GIScience & Remote Sensing,
Год журнала:
2024,
Номер
62(1)
Опубликована: Дек. 13, 2024
Desert
shrubs
are
the
dominant
vegetation
type
in
arid
deserts
and
serve
as
crucial
elements
sand
retention,
biodiversity
maintenance,
carbon
sequestration.
However,
due
to
their
patchy
scattered
distributions
spectral
resemblance
herbaceous
plants,
desert
shrub
mapping
relies
on
high-resolution
imagery,
which
is
less
accessible
for
large-scale
mapping.
Here,
a
set
of
indices
Sentinel-2
(DSMIS)
universal
medium-resolution
imagery
(DSMIL)
developed
distinguish
with
dense
vimen
canopies.
The
index
exploits
canopy
structure
characteristics,
have
sparse
multilayered
high
proportion
desiccated
branches,
resulting
consistently
low
reflectance
red-edge
near-infrared
range.
effectiveness
DSMI
was
examined
Ordos,
China.
In
experiment,
an
optimal
threshold
10.3
obtained
via
DSMIs
Sentinel-2,
achieved
overall
accuracy
91.6%
identified
minimum
coverage
0.23.
comparison,
9.7
by
DSMIL
Landsat-8,
achieving
90.1%
identifying
0.17.
performance
superior
that
commonly
used
random
forest,
this
could
further
improve
classification
complement
machine
learning
methods.
late
stage
nongrowing
season
period
index.
also
performed
well
at
two
test
sites
diverse
species
growing
conditions.
This
study
provides
novel
practical
tool
monitoring
desertification
regions.
It
offers
new
perspective
historical
dynamic
studies
other
land
cover
types
where
only
optical
data
available.
Sensors,
Год журнала:
2025,
Номер
25(10), С. 3147 - 3147
Опубликована: Май 16, 2025
Declassified
Keyhole
imagery
partially
provides
multi-temporal
coverage
that
can
support
land-use
change
analysis.
However,
the
volume
of
commercial
(paid)
data
is
much
larger
than
free
imagery,
and
extent
to
which
enhance
application
for
analysis
remains
unknown.
In
this
work,
full
archive
images
China
was
obtained
from
USGS
identify
regions
with
repeated
automatically
by
using
ArcPy
library
in
Python.
The
years
1960
1984
were
divided
into
five
5-year
periods
(T1,
1960~1964;
T2,
1965~1969;
T3,
1970~1974;
T4,
1975~1979;
T5,
1980~1984).
images'
metadata,
including
resolution,
acquisition
time,
image
extent,
utilized
classify
meter
level
(C1),
five-meter
(C2),
ten-meter
(C3).
spatial
distributions
combinations
at
different
resolutions
each
period
resolution
across
investigated
extract
repeated-coverage
regions.
proportions
nearly
100%
C1
T5
periods;
C2
T1
T2;
C3
T3.
T3
featured
extensive
all
three
(66%).
mainly
covered
C2/C3
(93%),
T4
had
C1/C3
(68%).
contrast,
T2
relied
primarily
on
(100%),
only
(96%).
For
changes
almost
areas
T3/T4/T5
time
span
could
be
detected,
images,
corresponding
spans
T1/T2
T1/T3.
Although
study
focused
area
detection
within
China,
methodology
Python
codes
provided
allow
implementation
an
automated
process
1960s
1980s
other
worldwide.
Land,
Год журнала:
2024,
Номер
13(6), С. 845 - 845
Опубликована: Июнь 13, 2024
Drylands
are
characterized
by
unique
ecosystem
types,
sparse
vegetation,
fragile
environments,
and
vital
services.
The
accurate
mapping
of
dryland
ecosystems
is
essential
for
their
protection
restoration,
but
previous
approaches
primarily
relied
on
modifying
land
use
data
derived
from
remote
sensing,
lacking
the
direct
utilization
latest
sensing
technologies
methods
to
map
ecosystems,
especially
failing
effectively
identify
key
with
vegetation.
