Annals of the American Association of Geographers,
Journal Year:
2024,
Volume and Issue:
114(7), P. 1568 - 1586
Published: June 18, 2024
The
phenomena
with
within-strata
characteristics
that
are
more
similar
than
between-strata
ubiquitous
(e.g.,
land-use
types
and
image
classifications).
It
can
be
summarized
as
spatial
stratified
heterogeneity
(SSH),
which
is
measured
attributed
using
the
geographical
detector
(Geodetector)
q-statistic.
SSH
typically
calibrated
by
stratification
hundreds
of
algorithms
have
been
developed.
Little
discussed
about
conditions
methods.
In
this
work,
a
novel
method
based
on
head/tail
breaks
introduced
for
purpose
better
capturing
variables
heavy-tailed
distribution.
Compared
to
conventional
sample-based
stratifications,
presented
approach
population-based
optimized
indicates
an
underlying
scaling
property
in
spaces.
requires
no
prior
knowledge
or
auxiliary
supports
naturally
determined
number
strata
instead
being
subjectively
preset.
addition,
our
reveals
inherent
hierarchical
structure
variables,
characterizes
its
dominant
components
across
all
scales,
provides
potential
make
meaningful
interpretable.
advantages
were
illustrated
several
case
studies
natural
social
sciences.
proposed
versatile
flexible
so
it
applied
both
nongeographical
conducive
advancing
SSH-related
well.
This
study
new
way
thinking
advocating
law
advances
understanding
phenomena.
Water,
Journal Year:
2025,
Volume and Issue:
17(2), P. 230 - 230
Published: Jan. 16, 2025
Fujian
Province
is
an
important
soil
and
water
conservation
region
in
hilly
South
China.
However,
there
has
been
limited
attention
paid
to
the
assessment
of
production
at
provincial
level,
distribution
patterns
ecosystem
services
under
different
environmental
gradients
regions
have
not
revealed.
This
study
evaluated
spatiotemporal
characteristics
yield
based
on
InVEST
model
2000,
2010,
2020,
explored
their
differences
six
gradients:
elevation,
slope,
terrain
position
index,
geomorphy,
LULC,
NDVI.
The
results
statistics
showed
significant
spatial
differentiation
temporal
change
yield;
changes
both
exhibited
obvious
clustering
cold
hot
spots
(low
high
values);
cities
were
higher
than
those
conservation.
index
Geodetector
that
retention
gradients;
generally
lower
degree
more
sensitive
response
factors
(slope,
TPI,
DEM).
high-value
1000
2160
m
for
DEM,
25°
70.2°
0.81
1.42
medium
mountain
forest
land
0.9
0.92
NDVI,
which
indicates
mountainous
with
altitude,
steep
slopes,
changes,
vegetation
coverage.
exhibit
distributions
across
gradients,
should
be
adapting
local
conditions
ecological
environment
development.
Scientific Data,
Journal Year:
2024,
Volume and Issue:
11(1)
Published: June 15, 2024
Abstract
In
low-
and
middle-income
countries,
the
substantial
costs
associated
with
traditional
data
collection
pose
an
obstacle
to
facilitating
decision-making
in
field
of
public
health.
Satellite
imagery
offers
a
potential
solution,
but
image
extraction
analysis
can
be
costly
requires
specialized
expertise.
We
introduce
SatelliteBench,
scalable
framework
for
satellite
vector
embeddings
generation.
also
propose
novel
multimodal
fusion
pipeline
that
utilizes
series
metadata.
The
was
evaluated
generating
dataset
12,636
images
accompanied
by
comprehensive
metadata,
from
81
municipalities
Colombia
between
2016
2018.
then
3
tasks:
including
dengue
case
prediction,
poverty
assessment,
access
education.
performance
showcases
versatility
practicality
offering
reproducible,
accessible
open
tool
enhance
International Journal of Geographical Information Science,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 27
Published: Nov. 14, 2024
Spatial
interpolation
is
essential
for
handling
sparsity
and
missing
spatial
data.
Current
machine
learning-based
methods
are
subject
to
the
statistical
constraints
of
stratified
heterogeneity
(SSH),
normally
involving
separate
modeling
each
stratum
simple
weighted
averaging
integrate
intra-stratum
inter-strata
features.
However,
these
models
overlook
different
contributions
features
locations
within
a
(heterogeneous
associations,
HIA)
explanation
effects
on
process,
leading
suboptimal
unreliable
outcomes.
This
article
proposes
novel
explainable
method
considering
SSH
(X-SSHM).
environmental
utilized
describe
information,
which
fed
into
random
forest-based
learners
achieve
high-level
semantic
feature
mapping.
Geographically
regression
employed
unified
expression
HIA,
obtaining
final
result.
Shapley
(GSHAP)
proposed
decompose
marginal
Model
performance
evaluated
simulated
soil
organic
matter
datasets.
X-SSHM
outperformed
five
baselines
regarding
accuracy.
Moreover,
validated
X-SSHM's
ability
elucidate
mechanisms
by
SSH,
autocorrelation
HIA
affect
model
process.
