Environment International,
Journal Year:
2023,
Volume and Issue:
183, P. 108392 - 108392
Published: Dec. 16, 2023
Large
land
consolidation
projects
modify
the
structures
and
functions
of
regional
ecosystems
through
reshaping
territorial
spatial
pattern,
thereby
affecting
ecological
environmental
quality
(EEQ).
To
investigate
effects
large-scale
on
EEQ,
this
study
takes
major
project
"bulldoze
mountains
to
create
land"
(BMCL)
in
Yan'an
City
as
a
research
object
evaluates
change
EEQ
based
Remote
Sensing
Ecological
Index
(RSEI).
The
consolidated
area
control
were
set
up
comparatively
analyze
processes
distribution
characteristics
these
two
areas
full
life
cycle
BMCL.
According
results,
mean
RSEI
was
0.128
lower
than
that
area,
always
area.
BMCL
had
strong
negative
impact
grade
especially
early
stage.
However,
positive
effect
gradually
emerged
late
stage
large
project.
overall
has
also
improved.
results
stepwise
regression
analysis
indicated
wetness
component
normalized
differential
vegetation
index
played
key
roles
improving
Overall,
local
strongly
affected
but
would
not
cause
whole
region
experience
any
dramatic,
abrupt
short
term.
This
provided
references
for
evaluation
at
scale,
offering
feasible
way
evaluate
spatio-temporal
Sustainability,
Journal Year:
2024,
Volume and Issue:
16(4), P. 1447 - 1447
Published: Feb. 8, 2024
The
environmental
quality
of
a
mining
city
has
direct
impact
on
regional
sustainable
development
and
become
key
indicator
for
assessing
the
effectiveness
national
policies.
However,
against
backdrop
accelerated
urbanization,
increased
demand
resource
development,
promotion
concept
ecological
civilization,
cities
are
faced
with
major
challenge
balancing
economic
protection.
This
study
aims
to
deeply
investigate
spatial
temporal
variations
its
driving
mechanisms
mineral
resource-based
cities.
utilizes
wide
coverage
multitemporal
capabilities
MODIS
optical
thermal
infrared
remote
sensing
data.
It
innovatively
develops
index
(RSEI)
algorithm
PIE-Engine
cloud
platform
quickly
obtain
RSEI,
which
reflects
environment.
evolution
characteristics
in
seven
typical
China
from
2001
2022
were
analyzed.
Combined
vector
mine
surface
data,
variability
impacts
activities
environment
quantitatively
separated
explored.
In
particular,
taken
into
account
by
creating
buffer
zones
zoning
statistics
analyze
response
relationship
between
RSEI
these
factors,
including
distance
area
percentage
area.
addition,
drivers
2019
analyzed
through
Pearson
correlation
coefficients
pixel
10
natural,
economic,
mining.
Regression
modeling
was
performed
using
random
forest
(RF)
model,
ranked
order
importance
factor
assessment.
results
showed
that
(1)
changed
significantly
during
period,
negative
significant.
(2)
areas
low
values
closely
related
(3)
generally
lower
than
average
level
gradually
as
site
increased.
(4)
increase
size
initially
exacerbates
environment,
but
is
weakened
beyond
certain
threshold.
(5)
most
important
affecting
followed
DEM,
GDP,
precipitation.
great
advancing
formulating
strategies.
Geocarto International,
Journal Year:
2024,
Volume and Issue:
39(1)
Published: Jan. 1, 2024
Timely
and
objective
assessment
of
the
optimal
season
for
construction
remote
sensing
ecological
index
(RSEI)
is
great
significance
accurate
effective
environment
quality.
We
manipulated
RSEI
in
to
monitor
seasonal
variations
quality
(EEQ)
Beijing-Tianjin-Hebei
(JJJ)
region
from
2001
2020.
First,
we
evaluated
image
across
all
four
seasons
filled
missing
observations
through
liner
interpolation.
Second,
Seasonal
was
constructed
using
MODIS
compared
different
years.
Third,
temporal
spatial
within
same
EEQ.
Additionally,
Moran's
I
utilized
evaluate
autocorrelation
EEQ,
stability
correlation
between
indicators
compared.
The
results
showed
that:
1)
PC1
component
concentrates
most
characteristics
indicators,
especially
summer
(over
71%);
2)
Moran'
2001,
2006,
2011,
2016
2020
are
0.909,
0.898,
0.917,
0.921
0.892,
respectively,
which
indicated
that
EEQ
has
a
strong
positive
correlation.
3)
high
years,
standard
deviation
fluctuated
slightly
summer,
std
NDVI,
WET,
LST
and,
NDBSI
were
0.005,
0.052,
0.026
0.017,
respectively.
This
study
theoretically
demonstrates
constructing
RSEI,
filling
research
gap
previous
studies
regarding
rationale
selecting
images
periods
vigorous
vegetation
growth
construction,
can
provide
reference
optimum
monitoring
urban
future.
Geomatics Natural Hazards and Risk,
Journal Year:
2024,
Volume and Issue:
15(1)
Published: March 14, 2024
Natural
hazards
usually
cause
heavy
casualties
and
vast
economic
losses,
as
well
severe
damage
to
the
ecological
environment.
Quantitative
scientific
evaluations
of
environment
quality
(EEQ)
its
recovery
trend
after
can
provide
valuable
insights
for
disaster
risk
reductions.