This
study
attempts
integrate
Google
Earth
Engine
(GEE),
random
forest
(RF)
algorithm,
multi-source
(spectral,
radar,
terrain,
texture),
feature
optimization,
image
segmentation
develop
a
fine-scale
method
an
ecologically
critical
area
in
northern
China.
results
showed
following:
(1)
Incorporating
significantly
improved
overall
classification
accuracy
radar
features
contributing
most,
followed
terrain
texture
features.
(2)
Optimizing
set
can
enhance
accuracy,
reaching
91.34%
kappa
coefficient
0.90.
(3)
User’s
accuracies
exceeded
90%
forest,
cropland,
water,
were
slightly
lower
steppe
shrub-steppe
still
above
85%,
demonstrating
efficacy
GEE
RF
algorithm
vegetation
other
ecosystems.
Accurate
requires
accounting
regional
heterogeneity
optimizing
sample
selection
based
field
surveys
precisely
depict
patterns
complex
regions.
mapped
typical
region,
provides
baseline
ecological
restoration
policies
this
as
well
methodological
reference
similar
Land,
Год журнала:
2024,
Номер
13(10), С. 1657 - 1657
Опубликована: Окт. 11, 2024
Maintaining
a
balance
between
urban
land
(UL)
expansion
and
population
(UP)
growth
is
one
of
the
goals
sustainable
development,
maintaining
this
requires
more
theoretical
exploration
regional
experience.
This
paper
re-evaluated
imbalances
in
(IGULUP)
from
perspective
allometric
explored
its
influencing
mechanism,
taking
agglomerations
(UAs)
China
as
case.
reveals
that
rate
UL
slightly
higher
than
UP.
However,
IGULUP
vary
according
to
development
stages.
UAs
primary
stage
early
face
dilemma
where
grows
faster
Conversely,
for
later
mature
stage,
UP
UL.
Finally,
an
increase
economic
level,
agglomeration,
fiscal
expenditure,
compactness
can
help
mitigate
gap
In
contrast,
industrial
structure,
urbanization
foreign
direct
investment
may
hinder
improvement
by
accelerating
expansion.
These
findings
make
contributions
formulation
targeted
use
control
policies
strategies.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 9, 2024
Abstract
Land
use
change
is
an
important
driving
factor
for
global
environmental
change.
Clarifying
its
changing
characteristics
and
factors
of
great
guiding
significance
optimizing
land
patterns,
improving
regional
ecological
environment,
increasing
efficiency.
This
article
based
on
the
grid
data
in
Chuzhou
City
from
2010,
2015,
2020,
ENVI
GIS
software
are
used
to
preprocess
data.
The
transfer
matrix
dynamic
degree
model
used,
combined
with
actual
situation
City,
2010
2020
analyzed.
On
this
basis,
principal
component
analysis
analyze
forces
interannual
changes
City.
results
show
that
structure
was
still
mainly
composed
arable
land,
forest
construction
land.
area
other
types
relatively
small,
but
grassland
decreased
significantly.
unused
continued
increase,
showing
largest
increase;
In
past
10
years,
has
undergone
significant
changes,
a
smaller
difference
between
different
trend
towards
balanced
structure;
main
rapid
economic
development
agricultural
production
productivity.
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Июль 12, 2024
Abstract
Burkina
Faso's
protected
areas,
particularly
Corridor
1,
are
under
heavy
pressure,
resulting
in
the
degradation
of
these
areas.
Despite
efforts
made
field
by
government
and
its
partners,
results
still
mixed.
Several
studies
have
analysed
changes
vegetation
cover
landscape
but
failed
to
examine
spatial
behaviour
factors
responsible
for
The
aim
this
research
project
is
fill
gap
describing
identifying
mapping
that
exert
pressure
their
impact
on
corridor
1
Po-Nazinga-Sissili
ecological
complex.
methodology
implemented
based
a
hierarchical
multi-criterion
analysis
using
geographic
information
system
tools.
