
(OLI)
imagery.
The
integrates
cascaded
cross-channel
parametric
pooling
average
layer,
applies
hierarchical
sampling
strategy
realize
automatic
dataset,
determines
technical
scheme
model-related
parameters,
finally
performs
classification
remote
sensing
images.
This
used
extract
from
Qinhuangdao
City,
Hebei
Province,
compared
experimental
results
with
those
obtained
by
methods.
show
that:
(1)
proposed
(DCNN)
can
automatically
construct
dataset
classify
images
using
networks,
which
improves
simplifies
application
model.
(2)
DCNN
provides
best
in
area.
overall
accuracy
data
82.0%,
kappa
coefficient
0.76.
improved
5%
14%
support
vector
machine
maximum
likelihood
method,
respectively.
Geomatics Natural Hazards and Risk,
Journal Year:
2020,
Volume and Issue:
11(1), P. 112 - 130
Published: Jan. 1, 2020
This
study
was
conducted
to
investigate
the
spatiotemporal
changes
of
land
use/land
cover
(LULC)
along
eastern
coast
United
Arab
Emirates
(UAE)
over
a
20-year
period
using
an
integration
remote
sensing
and
Geographic
Information
Systems
techniques.
The
impact
use
change
on
flooding
potential
also
investigated
through
hydrologic
model
simulations.
Landsat
images
years
1996,
2006
2016
were
processed
analyzed.
Change
detection
carried
out
assess
in
built-up
areas.
Furthermore,
urbanization
assessed
two
major
watersheds
Fujairah
Emirate.
It
observed
that
for
1996–2006
vegetation
areas
had
increased
at
rate
11.23%
24.56%,
respectively.
For
2006–2016,
this
expansion
more
than
doubled
terms
class
(27.51%)
slightly
(28.98%).
analysis
revealed
has
mostly
occurred
coastal
boundary.
Hydrologic
simulations
quantified
role
increasing
potential.
increase
depends
watershed
characteristics
magnitude
rainfall
event.
Land Degradation and Development,
Journal Year:
2020,
Volume and Issue:
32(2), P. 792 - 802
Published: Sept. 30, 2020
Abstract
Changes
in
land
management
and
climate
alter
vegetation
dynamics,
but
the
determinants
of
changes
often
remain
elusive,
especially
global
drylands.
Here
we
assess
grassland
greenness
on
Mongolian
Plateau,
one
world's
largest
biomes,
which
covers
Mongolia
province
Inner
China.
We
use
spatial
panel
regressions
to
quantify
impact
precipitation,
temperature,
radiation,
intensity
livestock
grazing
normalized
difference
indices
(NDVI)
during
growing
seasons
from
1982
2015
at
county
level.
The
results
suggest
that
Plateau
experienced
greening
2015.
Precipitation
animal
density
were
most
influential
factors
contributing
higher
NDVI
grasslands
Mongolia.
Our
highlight
dominant
effect
variability,
precipitation
findings
challenge
common
belief
pressure
is
key
driver
for
degradation.
analysis
exemplifies
how
representative
wall‐to‐wall
large
areas
can
be
attained
exploring
space–time
data
adds
empirical
insights
puzzling
relationship
between
growth
dryland
areas.