This
study
takes
2010
Ms7.1
Yushu
earthquake
an
example
explore
spatiotemporal
changes
driving
mechanisms
EEQ
before
using
remote
sensing
GIScience.
First,
Moderate-resolution
Imaging
Spectroradiometer
(MODIS)
data
was
selected
establish
based
index
(RSEI).
Then,
we
analyzed
characteristics
Yushu's
from
2001
2020
explored
spatial
autocorrelation
relationships.
Last,
mechanism
in
GeoDetector
model.
The
main
conclusions
are
follows:
(1)
From
perspective
RSEI
time
series,
County
strongly
negatively
affected
during
recovered
earthquake.
(2)
Based
on
a
distribution
analysis,
it
be
observed
that
regions
with
relatively
high
primarily
concentrated
central
southern
areas.
Conversely,
northwestern
southeastern
areas
display
lower
quality.
Moreover,
has
strong
correlation
clustering,
evidenced
by
Moran's
I
value
exceeding
0.7
over
years.
(3)
results,
elevation
population
were
found
key
factors
affecting
post-disaster
EEQ.
interaction
between
slope
plays
most
critical
role
process
recovery.
provides
theoretical
basis
evolution
helps
decision-makers
better
balance
relationship
social
development
environmental
protection
management
urban
planning.
It
also
useful
reference
guidance
future
under
similar
disasters.
International Journal of Digital Earth,
Journal Year:
2023,
Volume and Issue:
16(1), P. 988 - 1007
Published: March 21, 2023
Spatiotemporal
residual
noise
in
terrestrial
earth
observation
products,
often
caused
by
unfavorable
atmospheric
conditions,
impedes
their
broad
applications.
Most
users
prefer
to
use
gap-filled
remote
sensing
products
with
time
series
reconstruction
(TSR)
algorithms.
Applying
currently
available
implementations
of
TSR
large-volume
datasets
is
time-consuming
and
challenging
for
non-professional
limited
computation
or
storage
resources.
This
study
introduces
a
new
open-source
software
package
entitled
'HANTS-GEE'
that
implements
well-known
robust
algorithm,
i.e.
Harmonic
ANalysis
Time
Series
(HANTS),
on
the
Google
Earth
Engine
(GEE)
platform
scalable
data.
Reconstruction
tasks
can
be
conducted
user-defined
spatiotemporal
extents
when
raw
are
GEE.
According
site-based
regional-based
case
evaluation,
tool
effectively
eliminate
cloud
contamination
Compared
traditional
PC-based
HANTS
implementation,
HANTS-GEE
provides
quite
consistent
results
most
vegetated
sites.
The
provide
services
accelerated
processing
speed
reduced
internet
data
transmission
volume,
promoting
algorithm
usage
much
broader
user
communities.
To
our
knowledge,
first
support
full-stack
popular
open-access
satellite
sensors
platforms.
Remote Sensing,
Journal Year:
2023,
Volume and Issue:
15(13), P. 3404 - 3404
Published: July 5, 2023
Global
mapping
of
essential
vegetation
traits
(EVTs)
through
data
acquired
by
Earth-observing
satellites
provides
a
spatially
explicit
way
to
analyze
the
current
states
and
dynamics
our
planet.
Although
significant
efforts
have
been
made,
there
is
still
lack
global
consistently
derived
multi-temporal
trait
maps
that
are
cloud-free.
Here
we
present
processing
chain
for
spatiotemporally
continuous
production
four
EVTs
at
scale:
(1)
fraction
absorbed
photosynthetically
active
radiation
(FAPAR),
(2)
leaf
area
index
(LAI),
(3)
fractional
cover
(FVC),
(4)
chlorophyll
content
(LCC).
The
proposed
workflow
presents
scalable
approach
cloud-free
EVTs.
Hybrid
retrieval
models,
named
S3-TOA-GPR-1.0-WS,
were
implemented
into
Google
Earth
Engine
(GEE)
using
Sentinel-3
Ocean
Land
Color
Instrument
(OLCI)
Level-1B
along
with
associated
uncertainty
estimates.
We
used
Whittaker
smoother
(WS)
temporal
reconstruction
EVTs,
which
led
streams,
here
applied
year
2019.
Cloud-free
produced
5
km
spatial
resolution
10-day
time
intervals.
consistency
plausibility
EVT
estimates
resulting
annual
profiles
evaluated
per-pixel
intra-annually
correlating
against
corresponding
products
both
MODIS
Copernicus
Service
(CGLS).
most
consistent
results
obtained
LAI,
showed
intra-annual
correlations
an
average
Pearson
correlation
coefficient
(R)
0.57
CGLS
LAI
product.
Globally,
results,
specifically
obtaining
higher
than
R>
0.5
reference
between
30
60°
latitude
in
Northern
Hemisphere.
Additionally,
goodness-of-fit
statistics
also
calculated
locally
over
distinct
vegetated
land
covers.
As
general
trend,
covers
pronounced
phenological
high
different
products.
However,
sparsely
fields
as
well
areas
near
equator
linked
smaller
seasonality
lower
correlations.
conclude
gap-free
was
overall
consistent.
Thanks
GEE,
entire
OLCI
L1B
catalogue
can
be
processed
efficiently
on
scale
made
WS
method.
GEE
facilitates
operationally
applicable
easily
accessible
broader
community.