Land
uses
data
from
2010
2020
location
offences
were
used.
Documentary
was
also
carried
out
characterise
factors.
show,
firstly,
has
been
declining,
with
14.2%
reduction
shrub
savannah,
while
area
fields
increased
59.4%
10
years.
Secondly,
used
identify
areas
south
near
villages
Sarro
Oualem.
Finally,
corridor's
vulnerability
shows
subject
strong
experiencing
significant
plant
cover.
show
Faso
essentially
due
human
action.
Land,
Год журнала:
2024,
Номер
13(9), С. 1476 - 1476
Опубликована: Сен. 12, 2024
Since
China’s
reform
and
opening
up
in
1978,
the
reclamation
abandonment
of
cropland
Xinjiang
have
become
significant
features
land
use
change
arid
Northwest
China.
However,
spatiotemporal
changes
driving
mechanisms
over
long
time
periods
are
still
unclear,
but
this
is
crucial
understanding
inland
land,
providing
important
insights
for
management
agricultural
development.
Based
on
40
years
remote
sensing
data
resources
environment,
study
examines
characteristics
four
since
1980.
Additionally,
it
uses
an
optimal
parameter
geographical
detector
model
to
quantify
factors
each
period.
The
results
indicate
that
experiences
a
“slow
decrease–rapid
increase”
trend,
forming
“V-shaped”
pattern,
while
shows
“rapid
decrease–slow
“U-shaped”
pattern.
These
trends
can
be
divided
into
three
periods:
1980–1990
(unstable
growth),
1990–2010
(stable
2010–2020
(growth
with
constraints).
movement
pattern
reclamation’s
center
gravity
“slightly
southeast–slightly
northeast–southwest”,
whereas
abandonment’s
shifts
“northeast–southwest–northeast”.
Further
analysis
reveals
impact
technological
investment
infrastructure
has
increased,
influence
natural
environmental
decreased.
Although
climate
water
remain
key
abandonment,
economic
social
gradually
diminished,
mechanization
steadily
risen.
GIScience & Remote Sensing,
Год журнала:
2024,
Номер
62(1)
Опубликована: Дек. 13, 2024
Desert
shrubs
are
the
dominant
vegetation
type
in
arid
deserts
and
serve
as
crucial
elements
sand
retention,
biodiversity
maintenance,
carbon
sequestration.
However,
due
to
their
patchy
scattered
distributions
spectral
resemblance
herbaceous
plants,
desert
shrub
mapping
relies
on
high-resolution
imagery,
which
is
less
accessible
for
large-scale
mapping.
Here,
a
set
of
indices
Sentinel-2
(DSMIS)
universal
medium-resolution
imagery
(DSMIL)
developed
distinguish
with
dense
vimen
canopies.
The
index
exploits
canopy
structure
characteristics,
have
sparse
multilayered
high
proportion
desiccated
branches,
resulting
consistently
low
reflectance
red-edge
near-infrared
range.
effectiveness
DSMI
was
examined
Ordos,
China.
In
experiment,
an
optimal
threshold
10.3
obtained
via
DSMIs
Sentinel-2,
achieved
overall
accuracy
91.6%
identified
minimum
coverage
0.23.
comparison,
9.7
by
DSMIL
Landsat-8,
achieving
90.1%
identifying
0.17.
performance
superior
that
commonly
used
random
forest,
this
could
further
improve
classification
complement
machine
learning
methods.
late
stage
nongrowing
season
period
index.
also
performed
well
at
two
test
sites
diverse
species
growing
conditions.
This
study
provides
novel
practical
tool
monitoring
desertification
regions.
It
offers
new
perspective
historical
dynamic
studies
other
land
cover
types
where
only
optical
data
available.
